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000-103 AIX 6.1 Basic Operations

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000-103 exam Dumps Source : AIX 6.1 Basic Operations

Test Code : 000-103
Test designation : AIX 6.1 Basic Operations
Vendor designation : IBM
: 81 real Questions

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IBM AIX 6.1 Basic Operations

WebSphere vs. .internet: IBM and Microsoft snap head to head | real Questions and Pass4sure dumps

After undertaking a few benchmarks, Microsoft concluded that .internet presents superior performance and cost-efficiency ratio than WebSphere. IBM rebutted Microsoft’s findings and performed different assessments proving that WebSphere is advanced to .internet. Microsoft answered through rejecting a few of IBM’s claims as deceptive and repeating the assessments on distinctive hardware with separate consequences.


Microsoft has benchmarked .net and WebSphere and published the benchmark source code, hasten suggestions, utilize guidelines and a findings record published at entitled Benchmarking IBM WebSphere 7 on IBM Power6 and AIX vs. Microsoft .internet on HP BladeSystem and windows Server 2008.   This benchmark suggests a lots larger transactions per 2nd (TPS) cost and improved cost/efficiency ratio when the utilize of WebSphere 7 on home windows Server 2008 over WebSphere on AIX 5.3, and even more suitable results when the utilize of .net on windows Server 2008 over WebSphere on the very OS. The can charge/efficiency ratio for the utility benchmark used is:

IBM vigour 570 with WebSphere 7 and AIX 5.three HP BladeSystem C7000 with WebSphere 7 and home windows Server 2008 HP BladeSystem C7000 with .web and home windows Server 2008 $32.45 $7.92 $three.ninety nine

IBM has rebutted Microsoft’s benchmark and known as some of their claims as false, and performed a special benchmark, with distinctive outcomes. The benchmark used together with the findings acquire been posted in Benchmarking AND BEATING Microsoft’s .net three.5 with WebSphere 7! (PDF). The source code of the benchmark turned into now not posted. The effects point to WebSphere as an improved performing core-tier than .net with 36% extra TPS for one application benchmark and from 176% to 450% improved throughput for one in sum IBM’s ordinary benchmarks.

Microsoft spoke back to IBM and defended their claims and benchmarking outcomes with Response to IBM’s Whitepaper Entitled Benchmarking and Beating Microsoft .web three.5 with WebSphere 7 (PDF). Microsoft has additionally re-run their benchmark, modified to consist of a separate verify current corresponding to the one used by IBM of their assessments, operating it on separate hardware, a unique multi-core server, founding that indeed WebSphere is stronger than .net if using IBM’s notice at various movement but best a cramped bit improved, between 3% and %6, no longer as suggested by using IBM. anyway that, these later findings don't change the common ones given that the benchmark was hasten on a different hardware configuration. within the end, Microsoft invites IBM to “an unbiased lab to execute additional checking out”.

Microsoft trying out .web towards WebSphere

Microsoft has conducted a train of checks evaluating WebSphere/Java in opposition t .web on three different platforms. The details of the benchmarks carried out and the verify results were posted in the whitepaper entitled Benchmarking IBM WebSphere® 7 on IBM® Power6™ and AIX vs. Microsoft® .internet on Hewlett Packard BladeSystem and windows Server® 2008 (PDF).

platforms proven:

  • IBM vigor 570 (power 6) running IBM WebSphere 7 on AIX 5.3
  • 8 IBM Power6 cores at 4.2GHz
  • 32 GB RAM
  • AIX 5.3
  • 4 x 1 GB NICs
  • Hewlett Packard BladeSystem C7000 running IBM WebSphere 7 on home windows Server 2008
  • four Hewlett Packard ProLiant BL460c blades
  • One Quad-Core Intel® Xeon® E5450 (three.00GHz, 1333MHz FSB, 80W) Processor/blade
  • 32 GB RAM/blade
  • home windows Server 2008/sixty four-bit/blade
  • 2 x 1 GB NICs/blade
  • Hewlett Packard BladeSystem C7000 running .internet on home windows Server 2008
  • identical because the ancient one however the functions proven hasten on .net in its Place of WebSphere.
  • a number of three checks acquire been carried out on every platform:

  • exchange web software Benchmarking The purposes proven acquire been IBM’s change 6.1 and Microsoft’s StockTrader 2.04. This collection of assessments acquire evaluated the performance of comprehensive facts-pushed internet applications working on usurp of the above mentioned systems. The internet pages accessed had one or constantly more operations serviced by using courses contained with the aid of the enterprise layer and ending with synchronous database calls.
  • trade middle Tier net functions Benchmarking This benchmark was intended to measure the performance of the net service layer executing operations which ended up in database transactions. The verify changed into akin to internet utility, however operations acquire been counted in my opinion.
  • WS examine web capabilities Benchmarking This notice at various turned into just like the outdated one but there was no enterprise docile judgment nor database entry. This become based on WSTest workload originally devised by using sun and augmented by Microsoft. The features tier provided three operations: EchoList, EchoStruct and GetOrder. Having no company logic, the verify measured most efficient the raw performance of the net service software.
  • Two database configurations were used, one for the all-IBM platform and a different for the different two: IBM DB2 V9.5 commercial enterprise version with IBM DB2 V9.5 JDBC drivers for facts access and SQL Server 2008 databases commercial enterprise version. Two databases acquire been deploy for every configuration operating on HP BL680c G5 blades:

  • 4 Quad-Core Intel XEON CPUs, @2.4GHZ (16 cores in each blade)
  • sixty four GB RAM
  • four x 1GB NICs
  • IBM DB 9.5 enterprise edition sixty four-bit or Microsoft SQL Server 2008 sixty four-bit
  • Microsoft windows Server 2008 sixty four-bit, enterprise version
  • 2 4GB HBAs for fiber/sans entry to the EVA 4400 storage
  • The storage became secured on HP StorageWorks EVA 4400 Disk Array:

  • 96 15K drives total
  • 4 analytic volumes along with 24 drives each and every
  • Database server 1: analytic extent 1 for logging
  • Database server 1: analytic extent 2 for database
  • Database server 2: analytic extent 3 for logging
  • Database server 2: analytic extent four for database
  • The internet utility benchmark used 32 client machines working examine scripts. every computer simulated hundreds of purchasers having a 1 2d suppose time. The tests used an tailored version of IBM’s exchange 6.1 utility on SUT #1 & #2 and Microsoft’s StockTrader utility on SUT #3.


    For the net provider and WSTest benchmarks, Microsoft used 10 valued clientele with a 0.1s suppose time. For WSTest, the databases acquire been not accessed. Microsoft has created a WSTest-compliant benchmark for WebSphere 7 and JAX-WS and another in C# for .web using WCF.


    Microsoft’s whitepaper incorporates greater details on how the checks had been carried out together with the DB configuration, DB access used, caching configuration, notice at various scripts, tuning parameters used and others.


    The benchmarking consequences including the expenses/efficiency ratio are proven in the following table:

      IBM vigor 570 with WebSphere 7 and AIX 5.three HP BladeSystem C7000 with WebSphere 7 and home windows Server 2008 HP BladeSystem C7000 with .web and windows Server 2008 total center-Tier materiel cost $260,128.08 $87,161.00 $50,161.00 exchange internet utility Benchmark 8,016 TPS eleven,004 TPS 12,576 TPS charge/performance $32.forty five $7.92 $three.99 exchange core Tier internet provider Benchmark 10,571 TPS 14,468 TPS 22,262 TPS cost/performance $24.61 $6.02 $2.25 WSTest EchoList test10,536 TPS 15,973 TPS 22,291 TPS can charge/performance $24.sixty nine $5.46 $2.25 WSTest EchoStruct examine11,378 TPS 16,225 TPS 24,951 TPS can charge/efficiency $22.86 $5.37 $2.01 WSTest GetOrder test11,009 TPS 15,491 TPS 27,796 TPS cost/performance $23.sixty three $5.63 $1.80

    according to Microsoft’s benchmarking results, running WebSphere on HP BladeSystem with windows Server 2008 is set 30% extra productive and the can charge-efficiency ratio is 5 instances lower than working WebSphere on IBM vigour 570 with AIX 5.3. The .internet/windows Server 2008 configuration is much more efficient and the cost/performance ratio drops to half compared to WebSphere/windows Server 2008 and it is 10 times smaller than WebSphere/energy 570/AIX. The charge-performance ratio is so unreasonable for the primary platform because the fee of the complete core-tier is over $250,000 whereas the performance is decrease than the other systems.

    Microsoft’s benchmarking whitepaper (PDF) includes an appendix with complete particulars of the hardware and software fees. The benchmarking checks used, together with supply code, are posted on StockTrader site.

    IBM’s Rebuttal

    In one other paper, Benchmarking AND BEATING Microsoft’s .web three.5 with WebSphere 7! (PDF), IBM has rejected Microsoft’s benchmark and created one other one displaying that WebSphere is performing more suitable than .web.

    Microsoft had observed that StockTrader is comparable to IBM’s exchange application:

    Microsoft created an utility that's functionally comparable to the IBM WebSphere exchange software, both in terms of consumer performance and middle-tier database access, transactional and messaging conduct.

    IBM rejected Microsoft’s claim:

    The software claims to be “functionally equivalent” to the IBM WebSphere exchange 6.1 sample software. It isn't a “port” of the application in any sense. Little, if any, of the fashioned software design turned into ported. Microsoft has made this an utility that showcases using its proprietary technologies. a major indication of here's the indisputable fact that the .internet StockTrader application is not a universally available net software for the understanding that it will probably best be accessed by using information superhighway Explorer, and never by passage of different internet browsers.

    furthermore, IBM noted that change become now not designed to benchmark WebSphere’s efficiency however reasonably to

    serve as a sample application illustrating the usage of the points and functions contained in WebSphere and how they concerning utility efficiency. moreover, the utility served as a pattern which allowed developers to explore the tuning capabilities of WebSphere.

    IBM had other complaints regarding Microsoft’s benchmark:

    Microsoft created a totally new utility [StockTrader] and claimed useful equivalence at the utility stage. The fact is that the Microsoft version of the application used proprietary SQL statements to entry the database, not like the customary version of change 6.1 which turned into designed to be a transportable and commonplace software.

    They employed customer facet scripting to shift one of the vital software function to the customer.

    They established internet functions capabilities by means of inserting an pointless HTTP server between the WebSphere server and the customer.

    And If that changed into now not satisfactory, they failed to correctly pomp screen and regulate the WebSphere utility server to achieve peak efficiency.

    IBM’s aggressive job office group (CPO) has ported StockTrader 2.0 to WebSphere developing CPO StockTrader and claiming: “we did a port that faithfully reproduced Microsoft’s application design. The intent was to achieve an apples-to-apples comparison.” So, trader 6.1 became ported by passage of Microsoft from WebSphere to .internet below the designation StockTrader and ported once again with the aid of IBM returned to WebSphere beneath the designation CPO StockTrader. IBM benchmarked CPO StockTrader against StockTrader and obtained stronger consequences for WebSphere against .web:


    IBM has likewise recommended they are the utilize of pleasant fiscal institution, an application supposititious to benchmark WebSphere in opposition t .web. in this notice at various WebSphere outperforms .web a pair of instances:


    in their StockTrader vs. CPO StockTrader benchmark, IBM used scripts simulating user undertaking: “login, getting costs, stock purchase, inventory promote, viewing of the account portfolio, then a logoff” and operating in stress mode devoid of believe times. 36 clients acquire been simulated, sufficient to drive every server at maximum throughput and utilization. The statistics back turned into validated and mistake acquire been discarded.

