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M2090-744 IBM DB2 BLU/Cloud Sales Mastery v1

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M2090-744 exam Dumps Source : IBM DB2 BLU/Cloud Sales Mastery v1

Test Code : M2090-744
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Vendor appellation : IBM
: 15 true Questions

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IBM IBM DB2 BLU/Cloud Sales

IBM Touts BLU Acceleration great information technology Now in DB2 | killexams.com true Questions and Pass4sure dumps

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IBM pronounces recent Servers and tools for Hybrid Clouds | killexams.com true Questions and Pass4sure dumps

may 11, 2015

IBM nowadays introduced a combined package of recent servers and storage application and solutions in a circulation to speed up the development of hybrid cloud computing. The commerce additionally revealed bendy software licensing of its middleware to uphold customers speed up their adoption of hybrid cloud environments.

The aggregate of IBM power techniques servers, IBM Spectrum Storage, z techniques, IBM Middleware, IBM SoftLayer, and OpenStack utility can aid companies navigate between cloud and on-premises environments and profit advantageous insights on key company information wherever it is generated.

"IBM hybrid cloud solutions are developed for the enterprise and purchasers are the utilize of them to enable recent commerce fashions to drive growth," talked about Don Boulia, vp of cloud capabilities of IBM techniques. "Hybrid cloud computing requires recent degrees of openness, dynamic statistics administration, integration, automation and scalable efficiency in server, storage and utility technologies. IBM brings entire of those applied sciences collectively from on-premises   records facilities and inner public and personal clouds to greater successfully manage typical computing with recent mobile, great records, and sociable computing workloads."

among the recent bulletins is Rocket data entry service on Bluemix for z techniques, supposititious to give companies a connection to facts on the IBM z programs mainframe for construction of cell applications through Bluemix. birth in June, consumers can entry a free tribulation of the provider, which works with a sweep of database storage systems, including VSAM, ADABASE, IMS, CICS, and DB2, and makes it viable for access via mediocre cellular software interfaces, together with MongoDB, JDBC, and the rest protocol.

extra recent IBM techniques consist of IBM power tackle E850, a four-socket tackle with elastic capability and up to 70% guaranteed utilization. The E850 is targeted at cloud service providers or medium and massive organizations seeking to securely and efficaciously set up multi-tenancy workloads, while speeding access to facts with larger in-memory databases with as much as 4TB of installed memory, optimized for the peaks and valleys of company needs.

furthermore, the IBM vigour device E880, designed to scale to 192 cores, is pertinent for IBM DB2 with BLU Acceleration, bettering the efficiency of cloud deployments; and the PurePOWER device, a converged infrastructure for cloud, is meant to uphold convey insights within the cloud, and is managed with OpenStack.

The commerce furthermore will be delivery IBM Spectrum control Storage Insights, a brand recent software-defined storage reply offers data management as a hybrid cloud service to optimize on-premises storage infrastructures. Storage Insights is designed to simplify storage administration by using enhancing storage visibility and applies analytics to ease means planning, raise efficiency monitoring, and enrich storage utilization through reclaiming under-utilized storage. moreover, the IBM XIV GEN 3 is a brand recent system designed for cloud with real-time compression that enables scaling as exact for statistics storage means expands, the vendor provides.

IBM will offer a self-carrier portal the plot purchasers can scale their infrastructure and software license footprint in minutes the utilize of the PureApplication carrier later this quarter.

greater details are available at www.ibm.com.


IBM pushes MPP engine to enlarge cloud database capabilities line | killexams.com true Questions and Pass4sure dumps

IBM continues to update its dashDB relational facts warehouse system as participate of an exertion to extra its cloud database services portfolio. And the enterprise confirmed off dashDB and its latest addition to the technology -- aid for massively parallel processing (MPP) across clustered systems -- at a self-styled "boot camp" adventure in Boston ultimate week.

launched final fall, dashDB is according to the BLU Acceleration in-memory computing know-how from IBM's flagship DB2 relational database, however additionally brings IBM Netezza columnar-fashion processing to cloud implementations. As such, the software is designed to be a competitor to Amazon Redshift, the cloud records warehouse service that Amazon web services (AWS) brought to market at the discontinue of 2012.