    The entrance finish turned into carried out with WebSphere 7/home windows Server 2008 in a unique case and .web three.5 with IIS 7/home windows Server 2008 within the other. The returned conclusion database turned into DB2 8.2 and SQL Server 2005, each on home windows Server 2003.

    The hardware used for trying out become:

    performance checking out device HardwareX345 8676 Server2 X three.06 GHz Intel Processor with Hyper Thread Technology8 GB RAM18.2 GB 15K rpm SCSC tough Disk Drive1 GB Ethernet interfaceApplication Server Hardware IBM X3950 Server, 8 x three.50 Ghz, Intel Xeon Processors with Hyper Thread know-how, sixty four GB RAMDatabase Server HardwareX445 8670 Server, 8x 3.0 Ghz. Intel Xeon Processors with Hyper Thread expertise, 16 GB RAMUltraSCSI 320 Controller , EXP 300 SCSI expansion Unit, 14x 18.2 GB 15K rpm difficult Disk pressure configured as 2 Raid Arrays.One for Logs & One for Database, each and every array is constituted of 7 difficult disks in a Raid 0 configuration.The Ethernet community spine The isolated community hardware is made from 3x 3Comm SuperStack 4950 switches and one 3 Comm SuperStack 4924 switch operating at 1 GB.

    The software and hardware configuration for the pleasant bank benchmark turned into comparable to the StockTrader one.

    IBM’s whitepaper incorporates counsel concerning the friendly bank software, but doesn't component to the supply code. It likewise mentions that the application was originally designed for .net Framework 1.1 and changed into just recompiled on .net three.5 without being up to date to compose utilize of the newest applied sciences.

    Microsoft Response to IBM’s Rebuttal

    Microsoft has answered to IBM’s rebuttal in yet yet another whitepaper, Response to IBM’s Whitepaper Entitled Benchmarking and Beating Microsoft .internet three.5 with WebSphere 7 (PDF). in this doc, Microsoft defends their customary benchmarking consequences and affirms that IBM made some deceptive claims in their rebuttal doc entitled Benchmarking AND BEATING Microsoft’s .web 3.5 with WebSphere 7!, and IBM did not utilize an usurp benchmarking procedure.  more has been posted at

    really, Microsoft observed privilege here claims are false:

  • IBM claim: The .net StockTrader does not faithfully reproduce the IBM trade application performance.Microsoft response: this declare is false; the .internet StockTrader 2.04 faithfully reproduces the IBM WebSphere alternate application (using ordinary .net Framework technologies and coding practices), and may be used for just benchmark comparisons between .net 3.5 and IBM WebSphere 7.
  • IBM claim: The .net StockTrader uses customer-aspect script to shift processing from the server to the client.Microsoft response: this declare is false, there is no client-aspect scripting in the .web StockTrader software.
  • IBM declare: The .internet StockTrader uses proprietary SQL.Microsoft response: the .net StockTrader uses regular SQL statements coded for SQL Server and/or Oracle; and offers an information entry layer for each. The IBM WebSphere 7 trade application in a similar passage uses JDBC queries coded for DB2 and/or Oracle. Neither implementation makes utilize of saved tactics or features; sum company logic runs in the application server. simple pre-prepared SQL statements are used in both purposes.
  • IBM claim: The .internet StockTrader is not programmed as a universally available, skinny-customer net software. hence it runs best on IE, not in Firefox or other browsers.Microsoft response: in fact, the .net StockTrader web tier is programmed as a universally obtainable, unadulterated thin client net software. however, a simple problem in theuse of HTML remark tags factors concerns in Firefox; these remark tags are being updated to permit the application to correctly render in any industry commonplace browser, including Firefox.
  • IBM claim: The .internet StockTrader has errors beneath load.Microsoft response: here's false, and this doc contains additional benchmark checks and Mercury LoadRunner details proving this IBM pretense to be false.
  • also, Microsoft complained that IBM had developed friendly fiscal institution for .net Framework 1.1 years in the past the usage of out of date technologies:

    IBM’s friendly bank benchmark makes utilize of an out of date .net Framework 1.1 software that comprises technologies equivalent to DCOM which acquire been obsolete for many years. This benchmark should still be utterly discounted except Microsoft has the casual to overview the code and replace it for .net 3.5, with more recent technologies for ASP.web, transactions, and home windows communique basis (WCF) TCP/IP binary remoting (which replaced DCOM because the favorite remoting expertise).

    Microsoft considered IBM failed by passage of no longer featuring the supply code for CPO StockTrader and pleasant fiscal institution functions and reiterated the indisputable fact that sum of the supply code for Microsoft’s benchmark applications worried in this case had been made public.

    Microsoft additionally noticed that IBM had used a modified check script which “blanketed a heavier emphasis on buys and additionally blanketed a promote operation”. Microsoft re-performed their benchmark using IBM’s modified check script stream, one including the operations purchase and sell beside Login, Portfolio, Logout, on a unique 4-core utility server putting forward that

    these checks are in response to IBM’s revised script and are supposititious to meet some of these IBM rebuttal test situations as outlined in IBM’s response paper. They should not be regarded in any method as a change to their accustomed outcomes (performed on distinctive hardware, and distinctive check script circulation); because the long-established results remain valid.

    The verify changed into carried on:

    software Server(s) Database(s) 1 HP ProLiant BL460c1 Quad-core Intel Xeon E5450 CPU (three.00 GHz)32 GB RAM2 x 1GB NICsWindows Server 2008 sixty four-bit.internet three.5 (SP1) 64-bitIBM WebSphere sixty four-bit 1 HP ProLiant DL380 G52 Quad-core Intel Xeon E5355 CPUs (2.67 GHz)sixty four GB RAM2 x 1GB NICsWindows Server 2008 sixty four-bitSQL Server 2008 sixty four-bitDB2 V9.7 sixty four-bit

    The result of the verify indicates an identical performance for WebSphere and .web.


    one in every of IBM’s complaints had been that Microsoft inserted an pointless HTTP net server in front of WebSphere reducing the variety of transactions per 2d. Microsoft admitted that, however brought:

    using this HTTP Server become totally discussed within the common benchmark paper, and is finished based on IBM’s personal most usurp apply deployment instructions for WebSphere. In one of these setup, IBM recommends the usage of the IBM HTTP Server (Apache) because the entrance finish net Server, which then routes requests to the IBM WebSphere application server. In their checks, they co-located this HTTP on the very desktop as the utility Server. this is equivalent to the .web/WCF internet carrier checks, the Place they hosted the WCF internet functions in IIS 7, with co-discovered IIS 7 HTTP Server routing requests to the .internet application pool processing the WCF service operations. So in each tests, they tested an equivalent setup, the usage of IBM HTTP Server (Apache) as the entrance conclusion to WebSphere/JAX-WS capabilities; and Microsoft IIS 7 because the entrance finish to the .net/WCF services. for this reason, they stand behind sum their common effects.

    Microsoft performed yet a different verify, the WSTest, without the middleman HTTP internet server on a unique quad-core server just like the outdated one, and acquired privilege here influence:


    each tests carried out by Microsoft on a unique server exhibit WebSphere protecting a mild performance potential over .net but no longer as a lot as IBM pretended of their paper. anyway that, Microsoft remarked that IBM didn't finger upon middle-tier can freight comparison which vastly favors Microsoft.

    Microsoft persevered to challenge IBM to

    meet us [Microsoft] in an impartial lab to operate further checking out of the .internet StockTrader and WSTest benchmark workloads and pricing evaluation of the center tier software servers validated in their benchmark record. moreover, they invite the IBM aggressive response crew to their lab in Redmond, for discussion and additional checking out of their presence and under their assessment.

    remaining Conclusion

    often, a benchmark contains

  • a workload
  • a set of rules describing how the workload is to be processed – hasten guidelines -
  • a manner trying to be sure that the hasten suggestions are revered and results are interpreted correctly
  • A benchmark is constantly supposititious to evaluate two or more programs as a passage to check which one is more suitable for performing sure tasks. Benchmarks are additionally used by companies to improve their hardware/application earlier than it goes to their purchasers through checking out diverse tuning parameters and measuring the consequences or by means of spotting some bottlenecks. Benchmarks can likewise be used for advertising and marketing functions, to prove that a sure device has better performance than the competitor’s.

    within the beginning, benchmarks had been used to measure the hardware performance of a gadget, like the CPU processing energy. Later, benchmarks acquire been created to test and evaluate applications like SPEC MAIL2001 and even application servers like SPECjAppServer2004.

    There isn't any consummate benchmark. The workload can be tweaked to covet a undeniable platform, or the records can likewise be misinterpreted or incorrectly extrapolated. To be convincing, a benchmark has to be as transparent as viable. The workload definition should still be public, and if workable the source code may still be made obtainable for these interested to notice at. a transparent set of hasten rules are necessary so different parties can iterate the equal exams to behold the results for themselves. the style effects are interpreted and their which means requisite to be disclosed.

    We don't look to be conscious about a response from IBM to Microsoft’s closing paper. it could be entertaining to behold their reaction. probably, the most desirable solution to pellucid issues up is for IBM to compose the supply code of their checks public so anybody interested might notice at various and behold for themselves where is the fact. except then they can best speculate on the correctness and validity of these benchmarks.

    IBM i market Survey Fills within the Blanks | real Questions and Pass4sure dumps

    The IBM midrange group has a attractiveness for keeping the status quo. but that doesn’t insinuate it’s proof against trade. Shifts within the economic system, the expanding pressures from commerce managers to outcome extra with less, and the awareness that aggressive talents comes with modernization mingle to disrupt status quo thinkers. but does it in reality? statistics that pertain to IBM i stores are pretty much non-existent. a new stack of assistance coming from a survey conducted through HelpSystems adjustments that.

    The finished consequences of the survey acquire yet to be made public. however I’ve realized a pair of issues which are fantastic. for example:

    About sixty three % of the IBM i groups during this survey are running the 7.1 edition of the working system. And 24 % are at 6.1. mixed the total is 87 %, which leaves simplest single-digit percentages for 7.2, V5R3, and the early releases.

    IBM i 6.1 and 7.1 dominate because the most regular models of the working gadget, in line with the survey effects.

    fit these numbers with these:

    Of the survey takers, 38 percent utilize a unique power techniques server to hasten their businesses, and 50 % spoke of that they had between two and 5 IBM i techniques carrying the workloads. My arithmetic competencies lead me to the conclusion that 88 percent of sum survey takers well into the five-servers-or-much less class. Then factor into those numbers multiple IBM i partition being used by sixty two percent of the survey group.