Like other relational database providers, IBM has been pressed to reply to recent cloud choices -- exceptionally those from cloud computing chief AWS. final month, IBM announced an MPP edition of dashDB aimed at faster query processing and stronger scalability. uphold for the more and more accepted R analytical programming language is a different of IBM's fresh additions to dashDB.

The flat of R's integration with the cloud database become a plus within the eyes of 1 dashDB user from the massive records stronghold of digital promoting and marketing who spoke on the IBM Cloud information Boot Camp.

"From their component of view, dashDB is a columnar database with DB2 aspects that has R developed into it," said Shiv Sehgal, a options architect at RSG Media, an organization in huge apple that develops software to be used by television networks, publishers and different types of media businesses. In an interview, Sehgal stated the potential to supply handy entry to R to internal users and clients versed in it will be a crucial step in enabling commerce users to inquire of and reply analytical questions while not having to eddy to IT for assist.

massive records, huge kahuna

The rollout of dashDB has been gradual, but the know-how may hang tons of IBM's hopes for managing records within the cloud. Now, with MPP guide, dashDB can be the direction to the cloud for clients of DB2 and the Netezza statistics warehouse equipment.

"MPP basically is their huge kahuna -- with it, which you can add nodes as your warehousing wants develop," referred to John J. Park, dashDB product supervisor at IBM. "Strategically, here is the cloud providing to uphold their Netezza purchasers and DB2 valued clientele."

One abilities holdup for some clients: Park preeminent dashDB's compatibility with Netezza's implementation of the SQL programming language continues to be evolving. He estimated that Netezza SQL capabilities are presently coated in dashDB to the tune of eighty four%, including that IBM is calling to gain "ninety-plus-% compatibility" later this yr.

The dashDB advances escort IBM's acquisition final month of Compose Inc., a corporation in San Mateo, Calif., previously referred to as MongoHQ. Compose specializes in database as a service utility that automates the system of constructing, administering and scaling databases in the cloud. It has constructed up a great list of supported databases, birth with MongoDB, but moving on to encompass Elasticsearch, PostgreSQL, Redis and others. 

certainly one of IBM's targets in purchasing Compose is to enable builders to rapidly spin up circumstances of databases within the cloud. Compose's know-how and dashDB are available to builders through Bluemix, IBM's cloud platform as a provider (PaaS) offering. and that they're just a participate of IBM's becoming cloud database functions portfolio. IBM's cloud facts management crusade arguably kicked off in earnest early final year with its purchase of Cloudant Inc., the maker of utility in keeping with the Apache CouchDB challenge. Cloudant's NoSQL database is designed exceptionally to ply scalability and deployment concerns with relational databases used in cloud settings.

lots of users, a lot of facts

moreover the utilize of dashDB, RSG Media employs the Cloudant software as some thing of a knowledge lake to stage statistics for analytics, based on Sehgal. "Most critical is its scalability. it may tackle a gigantic scale of clients," he stated.

Sehgal and the users he supports even savor a lot of various kinds of facts to chew on. RSG's a number of techniques rob up net log and sociable media statistics, in addition to ratings, viewership and promoting information from information capabilities and advert platform suppliers, comparable to Nielsen, Rentrak and Operative Media.

One deliberate utilize of that records is enabling cable tv networks to appraise the profitability of programming choices -- as an example, when to flee Billy Madison on exact or Breaking unhealthy reruns. Such programming selections historically had been made by intestine intuition, however Sehgal said it really is changing, as election makers appear to be to utilize analytics tackle to gauge the cost of running a application versus the amount of cash or not it's more likely to gleam via cable fees or ad revenues.

The mixture of a NoSQL database and a SQL statistics warehouse supplied with the aid of the IBM cloud features portfolio brings every petite thing together, Sehgal talked about. "When it involves some of the functions we're doing, we're taking linear ad earnings records, Twitter data, [and] entire kinds of records. And to finally relate it returned to how a particular pomp is performing, they Do exigency a SQL approach." With the cloud, he delivered, "we are able to savor every thing in one area."

in line with a file launched by means of forecast enterprise research and Markets in January, the world marketplace for cloud-primarily based data administration functions is anticipated to develop at a compound annual cost of 30.5% -- from $3.51 billion in 2014 to $13.28 billion by means of 2019.

so far, a entire lot of the huge data cloud fanfare has gathered to startups working outdoor the relational mannequin. however fancy IBM, different established database avid gamers don't appear to be standing nevertheless. Oracle is making a great shove to construct up its cloud database features platform, together with a cloud edition of its NoSQL Database application; moreover, the latest release of Oracle Database 12c helps doc storage and SQL-based querying of JSON, an regularly-used format for cellular, web and cloud apps. And while working by itself columnar response to Amazon Redshift, Microsoft has additionally begun to promote DocumentDB, its NoSQL application for JSON that runs in its Azure cloud.


M2090-744 IBM DB2 BLU/Cloud Sales Mastery v1

Study pilot Prepared by Killexams.com IBM Dumps Experts


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M2090-744 exam Dumps Source : IBM DB2 BLU/Cloud Sales Mastery v1

Test Code : M2090-744
Test appellation : IBM DB2 BLU/Cloud Sales Mastery v1
Vendor appellation : IBM
: 15 true Questions

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Tried a lot to lucid my M2090-744 exam taking help from the books. But the intricate explanations and tough illustration made things worse and I skipped the test twice. Finally, my best friend suggested me the question & reply by killexams.com. And believe me, it worked so well! The quality contents were mighty to evanesce through and understand the topics. I could easily cram it too and answered the questions in barely 180 mins time. Felt elated to pass well. Thanks, killexams.com dumps. Thanks to my lovely friend too.


Feeling misfortune in passing M2090-744 exam? bank is here.
M2090-744 exam changed into my purpose for this yr. a very lengthy recent Years determination to save it in full M2090-744 . I honestly notionthat reading for this examination, making ready to pass and sitting the M2090-744 examination could be just as crazy as itsounds. luckily, i establish a few reviews of killexams.com on line and determined to apply it. It ended up being totally well worth it as the package deal had included each question I were given on the M2090-744 exam. I handed the M2090-744 totally strain-loose and came out of the testing middle lighthearted and cozy. simply well worth the cash, I suppose this is the nice exam enjoyfeasible.


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Big Blue's biggest mainframe yet is the size of a fridge | killexams.com true questions and Pass4sure dumps

At least twenty years after pundits first pronounced the death of the mainframe, IBM has released a recent one.

Of course, the proof of the pudding will be in the market, but IBM will be hoping that the billion dollars it's poured into developing the recent z13 mainframe will acquire the huge discontinue of town as excited as huge Blue itself is.

Ensuring that it won't be welcome in the UK after the next election, the z13 has enough grunt to ply “real time encryption of entire mobile transactions at any scale” – entire the course up to its claimed 2.5 billion transactions a day capacity, presumably.

The theory is that every e-commerce transaction touches off dozens of other system interactions, and that generic Intel-based systems won't scale up to ply them especially as mobility drives up the number of transactions.

As IBM's announcement claims: “z13 transactions are persistent, protected and auditable from end-to-end,” and built-in analytics let fraud detection flee against “100 per cent” of transactions.

IBM's  recent mainframe

We even hired a designer to give it exciting angles - the IBM z13 mainframe

IBM's enthusiasm for open-source pops up in various spots in the release: the machine supports Hadoop for unstructured data analysis, along with DB2 BLU running as an in-memory database on Linux, and the huge iron furthermore supports OpenStack. The latter will dovetail nicely into other cloud capabilities the company is highlighting, such as the capacity to flee 50 virtual servers per core, to a total of 8,000.

Those terminal two data intimate the fridge-sized z13 will currently flee 160 processor cores per cabinet. IBM reckons the processor pushing the z13 along runs at twice the speed of “the most common server processors” (nice qualification there), supports 300 per cent more memory, and with double the bandwidth and vector processing analytics.