    IBM i shops with between two and five servers outnumbered retail outlets with best a unique server in keeping with survey responses.

    according to what you recognize to this point, would you guess there's a more suitable number of taking allotment groups with fewer than 1,000 personnel or a superior number with greater than 1,000 personnel?

    The survey identifies basically 60 p.c in the smaller workforce category and that leaves 40 percent within the 1,000-employees-and-up category.

    software modernization tops the checklist of “considerations” for sum collaborating companies, with 59 p.c checking that field. 2nd on the list of issues is unreasonable availability. Third is the dwindling cadaver of workers with IBM i abilities.

    here is simply the tip of the iceberg. And what i will partake today is fairly primary stuff, even though it provides colour to an otherwise blurry photograph of what the IBM i community looks like.

    When the complete document is released in March, it will encompass details that expand the data. as an instance, there will be statistics regarding using partitions that may likewise be compared with the server facts outlined above. And together with that may be statistics regarding relocating servers to off-site places and tended to my managed carrier suppliers.

    other survey questions drunk into themes akin to commerce intelligence and records analytics, tape backup and catastrophe recuperation, the frequency of AIX and Linux on the equal vigor Server as IBM i and on other servers in the IT department.

    The degree of self credit that should still be placed in this survey falls short of one hundred percent. pomp me a survey that is irrefutable and i’ll pomp you an exceptional gold nugget (or accuse you of selling swamp land in Florida). but, on the very least, this places handles on a pot filled with topics that acquire relied on choicest guesses and hoped for outcomes.

    the vast majority of this information become gathered in September and October 2014. HelpSystems encouraged participation through sending emails to an inventory of its consumers and possibilities. if you are an avid reader of The four Hundred, you’ll stand in mind an article titled “attempting to find IBM i solutions” that additionally encouraged the IBM i group to buy allotment in this survey.

    IT Jungle and PowerWire participated within the edifice of the survey and are offering unique coverage of the effects.

    the entire number of surveys gathered and tabulated was 350, with sum however 52 of these coming from North the us.

    I behold this preliminary survey as a baseline for measuring shifts with persevered measurements in the future. developments are intricate to establish and not using a foundation. You acquire to know the Place you started to know how some distance you’ve come. This lays the groundwork for additional surveys, analysis, and reporting.

    by itself, as unique reference, it offers records from which evaluations can be made. It reveals fees of pride/dissatisfaction and the prevalence/scarcity of particular products and applied sciences.

    It can likewise be a useful appliance to aid champion or validate IT strategies and method and used to discover developments that otherwise would acquire long past unnoticed.

    thought management and trusted consultant is enormously favored popularity that HelpSystems hopes to obtain by means of taking on this task. It has proved to be efficient during the past as PowerTech, a HelpSystems company, has produced a status of IBM i security record for 10 years.

    This survey and the white paper HelpSystems plans to unencumber in March add substantiation to enterprise/technology initiatives that are infrequently quantified by means of IBM or individuals of the IBM i ISV neighborhood.

    IT Jungle plans to publish greater particulars of this survey and evaluation of particular subject areas as that suggestions turns into attainable.

    To gain a duplicate of the survey and a white paper authored through HelpSystems’ vice president of technical capabilities Tom Huntington, ensue this hyperlink and fill out a web kindhearted along with your contact tips.

    connected stories

    below New CEO, HelpSystems Snaps Up vie Halcyon

    attempting to find IBM i answers

    HelpSystems Grows With RJS And Coglin Mill Acquisitions

    State Of IBM i security? Dismal As normal, PowerTech Says

    the most referred to IBM i trends And expertise

    assist/systems Buys Dartware To construct Out Heterogeneous Monitoring

    help/methods Buys point to off BI items from IBM

    home windows gadget Programming: manner management | real Questions and Pass4sure dumps

    This chapter explains the fundamentals of process administration and likewise introduces the primary synchronization operations and wait features that will be critical sum through the relaxation of the publication.

    This chapter is from the booklet 

    A procedure carries its personal impartial virtual address house with each code and facts, included from different processes. each and every system, in turn, carries one or greater independently executing threads. A thread running inside a process can execute application code, create new threads, create new unbiased processes, and control verbal exchange and synchronization among the many threads.

    by passage of creating and managing tactics, functions can acquire dissimilar, concurrent projects processing info, performing computations, or speaking with different networked programs. it's even workable to augment software efficiency with the aid of exploiting distinctive CPU processors.

    This chapter explains the basics of procedure management and additionally introduces the fundamental synchronization operations and wait capabilities that may be critical sum over the leisure of the publication.

    each procedure contains one or more threads, and the home windows thread is the simple executable unit; behold the subsequent chapter for a threads introduction. Threads are scheduled on the groundwork of the commonplace elements: availability of elements such as CPUs and actual reminiscence, priority, fairness, and the like. windows has long supported multiprocessor programs, so threads can be allocated to separate processors inside a laptop.

    From the programmer's perspective, each home windows technique includes elements such as the following accessories:

  • One or extra threads.
  • A digital tackle district that's separate from different processes' address spaces. be conscious that shared reminiscence-mapped info partake physical reminiscence, however the sharing methods will probably utilize diverse digital addresses to entry the mapped file.
  • One or extra code segments, including code in DLLs.
  • One or greater records segments containing global variables.
  • environment strings with environment variable suggestions, such because the existing search path.
  • The manner heap.
  • elements such as open handles and other lots.
  • every thread in a procedure shares code, world variables, atmosphere strings, and components. each thread is independently scheduled, and a thread has the following facets:

  • A stack for method calls, interrupts, exception handlers, and automated storage.
  • Thread local Storage (TLS)—An arraylike assortment of pointers giving every thread the capability to allocate storage to create its own pleasing records atmosphere.
  • An argument on the stack, from the growing thread, which is continually pleasing for every thread.
  • A context structure, maintained via the kernel, with computer register values.
  • figure 6-1 suggests a manner with a few threads. This determine is schematic and doesn't point out precise reminiscence addresses, neither is it drawn to scale.

    This chapter shows how to labor with processes which includes a unique thread. Chapter 7 shows how to utilize separate threads.

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    AIX 6.1 Basic Operations

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    Windows System Programming: Process Management | real questions and Pass4sure dumps

    This chapter explains the basics of process management and likewise introduces the basic synchronization operations and wait functions that will be vital throughout the repose of the book.

    This chapter is from the book 

    A process contains its own independent virtual address space with both code and data, protected from other processes. Each process, in turn, contains one or more independently executing threads. A thread running within a process can execute application code, create new threads, create new independent processes, and manage communication and synchronization among the threads.

    By creating and managing processes, applications can acquire multiple, concurrent tasks processing files, performing computations, or communicating with other networked systems. It is even workable to improve application performance by exploiting multiple CPU processors.

    This chapter explains the basics of process management and likewise introduces the basic synchronization operations and wait functions that will be vital throughout the repose of the book.

    Every process contains one or more threads, and the Windows thread is the basic executable unit; behold the next chapter for a threads introduction. Threads are scheduled on the basis of the accustomed factors: availability of resources such as CPUs and physical memory, priority, fairness, and so on. Windows has long supported multiprocessor systems, so threads can be allocated to separate processors within a computer.

    From the programmer's perspective, each Windows process includes resources such as the following components:

  • One or more threads.
  • A virtual address space that is separate from other processes' address spaces. Note that shared memory-mapped files partake physical memory, but the sharing processes will probably utilize different virtual addresses to access the mapped file.
  • One or more code segments, including code in DLLs.
  • One or more data segments containing global variables.
  • Environment strings with environment variable information, such as the current search path.
  • The process heap.
  • Resources such as open handles and other heaps.
  • Each thread in a process shares code, global variables, environment strings, and resources. Each thread is independently scheduled, and a thread has the following elements:

  • A stack for procedure calls, interrupts, exception handlers, and automatic storage.
  • Thread Local Storage (TLS)—An arraylike collection of pointers giving each thread the aptitude to allocate storage to create its own unique data environment.
  • An argument on the stack, from the creating thread, which is usually unique for each thread.
  • A context structure, maintained by the kernel, with machine register values.
  • Figure 6-1 shows a process with several threads. This pattern is schematic and does not witness actual reminiscence addresses, nor is it drawn to scale.

    This chapter shows how to labor with processes consisting of a unique thread. Chapter 7 shows how to utilize multiple threads.

    How to Create a Pokemon Spawn Locations Recorder with CouchDB | real questions and Pass4sure dumps

    In a previous article, you’ve been introduced to CouchDB. This time, you’re going to create a full-fledged app where you can apply the things you learned. You’re likewise going to learn how to secure your database at the finish of the tutorial.

    Overview of the Project

    You’re going to build a Pokemon spawn locations recorder.

    This will allow users to save the locations of the monsters they encounter on Pokemon Go. Google Maps will be used to search for locations and a marker placed to pinpoint the exact location. Once the user is satisfied with the location, the marker can be interacted with, when it will point to a modal box which allows the user to enter the designation of the Pokemon and save the location. When the next user comes along and searches the very location, the values added by previous users will be plotted in the map as markers. Here’s what the app will notice like:

    pokespawn screen

    The plenary source code for the project is available on Github.

    Setting Up the progress Environment

    If you don’t acquire a good, isolated dev environment set up, it’s recommended you utilize Homestead Improved.

    The box doesn’t approach with CouchDB installed, so you’ll requisite to outcome that manually; but not just unostentatious CouchDB. The app needs to labor with geo data (latitudes and longitudes): you’ll supply CouchDB with the bounding box information from Google Maps. The bounding box represents the district currently being shown in the map, and sum the previous coordinates users acquire added to that district would be shown on the map as well. CouchDB cannot outcome that by default, which is why you requisite to install a plugin called GeoCouch in order to give CouchDB some spatial superpowers.

    The simplest passage to outcome that is by means of the GeoCouch docker container. You can likewise try to install GeoCouch manually but it requires you to install CouchDB from source and configure it sum by hand. I don’t really recommend this method unless you acquire a unix beard.

    Go ahead and install Docker into the VM you’re using, and approach back here once you’re done.

    Installing GeoCouch

    First, clone the repo and navigate inside the created directory.

    git clone cd docker-geocouch

    Next, open the Dockerfile and replace the script for getting CouchDB with the following:

    # pick up the CouchDB source RUN cd /opt; wget${COUCH_VERSION}/a$ tar xzf /opt/apache-couchdb-${COUCH_VERSION}.tar.gz

    You requisite to outcome this because the download URL that’s currently being used is already failing.

    Build the docker image:

    docker build -t elecnix/docker-geocouch:1.6.1 .

    This will buy a while depending on your internet connection so snap grab a snack. Once it’s done, create the container and start it:

    docker create -ti -p 5984:5984 elecnix/docker-geocouch:1.6.1 docker start <container id>

    Once it has started, you can test to behold if it’s running by executing the following command:

    curl localhost:5984

    Outside the VM, if you forwarded ports properly, that’ll be:


    It should recur the following:

    {"couchdb":"Welcome","uuid":"2f0b5e00e9ce08996ace6e66ffc1dfa3","version":"1.6.1","vendor":{"version":"1.6.1","name":"The Apache Software Foundation"}}

    Note that I’ll constantly refer to throughout the article. This is the IP assigned to Scotchbox, which is the Vagrant box I used. If you’re using Homestead Improved, the IP is You can utilize this IP to access the app. If you’re using something else entirely, proper as needed.