Later this year, there'll furthermore be a recent z/OS software iteration to boost the thumper's in-memory analytics and analysis, once again pitched as a huge thing for the mobile business. ®


Exploring the AppDynamics Integration with OpenShift Container Platform | killexams.com true questions and Pass4sure dumps

This was originally posted on OpenShift’s blog.

Introduction

Regardless of whether you are developing traditional applications or microservices, you will inevitably savor a requirement to monitor the health of your applications, and the components upon which they are built.

Furthermore, users of OpenShift Container Platform will often savor their own existing enterprise gauge monitoring infrastructure into which they will be looking to integrate applications they build. As participate of Red Hat’s Professional Services organisation, one of the monitoring platforms I encounter whilst working with OpenShift in the realm is the AppDynamics SaaS offering.

In this post, I will flee through how they can rob a Source-to-Image (S2I) builder, customise it to add the monitoring agent, and then utilize it as the basis of a Fuse Integration Services application, written in Apache Camel, and using the Java CDI approach.

Register with AppDynamics

Before getting into the process of modifying the S2I builder image and building the application, the first thing they exigency to Do is register with the AppDynamics platform. If you’re an existing consumer of this service, then this step obviously isn’t required!

Either way, once registered, they exigency to download the Java agent. In this example, I’ve used the Standalone JVM agent, but there are many more options to select from, and one of those may better suit your requirements.

Adding the Agent to your Image

There are two primary ways you can evanesce about adding the AppDynamics Java agent to your image.

Firstly, you can use Source-To-Image (S2I) to add the Java agent to the standard fis-java-openshift base image at the very time as pulling in entire your other dependencies – mainly source code and libraries.

Secondly, you can extend the fis-java-openshift S2I builder image itself, add your own layer containing the Java agent, and utilize this recent image as the basis for your builds.

Using S2I

When using S2I to create an image, OpenShift can execute a number of scripts as participate of this process. The two scripts they are interested in in this context are assemble and run.

In the fis-java-openshift image, the S2I scripts are located in /usr/local/s2i. We can override the actions of these scripts by adding an .s2i/bin directory into the code repository, and creating their recent scripts there.

Assemble

The assemble script is going to be the script that pulls in the Java agent and unpacks it ready for use. Whilst they exigency to override it to carry out this task, they furthermore exigency it to carry on performing the tasks it currently performs in addition to any customisations they might add:

#!/bin/bash # flee original assemble script /usr/local/s2i/assemble # install appdynamics agent curl -H "Accept: application/zip" https://codeload.github.com/benemon/fis-java-appdynamics-plugin/zip/master -o /deployments/appdynamics.zip pushd /deployments unzip appdynamics.zip pushd fis-java-appdynamics-plugin-master/ mv appdynamics/ ../ popd rm -rf fis-java-appdynamics-plugin-master/ rm -f appdynamics.zip popd

As can be seen above, they actually acquire this script to execute the original assemble script before they add the AppDynamics agent – this way, if the Maven build fails, they haven’t wasted any time downloading any artifacts we’re not going to use.

Run

The flee script is going to be the script that sets up the environment to allow us to utilize the AppDynamics Java agent, and – you’ve guessed it – flee their app! Just as with the assemble script, they silent want run to carry on executing their application when their customisations are complete. Therefore, entire they Do here is acquire it to check for the presence of an environment variable, and if it’s found, configure the environment to utilize AppDynamics.

#!/bin/bash if [ x"$APPDYNAMICS_AGENT_ACCOUNT_NAME" != "x" ]; then mkdir /deployments/logs export JAVA_OPTIONS="-javaagent:/deployments/appdynamics/javaagent.jar -Dappdynamics.agent.logs.dir=/deployments/logs $JAVA_OPTIONS" fi exec /usr/local/s2i/run

In this case, we’re looking for a variable called APPDYNAMICS_AGENT_ACCOUNT_NAME. After all, if they haven’t configured any credentials for the Java agent, then it can’t connect to the AppDynamics SaaS anyway.

Template

Finally, to bring this entire together, we can utilize a Template to drag entire of these components together, launch the build process, and deploy their application.