    Setting Up the Project

    You’re going to utilize the Slim framework to quicken up the progress of the app. Create a new project using Composer:

    php composer create-project slim/slim-skeleton pokespawn

    pokespawn is the designation of the project, so snap ahead and navigate to that directory once Composer is done installing. Then, install the following extra packages:

    composer require danrovito/pokephp guzzlehttp/guzzle gregwar/image vlucas/phpdotenv

    Here’s a brief overview on each one:

  • danrovito/pokephp – for easily talking to the Pokemon API.
  • guzzlehttp/guzzle – for making requests to the CouchDB server.
  • gregwar/image – for resizing the Pokemon sprites returned by the Pokemon API.
  • vlucas/phpdotenv – for storing configuration values.
  • Setting Up the Database

    Access Futon from the browser and create a new database called pokespawn. Once created, snap inside the database and create a new view. You can outcome that by clicking on the view dropdown and selecting temporary view. Add the following inside the textarea for the Map Function:

    function(doc){ if(doc.doc_type == 'pokemon'){ emit(, null); } }

    create new view

    Once that’s done, click on the save as button, add pokemon as the designation of the design document, and by_name as the view name. Press on save to save the view. Later on, you’ll be using this view to insinuate Pokemon names based on what the user has entered.

    save view

    Next, create a design document for responding to spatial searches. You can outcome that by selecting Design documents in the view dropdown then click on new document. Once in the page for creating a design document, click on the add province button and add spatial as the province name, and the following as the value:

    { "points": "function(doc) {\n if (doc.loc) {\n emit([{\n type: \"Point\",\n coordinates: [doc.loc[0], doc.loc[1]]\n }], [, doc.sprite]);\n }};" }

    This design document utilizes the spatial functions provided by GeoCouch. The first thing it does is check whether the document has a loc province in it. The loc province is an array containing the coordinates of a specific location, with the first particular containing the latitude and the second particular containing the longitude. If the document meets this criteria, it uses the emit() function just like a common view. The key is a GeoJSON geometry and the value is an array containing the designation of the Pokemon and the sprite.

    When you compose a request to the design document, you requisite to specify the start_range and the end_range which has the format of a JSON array. Each particular can either be a number or a null. null is used if you want an open range. Here’s an illustration request:

    curl -X pick up --globoff '[-33.87049924568689,151.2149563379288]&end_range=[33.86709181198735,151.22298150730137]'

    And its output:

    { "update_seq": 289, "rows":[{ "id":"c8cc500c68f679a6949a7ff981005729", "key":[ [ -33.869107336588, -33.869107336588 ], [ 151.21772705984, 151.21772705984 ] ], "bbox":[ -33.869107336588, 151.21772705984, -33.869107336588, 151.21772705984 ], "geometry":{ "type":"Point", "coordinates":[ -33.869107336588, 151.21772705984 ] }, "value":[ "snorlax", "143.png" ] }] }

    If you want to learn more about what specific operations you can outcome with GeoCouch, be sure to read the documentation or the Wiki.

    Creating the Project

    Now you’re ready to write some code. First you’re going to buy a notice at the code for the back-end then snap on to the front-end code.

    Poke Importer

    The app requires some Pokemon data to be already in the database before it can be used, thus the requisite for a script that’s only executed locally. Create a poke-importer.php file at the root of your project directory and add the following:

    <?php require 'vendor/autoload.php'; set_time_limit(0); use PokePHP\PokeApi; use Gregwar\Image\Image; $api = new PokeApi; $client = new GuzzleHttp\Client(['base_uri' => '']); //create a client for talking to CouchDB $pokemons = $api->pokedex(2); //make a request to the API $pokemon_data = json_decode($pokemons); //convert the json response to array foreach ($pokemon_data->pokemon_entries as $row) { $pokemon = [ 'id' => $row->entry_number, 'name' => $row->pokemon_species->name, 'sprite' => "{$row->entry_number}.png", 'doc_type' => "pokemon" ]; //get image from source, save it then resize. Image::open("{$row->entry_number}.png") ->resize(50, 50) ->save('public/img/' . $row->entry_number . '.png'); //save the pokemon data to the database $client->request('POST', "/pokespawn", [ 'headers' => [ 'Content-Type' => 'application/json' ], 'body' => json_encode($pokemon) ]); resound $row->pokemon_species->name . "\n"; } echo "done!";

    This script makes a request to the Pokedex endpoint of the Pokemon API. This endpoint requires the ID of the Pokedex version that you want it to return. Since Pokemon snap only currently allows players to snare Pokemon from the first generation, supply 2 as the ID. This returns sum the Pokemon from the Kanto region of the original Pokemon game. Then loop through the data, extract sum the necessary information, save the sprite, and compose a new document using the extracted data.


    Open the src/routes.php file and add the following routes:

    <?php $app->get('/', 'HomeController:index'); $app->get('/search', 'HomeController:search'); $app->post('/save-location', 'HomeController:saveLocation'); $app->post('/fetch', 'HomeController:fetch');

    Each of the routes will respond to the actions that can be performed throughout the app. The root route returns the home page, the search route returns the Pokemon designation suggestions, the save-location route saves the location and the fetch route returns the Pokemon in a specific location.

    Home Controller

    Under the src directory, create an app/Controllers folder and inside create a HomeController.php file. This will execute sum the actions needed for each of the routes. Here is the code:

    <?php namespace App\Controllers; class HomeController { protected $renderer; public function __construct($renderer) { $this->renderer = $renderer; //the twig renderer $this->db = new \App\Utils\DB; //custom class for talking to couchdb } public function index($request, $response, $args) { //render the home page recur $this->renderer->render($response, 'index.html', $args); } public function search() { $name = $_GET['name']; //name of the pokemon being searched recur $this->db->searchPokemon($name); //returns an array of suggestions based on the user input } public function saveLocation() { $id = $_POST['pokemon_id']; //the ID assigned by CouchDB to the Pokemon recur $this->db->savePokemonLocation($id, $_POST['pokemon_lat'], $_POST['pokemon_lng']); //saves the pokemon location to CouchDB and returns the data needed to plot the pokemon in the map } public function fetch() { recur json_encode($this->db->fetchPokemons($_POST['north_east'], $_POST['south_west'])); //returns the pokemon's within the bounding box of Google map. } }

    The Home Controller uses the $renderer which is passed in via the constructor to render the home page of the app. It likewise uses the DB class which you’ll be creating shortly.

    Talking to CouchDB

    Create a Utils/DB.php file under the app directory. Open the file and create a class:

    <?php namespace App\Utils; class DB { }

    Inside the class, create a new Guzzle client. You’re using Guzzle instead of some of the PHP clients for CouchDB because you can outcome anything you want with it.

    private $client; public function __construct() { $this->client = new \GuzzleHttp\Client([ 'base_uri' => getenv('BASE_URI') ]); }

    The config is from the .env file at the root of the project. This contains the base URL of CouchDB.


    searchPokemon is answerable for returning the data used by the auto-suggest functionality. Since CouchDB doesn’t actually champion the like condition that you’re used to in SQL, you’re using a cramped hack to mimic it. The trick here is using start_key and end_key instead of just key which only returns exact matches. fff0 is one of the special unicode characters allocated at the very finish of the basic multilingual plane. This makes it a docile candidate for appending at the finish of the actual string being searched, which makes the repose of the characters become optional because of its towering value. Note that this hack only works for short words so it’s more than enough for searching for Pokemon names.

    public function searchPokemon($name) { $unicode_char = '\ufff0'; $data = [ 'include_docs' => 'true', 'start_key' => '"' . $name . '"', 'end_key' => '"' . $name . json_decode('"' . $unicode_char .'"') . '"' ]; //make a request to the view you created earlier $doc = $this->makeGetRequest('/pokespawn/_design/pokemon/_view/by_name', $data); if (count($doc->rows) > 0) { $data = []; foreach ($doc->rows as $row) { $data[] = [ $row->key, $row->id ]; } recur json_encode($data); } $result = ['no_result' => true]; recur json_encode($result); }

    makeGetRequest is used for performing the read requests to CouchDB and makePostRequest for write.

    public function makeGetRequest($endpoint, $data = []) { if (!empty($data)) { //make a pick up request to the endpoint specified, with the $data passed in as a query parameter $response = $this->client->request('GET', $endpoint, [ 'query' => $data ]); } else { $response = $this->client->request('GET', $endpoint); } recur $this->handleResponse($response); } private function makePostRequest($endpoint, $data) { //make a POST request to the endpoint specified, passing in the $data for the request body $response = $this->client->request('POST', $endpoint, [ 'headers' => [ 'Content-Type' => 'application/json' ], 'body' => json_encode($data) ]); recur $this->handleResponse($response); }

    savePokemonLocation saves the coordinates to which the Google map marker is currently pointing, along with the designation and the sprite. A doc_type province is likewise added for easy retrieval of sum the documents related to locations.

    public function savePokemonLocation($id, $lat, $lng) { $pokemon = $this->makeGetRequest("/pokespawn/{$id}"); //get pokemon details based on ID //check if supplied data are valid if (!empty($pokemon->name) && $this->isValidCoordinates($lat, $lng)) { $lat = (double) $lat; $lng = (double) $lng; //construct the data to be saved to the database $data = [ 'name' => $pokemon->name, 'sprite' => $pokemon->sprite, 'loc' => [$lat, $lng], 'doc_type' => 'pokemon_location' ]; $this->makePostRequest('/pokespawn', $data); //save the location data $pokemon_data = [ 'type' => 'ok', 'lat' => $lat, 'lng' => $lng, 'name' => $pokemon->name, 'sprite' => $pokemon->sprite ]; recur json_encode($pokemon_data); //return the data needed by the pokemon marker } recur json_encode(['type' => 'fail']); //invalid data }

    isValidCoordinates checks if the latitude and longitude values acquire a telling format.

    private function isValidCoordinates($lat = '', $lng = '') { $coords_pattern = '/^[+\-]?[0-9]{1,3}\.[0-9]{3,}\z/'; if (preg_match($coords_pattern, $lat) && preg_match($coords_pattern, $lng)) { recur true; } recur false; }

    fetchPokemons is the function that makes the request to the design document for spatial search that you created earlier. Here, you specify the southwest coordinates as the value for the start_range and the northeast coordinates as the value for the end_range. The response is likewise limited to the first 100 rows to obviate requesting too much data. Earlier, you’ve likewise seen that there are some data returned by CouchDB that aren’t really needed. It would be useful to extract and then recur only the data needed on the front-end. I chose to leave that as an optimization for another day.

    public function fetchPokemons($north_east, $south_west) { $north_east = array_map('doubleval', $north_east); //convert sum array items to double $south_west = array_map('doubleval', $south_west); $data = [ 'start_range' => json_encode($south_west), 'end_range' => json_encode($north_east), 'limit' => 100 ]; $pokemons = $this->makeGetRequest('/pokespawn/_design/location/_spatial/points', $data); //fetch sum pokemon's that are in the current area recur $pokemons; }

    handleResponse converts the JSON string returned by CouchDB into an array.

    private function handleResponse($response) { $doc = json_decode($response->getBody()->getContents()); recur $doc; }

    Open composer.json at the root directory and add the following privilege below the require property, then execute composer dump-autoload. This allows you to autoload sum the files inside the src/app directory and compose it available inside the App namespace:

    "autoload": { "psr-4": { "App\\": "src/app" } }

    Lastly, inject the Home Controller into the container. You can outcome that by opening the src/dependencies.php file and add the following to the bottom:

    $container['HomeController'] = function ($c) { recur new App\Controllers\HomeController($c->renderer); };

    This allows you to pass the Twig renderer to the Home Controller and makes HomeController accessible from the router.