The S2I process is possibly the simpler of the two methods outlined here for adding the AppDynamics Java agent to your application, but it does present some points of which you exigency to be aware:

  • The Java agent needs to be hosted somewhere accessible to your build process. It furthermore needs to be version controlled separately from the build, which adds extra build management overhead.
  • It will be downloaded every separate time you flee a build – not the most efficient course of deploying it if you savor an effective CI / CD pipeline and are doing multiple builds per hour!
  • Whilst it’s simpler to configure, it can present confusing problems during the build process. For example, if your assemble script creates some directories for your application to utilize (logging directories, for example), you may exigency to contemplate about how your build and application are being executed, and who owns what in that process.
  • Regardless of these minor issues, this is silent a powerful (and useful!) mechanism, and as such I savor provided a sample repository that allows you to execute an S2I build that should drag in the Java agent and flee it alongside an application.

    NOTE: If you’re silent interested in using the S2I process, and want to know more about how to configure the Java agent with environment variables, skip ahead to ‘Adding the AppDynamics agent to a FIS application’.

    Extending the Fuse Integration Services (FIS) base Image

    My preference for using the AppDynamics Java agent with applications built on FIS (and for similar utilize cases), is to add it into the base image once, so that it is accessible by the any applications based on that image.

    Dockerfile

    In this example, this is done by creating a recent Docker image, based on fis-java-openshift:latest and adding the Java agent into this project as an artifact to be added to that image:

    FROM registry.access.redhat.com/jboss-fuse-6/fis-java-openshift:latest USER root ADD appdynamics/ /opt/appdynamics/ RUN chgrp -R 0 /opt/appdynamics/ RUN chmod -R g+rw /opt/appdynamics/ RUN find /opt/appdynamics/ -type d -exec chmod g+x {} + #jboss from FIS USER 185

    In this Dockerfile, they are adding the content of the appdynamics directory in their Git repository to the fis-java-openshift base image, and altering its permissions so that it is owned by the JBoss user in that image.

    OpenShift

    In order to consume this Dockerfile and eddy it into a useable image, they savor a number of options. By far the simplest is to execute an oc new-build command against the repository hosting the Docker image – in the case of this image, this would be:

    oc new-build https://github.com/benemon/fis-java-appdynamics/#0.2-SNAPSHOT --context-dir=src/main/docker

    Note the utilize of the --context-dir switch pointing to the directory containing the Dockerfile. This informs OpenShift that it needs to notice in a sub-directory, not the root of the Git repository, for its build artifacts.

    Once we’ve executed the above command, they can tail the OpenShift logs from the CLI (or view them from the Web Console), and survey the Dockerfile build taking place. The output will be similar to this:

    [[email protected] ~]$ oc logs -f fis-java-appdynamics-1-build I0709 09:03:35.440237 1 source.go:197] Downloading "https://github.com/benemon/fis-java-appdynamics" ... Step 1 : FROM registry.access.redhat.com/jboss-fuse-6/fis-java-openshift ---> 771d26abb75d Step 2 : USER root ---> Using cache ---> c66c5f1378be Step 3 : ADD appdynamics/ /opt/appdynamics/ ---> ef153cb350d8 Removing intermediate container 44c776871f6f Step 4 : flee chown -R 185:185 /opt/appdynamics/ ---> Running in 861f8c27225e ---> ee1ac493f88d Removing intermediate container 861f8c27225e Step 5 : USER 185 ---> Running in 1d9fe0a02e6a ---> 73f598d8a0e9 Removing intermediate container 1d9fe0a02e6a Step 6 : ENV "OPENSHIFT_BUILD_NAME" "fis-java-appdynamics-1" "OPENSHIFT_BUILD_NAMESPACE" "dev1" "OPENSHIFT_BUILD_SOURCE" "https://github.com/benemon/fis-java-appdynamics" "OPENSHIFT_BUILD_COMMIT" "d025f9961896b25fcae479d62779ae455df334d3" ---> Running in 510a4b51db5a ---> c4e938d189eb Removing intermediate container 510a4b51db5a Step 7 : LABEL "io.openshift.build.commit.message" "Updated the FIS build artifacts" "io.openshift.build.source-location" "https://github.com/benemon/fis-java-appdynamics" "io.openshift.build.source-context-dir" "src/main/docker" "io.openshift.build.commit.author" "Benjamin Holmes \[email protected]\u003e" "io.openshift.build.commit.date" "Sat Jul 9 11:26:11 2016 +0100" "io.openshift.build.commit.id" "d025f9961896b25fcae479d62779ae455df334d3" "io.openshift.build.commit.ref" "master" ---> Running in 213844392db7 ---> 44fede9609fd Removing intermediate container 213844392db7 Successfully built 44fede9609fd I0709 09:04:06.573966 1 docker.go:118] Pushing image 172.30.49.26:5000/dev1/fis-java-appdynamics:latest ... I0709 09:04:10.970516 1 docker.go:122] shove successful