    Home Page Template

    Now you’re ready to proceed with the front-end. First, create a templates/index.html file at the root of the project directory and add the following:

    <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1"> <title>PokéSpawn</title> <link rel="stylesheet" href="lib/picnic/picnic.min.css"> <link rel="stylesheet" href="lib/remodal/dist/remodal.css"> <link rel="stylesheet" href="lib/remodal/dist/remodal-default-theme.css"> <link rel="stylesheet" href="lib/javascript-auto-complete/auto-complete.css"> <link rel="stylesheet" href="css/style.css"> <link rel="icon" href="favicon.ico"><!-- by Maicol Torti --> </head> <body> <div id="header"> <div id="title"> <img src="img/logo.png" alt="logo" class="header-item" /> <h1 class="header-item">PokéSpawn</h1> </div> <input type="text" id="place" class="controls" placeholder="Where are you?"><!-- text province for typing the location --> </div> <div id="map"></div> <!-- modal for saving pokemon location --> <div id="add-pokemon" class="remodal" data-remodal-id="modal"> <h3>Plot Pokémon Location</h3> <form method="POST" id="add-pokemon-form"> <div> <input type="hidden" name="pokemon_id" id="pokemon_id"><!-- id of the pokemon in CouchDB--> <input type="hidden" name="pokemon_lat" id="pokemon_lat"><!--latitude of the red marker --> <input type="hidden" name="pokemon_lng" id="pokemon_lng"><!--longitude of the red marker --> <input type="text" name="pokemon_name" id="pokemon_name" placeholder="Pokémon name"><!--name of the pokemon whose location is being added --> </div> <div> <button type="button" id="save-location">Save Location</button><!-- trigger the submission of location to CouchDB --> </div> </form> </div> <script src="lib/zepto.js/dist/zepto.min.js"></script><!-- event listening, ajax --> <script src="lib/remodal/dist/remodal.min.js"></script><!-- for modal box --> <script src="lib/javascript-auto-complete/auto-complete.min.js"></script><!-- for autocomplete text province --> <script src="js/main.js"></script> <script src="" defer></script><!-- for showing a map--> </body> </html>

    In the <head> are the styles from the various libraries that the app uses, as well as the styles for the app. In the <body> are the text province for searching locations, the map container, and the modal for saving a new location. Below those are the scripts used in the app. Don’t forget to replace YOUR_GOOGLEMAP_APIKEY in the Google Maps script with your own API key.


    For the main JavaScript file (public/js/main.js), first create variables for storing values that you will be needing throughout the entire file.

    var modal = $('#add-pokemon').remodal(); //initialize modal var map; //the google map var markers = []; //an array for storing sum the pokemon markers currently plotted in the map

    Next, create the function for initializing the map. A min_zoomlevel is specified to obviate users from zooming out until they can behold the entirety of the world map. You’ve already added a confine to the results that can be returned by CouchDB, but this is likewise a nice addition to obviate the users from expecting that they can select data from the entire world.

    function initMap() { var min_zoomlevel = 18; map = new google.maps.Map(document.getElementById('map'), { center: {lat: -33.8688, lng: 151.2195}, //set disableDefaultUI: true, //hide default UI controls zoom: min_zoomlevel, //set default zoom level mapTypeId: 'roadmap' //set sort of map }); //continue here... }

    Create the marker for pin-pointing locations that users want to add. Then, add an event listener for opening the modal for adding locations when the marker is pressed:

    marker = new google.maps.Marker({ map: map, position: map.getCenter(), draggable: true }); marker.addListener('click', function(){ var position = marker.getPosition(); $('#pokemon_lat').val(; $('#pokemon_lng').val(position.lng());; });

    Initialize the search box:

    var header = document.getElementById('header'); var input = document.getElementById('place'); var searchBox = new google.maps.places.SearchBox(input); //create a google map search box map.controls[google.maps.ControlPosition.TOP_LEFT].push(header); //position the header at the top left side of the screen

    Add various map listeners:

    map.addListener('bounds_changed', function() { //executes when user drags the map searchBox.setBounds(map.getBounds()); //make places inside the current district a priority when searching }); map.addListener('zoom_changed', function() { //executes when user zooms in or out of the map //immediately set the zoom to the minimum zoom flat if the current zoom goes over the minimum if (map.getZoom() < min_zoomlevel) map.setZoom(min_zoomlevel); }); map.addListener('dragend', function() { //executes the minute after the map has been dragged //loop through sum the pokemon markers and remove them from the map markers.forEach(function(marker) { marker.setMap(null); }); markers = []; marker.setPosition(map.getCenter()); //always Place the marker at the center of the map fetchPokemon(); //fetch some pokemon in the current viewable area });

    Add an event listener for when the Place in the search box changes.

    searchBox.addListener('places_changed', function() { //executes when the Place in the searchbox changes var places = searchBox.getPlaces(); if (places.length == 0) { return; } var bounds = new google.maps.LatLngBounds(); var Place = places[0]; //only pick up the first place if (!place.geometry) { return; } marker.setPosition(place.geometry.location); //put the marker at the location being searched if (place.geometry.viewport) { // only geocodes acquire viewport bounds.union(place.geometry.viewport); } else { bounds.extend(place.geometry.location); } map.fitBounds(bounds); //adjust the current map bounds to that of the Place being searched fetchPokemon(); //fetch some Pokemon in the current viewable area });

    The fetchPokemon function is answerable for fetching the Pokemon that were previously plotted in the currently viewable district of the map.

    function fetchPokemon(){ //get the northeast and southwest coordinates of the viewable district of the map var bounds = map.getBounds(); var north_east = [bounds.getNorthEast().lat(), bounds.getNorthEast().lng()]; var south_west = [bounds.getSouthWest().lat(), bounds.getSouthWest().lng()]; $.post( '/fetch', { north_east: north_east, south_west: south_west }, function(response){ var response = JSON.parse(response); response.rows.forEach(function(row){ //loop through sum the results returned var position = new google.maps.LatLng(row.geometry.coordinates[0], row.geometry.coordinates[1]); //create a new google map position //create a new marker using the position created above var poke_marker = new google.maps.Marker({ map: map, title: row.value[0], //name of the pokemon position: position, icon: 'img/' + row.value[1] //pokemon image that was saved locally }); //create an infowindow for the marker var infowindow = new google.maps.InfoWindow({ content: "<strong>" + row.value[0] + "</strong>" }); //when clicked it will point to the designation of the pokemon poke_marker.addListener('click', function() {, poke_marker); }); markers.push(poke_marker); }); } ); }

    This is the code for adding the auto-suggest functionality of the text province for entering the designation of a Pokemon. A renderItem function is specified to customize the HTML used for rendering each suggestion. This allows you to add the ID of the Pokemon as a data ascribe which you then utilize to set the value of the pokemon_id province once a suggestion is selected.

    new autoComplete({ selector: '#pokemon_name', //the text province to add the auto-complete source: function(term, response){ //use the results returned by the search route as a data source $.getJSON('/search?name=' + term, function(data){ response(data); }); }, renderItem: function (item, search){ //the code for rendering each suggestions. search = search.replace(/[-\/\\^$*+?.()|[\]{}]/g, '\\$&'); var re = new RegExp("(" + search.split(' ').join('|') + ")", "gi"); recur '<div class="autocomplete-suggestion" data-id="' + item[1] + '" data-val="' + item[0] + '">' + item[0].replace(re, "<b>$1</b>")+'</div>'; }, onSelect: function(e, term, item){ //executed when a suggestion is selected $('#pokemon_id').val(item.getAttribute('data-id')); } });

    When the save Location button is pressed, a request is made to the server to add the Pokemon location to CouchDB.

    $('#save-location').click(function(e){ $.post('/save-location', $('#add-pokemon-form').serialize(), function(response){ var data = JSON.parse(response); if(data.type == 'ok'){ var position = new google.maps.LatLng(, data.lng); //create a location //create a new marker and utilize the location var poke_marker = new google.maps.Marker({ map: map, title:, //name of the pokemon position: position, icon: 'img/' + data.sprite //pokemon image }); //create an infowindow for showing the designation of the pokemon var infowindow = new google.maps.InfoWindow({ content: "<strong>" + + "</strong>" }); //show designation of pokemon when marker is clicked poke_marker.addListener('click', function() {, poke_marker); }); markers.push(poke_marker); } modal.close(); $('#pokemon_id, #pokemon_lat, #pokemon_lng, #pokemon_name').val(''); //reset the form }); }); $('#add-pokemon-form').submit(function(e){ e.preventDefault(); //prevent the shape from being submited on enter }) Styles

    Create a public/css/styles.css file and add the following styles:

    html, cadaver { height: 100%; margin: 0; padding: 0; } #header { text-align: center; } #title { float: left; padding: 5px; color: #f5716a; } .header-item { padding-top: 10px; } h1.header-item { font-size: 14px; margin: 0; padding: 0; } #map { height: 100%; } .controls { margin-top: 10px; border: 1px solid transparent; border-radius: 2px 0 0 2px; box-sizing: border-box; -moz-box-sizing: border-box; height: 32px; outline: none; box-shadow: 0 2px 6px rgba(0, 0, 0, 0.3); } #place { background-color: #fff; margin-left: 12px; padding: 0 11px 0 13px; text-overflow: ellipsis; width: 300px; margin-top: 20px; } #place:focus { border-color: #4d90fe; } #type-selector { color: #fff; background-color: #4d90fe; padding: 5px 11px 0px 11px; } #type-selector label { font-family: Roboto; font-size: 13px; font-weight: 300; } #target { width: 345px; } .remodal-wrapper { z-index: 100; } .remodal-overlay { z-index: 100; } Securing CouchDB

    By default CouchDB is open to all. This means that once you expose it to the internet, anyone can wreak havoc in your database. Anyone can outcome any database operation by simply using Curl, Postman or any other appliance for making HTTP requests. In fact, this temporary status even has a name: the “admin party”. You’ve seen this in action in the previous tutorial and even when you created a new database, a view and a design document earlier. sum of these actions can only be performed by the server admin but you’ve gone ahead and done it without logging in or anything. still not convinced? Try executing this on your local machine:

    curl -X save

    You’ll pick up the following as a response if you don’t already acquire a server admin on your CouchDB installation:


    Yikes, right? The docile word is there’s an easy fix. sum you acquire to outcome is create a server admin. You can outcome so with the following command:

    curl -X save -d '"mysupersecurepassword"'

    The command above creates a new server admin named “kami” with the password “mysupersecurepassword”.

    By default, CouchDB doesn’t acquire any server admin so once you create one, the admin party is over. Note that server admins acquire god-like powers so you’re probably better off creating only one or two. Then create a handful of database admins who can only execute CRUD operations. You can outcome so by executing the following command:

    curl -HContent-Type:application/json -vXPUT http://kami:mysupersecurepassword@ --data-binary '{"_id": "org.couchdb.user:plebian","name": "plebian","roles": [],"type": "user","password": "mypass"}'

    If successful, it will recur a response similar to the following:

    * Trying * Connected to ( port 5984 (#0) * Server auth using Basic with user 'root' > save /_users/org.couchdb.user:plebian HTTP/1.1 > Host: > Authorization: Basic cm9vdDpteXN1cGVyc2VjdXJlcGFzc3dvcmQ= > User-Agent: curl/7.47.0 > Accept: */* > Content-Type:application/json > Content-Length: 101 > * upload completely sent off: 101 out of 101 bytes < HTTP/1.1 201 Created < Server: CouchDB/1.6.1 (Erlang OTP/R16B03) < Location: < ETag: "1-9c4abdc905ecdc9f0f56921d7de915b9" < Date: Thu, 18 Aug 2016 07:57:20 GMT < Content-Type: text/plain; charset=utf-8 < Content-Length: 87 < Cache-Control: must-revalidate < {"ok":true,"id":"org.couchdb.user:plebian","rev":"1-9c4abdc905ecdc9f0f56921d7de915b9"} * Connection #0 to host left intact

    Now you can try the very command from earlier with a different database name:

    curl -X save

    And CouchDB will bellow at you:

    {"error":"unauthorized","reason":"You are not a server admin."}

    For this to work, you now acquire to supply your username and password in the URL like so:

    curl -X save http://{your_username}:{your_password}@

    Ok, so that’s it? Well, not really because the only thing you’ve done is confine database operations that can only be done by server admins. This includes things like creating a new database, deleting a database, managing users, full-admin access to sum databases (including system tables), CRUD operations to sum documents. This leaves you with unauthenticated users still having the power to outcome CRUD stuff on any database. You can give this a try by logging out of Futon, pick any database you want to mess around with and outcome CRUD stuff in it. CouchDB will still happily execute those operations for you.

    So, how outcome you patch up the remaining holes? You can outcome that by creating a design document that will check if the username of the user who is trying to execute a write operation (insert or update) is the very as the designation of the user that’s allowed to outcome it. In Futon, log in using a server admin or database admin account, select the database you want to labor with, and create a new design document. Set the ID as _design/blockAnonymousWrites, add a province named validate_doc_update, and set the value to the following:

    function(new_doc, old_doc, userCtx){ if( != 'kami'){ throw({forbidden: "Not Authorized"}); } }

    The new version of the document, the existing document, and the user context are passed in as an argument to this function. The only thing you requisite to check is the userCtx which contains the designation of the database, the designation of the user who’s doing the operation, and an array of roles assigned to the user.

    A secObj is likewise passed as the fourth argument, but you don’t really requisite to labor on it; that’s why it’s omitted. Basically, the secObj describes what admin privileges acquire been set on the database.

    Once you’ve added the value, save the design document, log out, and try to create a new document or update an existing one and watch CouchDB complain at you.

    block anonymous writes

    Since you’re only checking for the username, you might be thinking that attackers can simply guess the username and supply any value to the password and it would work. Well, not really, because CouchDB first checks if the username and password are reform before the design document even gets executed.

    Alternatively, if you acquire many users in a unique database, you can likewise check for the role. The function below will sling an mistake at any user who doesn’t acquire the role of “pokemon_master”.

    function(new_doc, old_doc, userCtx) { if(userCtx.roles.indexOf('pokemon_master') == -1){ throw({forbidden: "Not Authorized"}); } }

    If you want to learn more about how to secure CouchDB, be sure to check out the following resources:

    Securing the App

    Let’s wrap up by updating the app to utilize the security measures that you’ve applied to the database. First update the .env file: change the BASE_URI with just the IP address and the port, and then add the username and password of the CouchDB user that you’ve created.

    BASE_URI="" COUCH_USER="plebian" COUCH_PASS="mypass"

    Then, update the constructor of the DB class to utilize the new details:

    public function __construct() { $this->client = new \GuzzleHttp\Client([ 'base_uri' => 'http://' . getenv('COUCH_USER') . ':' . getenv('COUCH_PASS') . '@' . getenv('BASE_URI') ]); } Conclusion

    That’s it! In this tutorial, you learned how to create a Pokemon spawn locations recorder app with CouchDB. With the serve of the GeoCouch plugin, you were able to execute spatial queries, and you learned how to secure your CouchDB database.

    Do you utilize CouchDB in your projects? What for? Any suggestions / features to add into this cramped project of ours? Let us know in the comments!

    Wern is a web developer from the Philippines. He loves edifice things for the web and sharing the things he has learned by writing in his blog. When he's not coding or learning something new, he enjoys watching anime and playing video games.

    LSI Nytro WarpDrive WLP4-200 Enterprise PCIe Review | real questions and Pass4sure dumps

    August 17th, 2012 by Kevin OBrien

    The LSI Nytro WarpDrive WLP4-200 represents LSI's second-generation trouble in the enterprise PCIe application acceleration space. LSI builds on an extensive history of enterprise storage products with the newly rebranded line of acceleration products dubbed LSI Nytro. The Nytro family includes the PCIe WarpDrive of course, but likewise encompasses LSI's Nytro XD caching and Nytro MegaRAID products that leverage brilliant caching with on-board twinkle for acceleration, offering customers an entire suite of options as they evaluate high-performance storage. The Nytro WarpDrive comes in a variety of configurations, including both eMLC and SLC versions, with capacities ranging from 200GB up to 1.6TB.

    Like the WarpDrive SLP-300 predecessor, the new Nytro WarpDrives labor in much the very passage RAIDing multiple SSDs together. The Nytro WarpDrive uses fewer controllers/SSDs this time around, opting for four instead of six in the original. The controllers acquire likewise been updated; the Nytro WarpDrive utilizes four latest-generation LSI SandForce SF-2500 controllers that are paired with SLC or eMLC NAND depending on the model. These SSDs are then joined together in RAID0 through an LSI PCIe to SAS bridge to shape a 200GB to 1600GB analytic obstruct device. The drive is then presented to the operating system, which in this case could weigh in multiple Windows, Linux, UNIX variants, with a well-established LSI driver that in many cases is built into the OS itself.

    In addition to LSI's renowned host compatibility and stability reputation, the other core technology component of the Nytro WarpDrive are the SandFroce controllers. LSI used the prior generation SF-1500 controllers in the SLP-300 first generation PCIe card; this time around they're using the SF-2500 family. While the controller itself has improved, there's likewise the added engineering benefit now that LSI has acquired SandForce. While the results may be more subtle, the benefits are there nonetheless and involve improved champion for the drive via firmware updates and generally a more tightly integrated unit.

    While stability and consistent performance across operating systems are important, those features just open the door. Performance is key and the Nytro WarpDrive doesn't disappoint. At the top end, the cards deliver sequential 4K IOPS of 238,000 read and 133,000 write, along with sequential 8K IOPS of 189,000 read and 137,000 write. Latency is the other just as vital performance spec; the Nytro WarpDrive posts latency as low as 50 microseconds.

    In this review they apply their plenary suite of enterprise benchmarks, across both Windows and Linux, with a robust set of comparables, including the prior generation LSI card and other leading application accelerators. Per their accustomed depth sum of their particular performance charts and content is delivered on a unique page to compose consumption of these data points as easy as possible.

    LSI Nytro WarpDrive Specifications

  • Single flat Cell (SLC)
  • 200GB Nytro WarpDrive WLP4-200
  • Sequential IOPS (4K) - 238,000 Read, 133,000 Write
  • Sequential Read and Write IOPS (8K) - 189,000 Read, 137,000 Write
  • Bandwidth (256K) - 2.0GB/s Read, 1.7GB/s Write
  • 400GB Nytro WarpDrive WLP4-400
  • Sequential IOPS (4K) - 238,000 Read, 133,000 Write
  • Sequential Read and Write IOPS (8K) - 189,000 Read, 137,000 Write
  • Bandwidth (256K) - 2.0GB/s Read, 1.7GB/s Write
  • Enterprise Multi flat Cell (eMLC)
  • 400GB Nytro WarpDrive BLP4-400
  • Sequential IOPS (4K) - 218,000 Read, 75,000 Write
  • Sequential Read and Write IOPS (8K) - 183,000 Read, 118,000 Write
  • Bandwidth (256K) - 2.0GB/s Read, 1.0GB/s Write
  • 800GB Nytro WarpDrive BLP4-800
  • Sequential IOPS (4K) - 218,000 Read, 75,000 Write
  • Sequential Read and Write IOPS (8K) - 183,000 Read, 118,000 Write
  • Bandwidth (256K) - 2.0GB/s Read, 1.0GB/s Write
  • 1600GB Nytro WarpDrive BLP4-1600
  • Sequential IOPS (4K) - 218,000 Read, 75,000 Write
  • Sequential Read and Write IOPS (8K) - 183,000 Read, 118,000 Write
  • Bandwidth (256K) - 2.0GB/s Read, 1.0GB/s Write
  • Average Latency < 50 microseconds
  • Interface - x8 PCI Express 2.0
  • Power Consumption - <25 watts
  • Form Factor - Low Profile (half-length, MD2)
  • Environmentals Operational at 0 to 45C
  • OS Compatiblity
  • Microsoft: Windows XP, Vista, 2003, 7; Windows Server 2003 SP2, 2008 SP2, 2008 R2 SP1
  • Linux: CentOS 6; RHEL 5.4, 5.5, 5.6, 5.7, 6.0, 6.1; SLES: 10SP1, 10SP2, 10SP4, 11SP1; OEL 5.6, 6.0
  • UNIX: FreeBSD 7.2, 7.4, 8.1, 8.2; Solaris 10U10, 11 (x86 & SPARC)
  • Hypervisors: VMware 4.0 U2, 4.1 U1, 5.0
  • End of Life Data Retention >6 months SLC, >3 months eMLC
  • Product Health Monitoring Self-Monitoring, Analysis and Reporting Technology (SMART) commands, plus additional SSD monitoring
  • Build and Design

    The LSI Nytro WarpDrive is a Half-Height Half-Length x8 PCI-Express card comprised of four custom form-factor SSDs connected in RAID0 to a main interface board. Being a half-height card, the Nytro WarpDrive is compatibile with more servers by simply swapping the backplane adapter. Shown below is their Lenovo ThinkServer RD240, used in many of their enterprise tests, which supports full-height cards.

    Similar to the previous-generation WarpDrive, LSI uses SandForce processors at the heart of the new Nytro WarpDrive. While the previous generation model used six SATA 3.0Gb/s SF-1500 controllers, the Nytro uses four SATA 6.0Gb/s SF-2500 controllers. The Nytro houses two of these SSDs in two sandwiched heatsink "banks" which are connected to the main board with a tiny ribbon cable. To interface these controllers with the host computer, LSI uses their own SAS2008 PCIe to SAS bridge, which has wide driver champion across multiple operating systems.