    NOTE: As an alternative to a gauge Dockerfile build, we can utilize the Kubernetes Fluent DSL to generate the BuildConfig and ImageStream objects as participate of a Template that will command OpenShift to Do a Dockerfile build based on the supplied project content. Using Kubernetes DSL is optional (you are more than welcome to define the objects manually), but as a Java developer this is a simple process to understand, it allows you to version control your entire image build process, and furthermore falls nicely into the ‘configuration as code’ discipline so prominent in the DevOps world. An illustration of how to utilize the Fluent DSL is supplied in the Github repository for the AppDynamics base image.

    Whichever process you settle upon (the supplied Github repository contains artifacts for both builds), OpenShift will generate a number of Kubernetes artifacts. What they are interested in here is the Image Stream…

    apiVersion: v1 kind: ImageStream metadata: ... generation: 1 labels: app: fis-java-appdynamics name: fis-java-appdynamics namespace: dev1 ... spec: {} status: dockerImageRepository: 172.30.49.26:5000/dev1/fis-java-appdynamics tags: .. tag: latest

    …and the BuildConfig:

    apiVersion: v1 kind: BuildConfig metadata: ... labels: app: fis-java-appdynamics name: fis-java-appdynamics namespace: dev1 ... spec: output: to: kind: ImageStreamTag name: fis-java-appdynamics:latest postCommit: {} resources: {} source: contextDir: src/main/docker git: uri: https://github.com/benemon/fis-java-appdynamics secrets: [] type: Git strategy: dockerStrategy: from: kind: ImageStreamTag name: fis-java-openshift:latest type: Docker triggers: - github: secret: 9Y66CCaSoOipX2pgeEXs type: GitHub - generic: secret: IrYOFwVX0pZKSkceG4D_ type: Generic - type: ConfigChange - imageChange: lastTriggeredImageID: registry.access.redhat.com/jboss-fuse-6/fis-java-openshift:latest type: ImageChange status: lastVersion: 1

    Please note that lines savor been removed from the above objects for the sake of brevity.

    Once the build of the fis-java-appdynamics image has completed successfully, they will savor a recent base image present in their namespace that contains the AppDynamics agent plugin.

    Magic.

    Adding the AppDynamics agent to a FIS application

    Given that I savor elected to result the second system of creating a recent base image with the AppDynamics Java agent added to it, I now exigency a course of configuring it.

    NOTE: These steps are much the very as those performed if you were to utilize the S2I builder process. However you can survey the subtle differences, such as the addition of JAVA_OPTIONS is performed by the .s2i/bin/run scriptas opposed to the DeploymentConfig in the Template in the sample repository here.

    Configuring the Agent

    The AppDynamics agent follows a similar agent model to many other profiling tools, in that it is added to a JVM using the -javaagent switch. When thinking in terms of immutable containers, they obviously want this entire configuration process to be as loosely coupled from the application image as possible.

    With this in mind, the simplest course to configure the AppDynamics Java agent is via environment variables. This is helpful, as the AppDynamics agent prioritises environment variables over any other forms of configuration it may savor available to it (such as controller-info.xml within the agent distribution). The AppDynamics Agent Configuration pilot has  further information.

    One option they savor here is to hard code entire of the requisite environment variables into an application DeploymentConfig. However, in this valiant recent world of immutable containers, short lived cloud applications workloads, and CI/CD pipelines they can be a bit cleverer than that.