    Unlike the first-generation WarpDrive, these passive heatsinks allow the NAND and SandForce controllers to shed heat into a heatsink first, which then gets passively cooled by airflow in the server chassis. This reduces hot-spots and ensures more stable hardware performance over the life of the product.

    A view from above the card shows the tightly sandwiched aluminum plates below, between, and on top of the custom SSDs that power the Nytro WarpDrive. The Nytro likewise supports legacy HDD indicator lights, for those who want that flat of monitoring to be externally visible.

    The LSI Nytro WarpDrive is fully PCIe 2.0 x8 power compliant, and only consumes <25 watts of power during its operation. This allows it to operate without any external power attached and gives it more hardware compatibility over devices such as the Fusion-io "Duo" devices that require external power (or champion for drawing power over PCIe spec) to operate at plenary performance.

    Each of the four SSDs powering the 200GB SLC LSI Nytro WarpDrive has one SandForce SF-2500 controller, and eight 8GB Toshiba SLC Toggle NAND pieces. This gives each SSD a total capacity of 64GB, which is then over-provisioned 22% to acquire a usable capacity of 50GB.


    To manage their Nytro WarpDrive products, LSI gives customers the CLI Nytro WarpDrive Management Utility. The management utility allows users to update the firmware, monitor the drive's health, as well as format the WarpDrive to distinction capacities by adjusting the flat of over-provisioning. Multiple versions of the utility are offered depending on the OS that's required, with Windows, Linux, FreeBSD, Solaris, and VMware supported.

    The Nytro WarpDrive Management Utility is as basic as they come, giving users just enough information or options to pick up the job done. With most of the time spent with these cards in production, you won't find many IT guys loading this utility up on a day to day basis, although the amount of information felt lacking compared to what other vendors offer.

    From a health monitoring aspect, the LSI management utility really only works to order you the exact temperature and yes/no response when it comes to figuring out how far into useful life the WarpDrive is. With a percentage reading of Warranty Remaining giving some indication of health, a particular pattern of total bytes written or total bytes read would be much better at letting the user know just how much the card has been used and how much life the future holds for it.

    Another feature that the utility offers that wasn't supported by the first-generation WarpDrive, is the aptitude to change the over-provisioning flat of the analytic obstruct device. In a stock configuration the their 200GB SLC Nytro WarpDrive had a usable capacity of 186.26GB, while the performance over-provisioning mode dropped that amount to 149.01GB. A third mode of max capacity over-provisioning was likewise listed, although it wasn't supported on their model.

    Nytro WarpDrive Formatting Modes (for 200GB SLC):

  • Performance over-provisioning - 149.01GB
  • Nominal over-provisioning - 186.26GB
  • Max capacity over provisioning - Not supported on their review model
  • Testing Background and Comparables

    When it comes to testing enterprise hardware, the environment is just as vital as the testing processes used to evaluate it. At StorageReview they present the very hardware and infrastructure establish in many datacenters where the devices they test would ultimately be destined for. This includes enterprise servers as well as proper infrastructure materiel like networking, rack space, power conditioning/monitoring, and same-class comparable hardware to properly evaluate how a device performs. not a bit of their reviews are paid for or controlled by the manufacturer of the materiel they are testing; with material comparables picked at their discretion from products they acquire in their lab.

    StorageReview Enterprise Testing Platform:

    Lenovo ThinkServer RD240

  • 2 x Intel Xeon X5650 (2.66GHz, 12MB Cache)
  • Windows Server 2008 criterion Edition R2 SP1 64-Bit and CentOS 6.2 64-Bit
  • Intel 5500+ ICH10R Chipset
  • Memory - 8GB (2 x 4GB) 1333Mhz DDR3 Registered RDIMMs
  • Review Comparables:

    640GB Fusion-io ioDrive Duo

  • Released: 1H2009
  • NAND Type: MLC
  • Controller: 2 x Proprietary
  • Device Visibility: JBOD, software RAID depending on OS
  • Fusion-io VSL Windows: 3.1.1
  • Fusion-io VSL Linux 3.1.1
  • 200GB LSI Nytro WarpDrive WLP4-200

  • Released: 1H2012
  • NAND Type: SLC
  • Controller: 4 x LSI SandForce SF-2500 through LSI SAS2008 PCIe to SAS Bridge
  • Device Visiblity: Fixed Hardware RAID0
  • LSI Windows:
  • LSI Linux: native CentOS 6.2 driver
  • 300GB LSI WarpDrive SLP-300

  • Released: 1H2010
  • NAND Type: SLC
  • Controller: 6 x LSI SandForce SF-1500 through LSI SAS2008 PCIe to SAS Bridge
  • Device Visiblity: Fixed Hardware RAID0
  • LSI Windows:
  • LSI Linus: native CentOS 6.2 driver
  • 1.6TB OCZ Z-Drive R4

  • Released: 2H2011
  • NAND Type: MLC
  • Controller: 8 x LSI SandForce SF-2200 through custom OCZ VCA PCIe to SAS Bridge
  • Device Visibility: Fixed Hardware RAID0
  • OCZ Windows Driver:
  • OCZ Linux Driver:
  • Enterprise Synthetic Workload Analysis (Stock Settings)

    The passage they notice at PCIe storage solutions dives deeper than just looking at traditional burst or steady-state performance. When looking at averaged performance over a long age of time, you lose sight of the details behind how the device performs over that entire period. Since twinkle performance varies greatly as time goes on, their new benchmarking process analyzes the performance in areas including total throughput, middling latency, peak latency, and criterion aberration over the entire preconditioning side of each device. With high-end enterprise products, latency is often more vital than throughput. For this understanding they snap to powerful lengths to point to the plenary performance characteristics of each device they save through their Enterprise Test Lab.

    We acquire likewise added performance comparisons to point to how each device performs under a different driver set across both Windows and Linux operating systems. For Windows, they utilize the latest drivers at the time of original review, which each device is then tested under a 64-bit Windows Server 2008 R2 environment. For Linux, they utilize 64-bit CentOS 6.2 environment, which each Enterprise PCIe Application Accelerator supports. Their main goal with this testing is to point to how OS performance differs, since having an operating system listed as compatible on a product sheet doesn't always weigh in the performance across them is equal.

    All devices tested snap under the very testing policy from start to finish. Currently, for each individual workload, devices are secure erased using the tools supplied by the vendor, preconditioned into steady-state with the identical workload the device will be tested with under cumbersome load of 16 threads with an outstanding queue of 16 per thread, and then tested in set intervals in multiple thread/queue depth profiles to point to performance under light and cumbersome usage. For tests with 100% read activity, preconditioning is with the very workload, although flipped to 100% write.

    Preconditioning and Primary Steady-State Tests:

  • Throughput (Read+Write IOPS Aggregate)
  • Average Latency (Read+Write Latency Averaged Together)
  • Max Latency (Peak Read or Write Latency)
  • Latency criterion aberration (Read+Write criterion aberration Averaged Together)
  • At this time Enterprise Synthetic Workload Analysis includes four common profiles, which can attempt to reflect real-world activity. These were picked to acquire some similarity with their past benchmarks, as well as a common ground for comparing against widely published values such as max 4K read and write speed, as well as 8K 70/30 commonly used for enterprise drives. They likewise included two legacy mixed workloads, including the traditional File Server and Webserver offering a wide mingle of transfer sizes. These terminal two will be phased out with application benchmarks in those categories as those are introduced on their site, and replaced with new synthetic workloads.

  • 4K
  • 100% Read or 100% Write
  • 100% 4K
  • 8K 70/30
  • File Server
  • 80% Read, 20% Write
  • 10% 512b, 5% 1k, 5% 2k, 60% 4k, 2% 8k, 4% 16k, 4% 32k, 10% 64k
  • Webserver
  • 100% Read
  • 22% 512b, 15% 1k, 8% 2k, 23% 4k, 15% 8k, 2% 16k, 6% 32k, 7% 64k, 1% 128k, 1% 512k
  • Looking at 100% 4K write activity under a cumbersome load of 16 threads and 16 queue over a 6 hour period, they establish that the LSI Nytro WarpDrive offered slower but very consistent throughput compared to the other PCIe Application Accelerators. The Nytro WarpDrive started at roughly 33,000 IOPS 4K write, and leveled off at 30,000 IOPS at the finish of this preconditioning phase. This compared to the first-generation WarpDrive that peaked at 130,000-180,000 IOPS and leveled off at 35,000 IOPS.

    Average latency during the preconditioning side quickly settled in at about 8.5ms, whereas the first-generation WarpDrive started around 2ms before tapering off to 7.2ms as it reached steady-state.

    When it comes to max latency there is almost no doubt that SLC is king in terms of spikes that are few and far between. The new Nytro WarpDrive had the lowest consistent max latency in Windows, which increased under its CentOS driver, but still remained very respectable.

    Looking at the latency criterion deviation, under Windows the Nytro WarpDrive offered some of the most consistent latency. matched by only the first-generation WarpDrive. In CentOS though, the criterion aberration was more than double, at over 20ms versus 7.2ms in Windows.

    After the PCIe Application Accelerators went through their 4K write preconditioning process, they sampled their performance over a longer interval. In Windows the LSI Nytro WarpDrive measured 161,170 IOPS read and 29,946 IOPS write, whereas its Linux performance measured 97,333 IOPS read and 29,788 IOPS write. Read performance in Windows and Linux was higher than the previous-generation WarpDrive, although 4K steady-state performance dropped 5,000 IOPS.

    The LSI Nytro WarpDrive offered the second to lowest 4K read latency, coming in behind the OCZ Z-Drive R4 that uses 8 SF-2200 controllers versus the Nytro WarpDrive's four SF-2500 controllers. Write latency was the slowest in the pack measuring 8.54ms in Windows and 8.591ms in Linux (not counting the OCZ Z-Drive R4 that was not even in the very ballpark).

    Looking at the highest peak latency over the duration of their final 4K read and write testing intervals, the LSI Nytro WarpDrive offered the lowest 4K write latency in the pack with 51ms in Windows. Its Linux performance measured 486ms, as well as a towering 4K read blip in Windows measuring 1,002ms, but overall it ranked well versus their other comparables.

    While peak latency will only point to the unique response time over an entire test, showing criterion aberration gives the entire picture as to how well the drive behaves over the entire test. The Nytro WarpDrive came in towards the middle of the pack, with read latency criterion aberration roughly twice that of the first-generation WarpDrive. criterion aberration in the write test was only slightly higher in Windows, but fell behind in Linux. In Windows, its write performance still came in towards the top of the pack, above the Fusion ioDrive Duo and OCZ Z-Drive R4.

    The next preconditioning test works with a more realistic read/write workload spread, versus the 100% write activity in their 4K test. Here, they acquire a 70% read and 30% write mingle of 8K transfers. Looking at their 8K 70/30 mixed workload under a cumbersome load of 16 threads and 16 queue over a 6 hour age the Nytro WarpDrive quickly leveled off at 87,000 IOPS, finishing as the fastest drive in the group in Windows. The Nytro WarpDrive levled off at around 70,000 IOPS in Linux, although that was still the fastest Linux performance in the group as well.

    In their 8K 70/30 16T/16Q workload, the LSI Nytro WarpDrive offered by far the most consistent middling latency, staying flat at 2.9ms throughout their Windows test, and 3.6ms in Linux.

    Similar to the conduct they measured in their 4K write preconditioning test, the SLC-based Nytro WarpDrive likewise offered extremely low peak latency over the duration of the 8K 70/30 preconditioning process. Its performance in Windows hovered around 25ms, while its Linux performance floated higher around 200ms.

    While peak latency over tiny intervals gives you an notion of how a device is performing in a test, looking at its criterion aberration shows you closely those peaks were grouped. The Nytro WarpDrive in Windows offered the lowest criterion aberration in the group, measuring almost half of the first-generation WarpDrive. In Linux the criterion aberration was much higher, by almost a factor of four, although that still ranked middle/top of the pack.

    Compared to the fixed 16 thread, 16 queue max workload they performed in the 100% 4K write test, their mixed workload profiles scale the performance across a wide range of thread/queue combinations. In these tests they span their workload intensity from 2 threads and 2 queue up to 16 threads and 16 queue. The LSI Nytro WarpDrive was able to present substantially higher performance at lower thread weigh workloads with a queue depth between 4 to 16. This edge played out largely over the entire test looking at its Windows performance, although in Linux that edge was capped to roughly 70,000 IOPS where the R4 (in Windows) was able to beat it in some areas.

    On the other half of through throughput equation, the LSI Nytro WarpDrive consistently offered some of the lowest latency in their 8K 70/30 tests. In Windows, the Nytro WarpDrive came in at the top of the pack, while the Z-Drive R4 in Windows beat the Nytro's performance in Linux.

    In their 8K 70/30 test the SLC-based LSI Nytro WarpDrive in Windows had more 1,000ms+ peak latency spikes, whereas the Linux driver kept that suppressed until the higher 16-thread workloads. While this conduct didn't disagree from the Fusion ioDrive Duo or Z-Drive R4, it had more towering latency spikes than the first-generation WarpDrive in Windows, especially when under more demanding loads.

    While the occasional towering spikes might notice discouraging, the plenary latency picture can be seen when looking at the latency criterion deviation. In their 8K 70/30 workload, the LSI Nytro WarpDrive offered the lowest criterion aberration throughout the bulk of their 8K tests,

    The File Server workload represents a larger transfer-size spectrum hitting each particular device, so instead of settling in for a static 4k or 8k workload, the drive must cope with requests ranging from 512b to 64K. In their File Server throughput test, the OCZ Z-Drive R4 had a commanding lead in both burst and as it neared steady-state. The LSI Nytro WarpDrive started off towards the bottom of the pack between 39-46,000 IOPS, but remained their over the duration of the test, while the Fusion ioDrive Duo and first-generation WarpDrive slipped below it.

    Latency in their File Server workload followed a similar path on the LSI Nytro WarpDrive as it did in the throughput section, where it started off relatively towering in terms of its burst capabilities, but stayed there over the duration of the test. This constant as a rock performance allowed it to approach in towards the top of the pack, while the others eventually slowed down over the endurance section of the preconditioning phase.

    With its SLC NAND configuration, their 200GB Nytro WarpDrive remained rather detached over the duration of their File Server preconditioning test, offering some of the lowest latency spikes out of the bunch. In this section the first-generation WarpDrive offered similar performance, as did the Fusion ioDrive Duo, although the later had many spikes into the 1,000ms range.

    The LSI Nytro WarpDrive easily came out on top when looking at the latency criterion aberration in the File Server preconditioning test. With a unique spike, it was nearly flat at 2ms for the duration of this 6 hour process, and proved to be more consistent than the first-generation WarpDrive.

    Once their preconditioning process finished under a towering 16T/16Q load, they looked at File Server performance across a wide range of activity levels. Similar to the Nytro's performance in their 8K 70/30 workload, it was able to present the highest performance at low thread and queue depth levels. This lead was taken over by the OCZ Z-Drive R4 in the File Server workload at levels above 4T/8Q, where the R4's eight controller weigh helped it stretch its legs further. Over the remaining portion of their throughput test, the Nytro WarpDrive came in second under the Z-Drive R4 in Windows.

    With towering throughput likewise comes low middling latency, where the LSI Nytro WarpDrive was able to very docile response times at lower queue depths, measuring as low as 0.366ms at 2T/2Q. It wasn't the quickest though, as the ioDrive Duo held the top spot, measuring 0.248ms in the very portion of the test. As the loads increased though, the Nytro WarpDrive came in just under the OCZ Z-Drive R4, utilizing half the controllers.

    Comparing the File Server workload max latency between the OCZ Z-Drive R4 and the LSI Nytro WarpDrive, it's easy to behold what the edge of SLC NAND is. Over the duration of the different test loads, the SLC-based Nytro WarpDrive and first-generation WarpDrive both offered some of the lowest peak response times and fewest overall peaks.

    Our latency criterion aberration analysis reiterated that the Nytro WarpDrive was able to approach in with class-leading performance over the duration of their File Server workload. The one district where responsiveness started to slip was under at 16T/16Q workload, where the Nytro WarpDrive in Linux had more variation in its latency.

    Our terminal workload is rather unique in the passage they anatomize the preconditioning side of the test compared to the main output. As a workload designed with 100% read activity, it's difficult to point to each device's just read performance without a proper preconditioning step. To withhold the conditioning workload the very as the testing workload, they inverted the pattern to be 100% write. For this understanding the preconditioning charts are much more theatrical than the final workload numbers.

    While it didn't rotate into an illustration of behind and constant wins the race, the Nytro WarpDrive had the lowest burst throughput (not counting the R4's problematic Linux driver's performance), but as the other devices slowed towards the finish of the preconditioning process, the Nytro WarpDrive came in second Place under the R4 in Windows. This save it ahead of both the ioDrive Duo and first-generation WarpDrive under their cumbersome 16T/16Q inverted Web Server workload.

    Average latency of the Nytro WarpDrive in their Web Server preconditioning test stayed flat at 20.9ms over the duration of the test. This compared to 31ms from the first-generation WarpDrive towards the second half of the test.

    In terms of most responsive PCIe Application Accelerator, the LSI Nytro WarpDrive came in on top with its performance in Windows during their Web Server Preconditioning test. It kept its peak response times under 120ms in Windows, and privilege above 500ms in Linux.

    With barely a spike in their Web Server preconditioning test, the LSI Nytro WarpDrive impressed again with its incredibly low latency criterion deviation. In Windows, it offered the most consistent performance, coming out on top of the first-generation WarpDrive. Its performance in Linux didn't fare as well, but still came in towards the middle of the pack.

    Switching back to a 100% read Web Server workload after the preconditioning process, the OCZ Z-Drive R4 offered the highest performance in Windows, but only after an efficient queue depth of 32. Before that the Nytro WarpDrive was able to approach out on top with lower thread counts over a queue depth of 4. The leader in the low thread/low queue depth arena was still the Fusion ioDrive Duo.

    The LSI Nytro WarpDrive was able to present impressive low-latency in their Web Server workload, measuring as low as 0.267ms in Linux with a 2T/2Q load. Its highest middling response time was 4.5ms in Linux with a 16T/16Q load. Overall it performed very well, bested by only the OCZ Z-Drive R4 in Windows under higher efficient queue depths.

    All of the PCIe Application Accelerators suffered from some towering latency spikes in their Web Server test, with minimal differences between OS, controller or NAND type. Overall Linux was LSI's stalwart suit for both the Nytro WarpDrive and first-generation WarpDrive, having fewer latency spikes versus the performance in Windows.

    While the peak latency performance may look problematic, what really matters is how the device performs over the entire duration of the test. This is where latency criterion aberration comes in to play, measuring how consistent the latency was overall. While the LSI Nytro WarpDrive in Windows had more frequent spikes compared to its Linux performance, it had a lower criterion aberration in Windows under higher efficient queue depths.


    The LSI Nytro WarpDrive WLP4-200 represents a solid step forward for LSI's application acceleration line. It's generally quicker in most areas than the prior generation SLP-300, thanks to the updated SandForce SF-2500 controller and improved firmware used this time around. Structurally it's simpler as well, dropping from six drives in RAID0 to four. LSI has likewise added a bunch of capacity and NAND options for the Nytro WarpDrive line, giving buyers a range of options from 200GB in SLC up to 1.6TB in eMLC. Overall the offering is more complete and well-rounded, offering flexibillty which should augment the market adoption for the Nytro WarpDrive family at large. 

    A Big selling point for LSI is the compatibility of their products on a hardware and OS level. They noted stalwart performance from the Nytro WarpDrive in both their Windows and Linux tests. The Windows driverset was definitely more polished, offering much higher performance in some areas. While the ioDrive Duo likewise showed very docile multi-OS support, the very can not be said about OCZ's Z-Drive R4, which had a gigantic gap in performance between their Windows and Linux drivers.

    When it comes to management, LSI offers software tools to check the health and handle basic commands for most major operating systems. Their CLI WarpDrive Management Utility is basic, but still gets the job done when it comes to formatting or over-provisioning the drive. The software suite is certainly a bit spartan, but even these tools are appreciated as some in the PCIe storage space don't present much of anything when it comes to drive management. 

    The most surprising aspect of the LSI Nytro WarpDrive is its conduct in their enterprise workloads. Compared to other PCIe Application Accelerators we've tested, its burst performance wasn't the most impressive, but the fact that it remained rock solid over the duration of their tests was. What it lacked in quicken off the line, it more than made up for in consistent latency with incredibly low criterion aberration under load. For enterprise applications that claim a narrow window of acceptable response times under load, low max latency and criterion aberration seperate the men from the boys. It's likewise vital to recollect that SandForce-based drives acquire compression benefits that aren't highlighted in this sort of workload testing. For this understanding and to point to an even more complete profile of enterprise drive performance, StorageReview is currently edifice out a robust set of application-level benchmarks that may point to further differences between enterprise storage products. 


  • Increased performance while reducing controller count
  • Industry leading host system compatibility
  • More NAND and capacity options than previous-generation WarpDrive
  • Incredibly consistent latency under stress
  • Cons

  • Limited software tools for drive management
  • Weaker burst performance (excellent steady-state performance)
  • Bottom Line

    The LSI Nytro WarpDrive WLP4-200 is a solid PCIe application accelerator and will win over enterprise customers for its excellent constant status performance, consistent performance over a variety of uses, and class-leading compatibility with host systems. LSI did a docile job with the Nytro WarpDrive from hardware design to smooth operation, with their main complaints being around drive management tools. While it doesn't burst out of the gate as rapidly as others, that's usually not terribly vital to the enterprise and there's something to be said for a drive that works well out of the box, and continues to operate well, in just about any operating system. 

    LSI Application Acceleration Products

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    MORGAN Studio

    is specialized in Architectural visualization , Industrial visualization , 3D Modeling ,3D Animation , Entertainment and Visual Effects .