    Using a Template for the application, they can silent define entire of the environment variables required by the AppDynamics agent, but they can furthermore utilize a mixture of templated parameters, and Kubernetes’ Downward API to effectively allow the container to introspect itself at runtime, and feed useful information about itself to the agent.

    Therefore, we can submit a Template that includes an environment variables component in its DeploymentConfig section which looks a petite fancy this:

    - name: JAVA_OPTIONS value: '-javaagent:/opt/appdynamics/javaagent.jar' - name: TZ value: Europe/London - name: APPDYNAMICS_CONTROLLER_HOST_NAME value: ${APPDYNAMICS_CONTROLLER_HOST_NAME} - name: APPDYNAMICS_CONTROLLER_PORT value: ${APPDYNAMICS_CONTROLLER_PORT} - name: APPDYNAMICS_CONTROLLER_SSL_ENABLED value: ${APPDYNAMICS_CONTROLLER_SSL_ENABLED} - name: APPDYNAMICS_AGENT_ACCOUNT_NAME value: ${APPDYNAMICS_AGENT_ACCOUNT_NAME} - name: APPDYNAMICS_AGENT_ACCOUNT_ACCESS_KEY value: ${APPDYNAMICS_AGENT_ACCOUNT_ACCESS_KEY} - name: APPDYNAMICS_AGENT_APPLICATION_NAME value: ${SERVICE_NAME} - name: APPDYNAMICS_AGENT_TIER_NAME valueFrom: fieldRef: apiVersion: v1 fieldPath: metadata.namespace - name: APPDYNAMICS_AGENT_NODE_NAME valueFrom: fieldRef: apiVersion: v1 fieldPath: metadata.name

    Note the utilize of Downward API reference for APPDYNAMICS_TIER_NAME and APPDYNAMICS_AGENT_NODE_NAME.

    NOTE: If you would fancy to try this with my sample template, you should execute the following command against your OpenShift environment:

    oc create -f https://raw.githubusercontent.com/benemon/camel-cxf-cdi-java-example/app...

    This creates the template within the current OpenShift project. This should be the very project in which you savor done the fis-java-appdynamics build, otherwise OpenShift won’t be able to locate the recent base image!

    When they present this via the OpenShift Web Console, they are shown a much more user friendly version of the above, allowing you to key in your AppDynamics account details without the exigency to store them in potentially troublesome static configuration files within the container.

    image00

    Once entire the fields savor been completed, click on ‘Create’, and (assuming entire mandatory fields savor been filled in), a screen will be presented confirming the successful creation of entire template objects.

    Once this Template has been instantiated successfully, OpenShift will start a build against the source code branch, using fis-java-appdynamics as the S2I builder image.

    Be cognizant that this project repository contains a gauge Maven settings.xml which can be used to define how Maven resolves the build dependencies. If you sustain long build times, this file can be updated to resolve to a local Maven repository, such as Sonatype Nexus, or JFrog Artifactory.

    After the build has completed successfully, a recent Pod will be started, running the application with its embedded Java agent (parts omitted for brevity):

    Executing /deployments/bin/run ... Launching application in folder: /deployments Running java -javaagent:/opt/appdynamics/javaagent.jar … Install Directory resolved to[/opt/appdynamics] log4j:WARN No appenders could be establish for logger (com.singularity.MissingMethodGenerator). log4j:WARN gratify initialize the log4j system properly. [Thread-0] Sat Jul 09 05:29:26 BST 2016[DEBUG]: AgentInstallManager - full Agent Registration Info Resolver is running [Thread-0] Sat Jul 09 05:29:26 BST 2016[INFO]: AgentInstallManager - full Agent Registration Info Resolver establish env variable [APPDYNAMICS_AGENT_APPLICATION_NAME] for application appellation [greeting-service] [Thread-0] Sat Jul 09 05:29:26 BST 2016[INFO]: AgentInstallManager - full Agent Registration Info Resolver establish env variable [APPDYNAMICS_AGENT_TIER_NAME] for tier appellation [dev1] [Thread-0] Sat Jul 09 05:29:26 BST 2016[INFO]: AgentInstallManager - full Agent Registration Info Resolver establish env variable [APPDYNAMICS_AGENT_NODE_NAME] for node appellation [greeting-service-1-fbcaa] [Thread-0] Sat Jul 09 05:29:26 BST 2016[INFO]: AgentInstallManager - full Agent Registration Info Resolver using selfService [true] [Thread-0] Sat Jul 09 05:29:26 BST 2016[INFO]: AgentInstallManager - full Agent Registration Info Resolver using selfService [true] [Thread-0] Sat Jul 09 05:29:26 BST 2016[INFO]: AgentInstallManager - full Agent Registration Info Resolver using application appellation [greeting-service] [Thread-0] Sat Jul 09 05:29:26 BST 2016[INFO]: AgentInstallManager - full Agent Registration Info Resolver using tier appellation [dev1] [Thread-0] Sat Jul 09 05:29:26 BST 2016[INFO]: AgentInstallManager - full Agent Registration Info Resolver using node appellation [greeting-service-1-fbcaa] [Thread-0] Sat Jul 09 05:29:26 BST 2016[DEBUG]: AgentInstallManager - full Agent Registration Info Resolver finished running [Thread-0] Sat Jul 09 05:29:26 BST 2016[INFO]: AgentInstallManager - Agent runtime directory set to [/opt/appdynamics/ver4.1.7.1] [Thread-0] Sat Jul 09 05:29:26 BST 2016[INFO]: AgentInstallManager - Agent node directory set to [greeting-service-1-fbcaa] [Thread-0] Sat Jul 09 05:29:26 BST 2016[INFO]: JavaAgent - Using Java Agent Version [Server Agent v4.1.7.1 GA #9949 ra4a2721d52322207b626e8d4c88855c846741b3d 18-4.1.7.next-build] [Thread-0] Sat Jul 09 05:29:26 BST 2016[INFO]: JavaAgent - Running IBM Java Agent [No] [Thread-0] Sat Jul 09 05:29:26 BST 2016[INFO]: JavaAgent - Java Agent Directory [/opt/appdynamics/ver4.1.7.1] [Thread-0] Sat Jul 09 05:29:26 BST 2016[INFO]: JavaAgent - Java Agent AppAgent directory [/opt/appdynamics/ver4.1.7.1] Agent Logging Directory [/opt/appdynamics/ver4.1.7.1/logs/greeting-service-1-fbcaa] Running obfuscated agent Started AppDynamics Java Agent Successfully. … Registered app server agent with Node ID[8494] Component ID[6859] Application ID [4075] Verifying Successful Integration

    Once the application has started successfully, and the agent has registered itself with AppDynamics, you should be able to survey your application on the AppDynamics Dashboard:

    image04

    Drilling down into the Application in the Dashboard furthermore confirms that the Downward API has done its job, and we’ve automatically pulled in both the container name, and the Kubernetes namespace.

    image03

    Testing Integration

    In order to acquire something a bit more meaningful out of the AppDynamics platform, I’ve save together a tiny test harness in SoapUI that simply runs a load test against the Fuse application’s RESTful endpoint:

    image02

    In OpenShift’s container logs they can survey these requests coming into the application, either via the Web Console or via the CLI.

    Once the test harness has completed its cycle, going back to the AppDynamics dashboard starts to give us a glimpse of something a bit more useful to us from an application monitoring and operations point of view:

    image01

    We can even drill down into the Web Service endpoints themselves, and examine the levels of load each is experiencing.

    image05

    Application Scaling

    One of the really nice things about using OpenShift, the Downward API, and AppDynamics in this course is that it even gives us useful information about health, request distribution and throughput when they scale out the application. Here the application has been scaled to 3 nodes:

    image06

    We can furthermore notice at the load and response times being experienced by users of the application service. Whilst this particular view gives an amalgamation of data, it’s a simple operation to drill down into an individual JVM to survey how it’s performing.

    Conclusion

    I savor barely scratched the surface of what they can monitor, log, and alert on with OpenShift, Fuse Integration Services, and AppDynamics. Hopefully though, it gives you a glimpse of what is viable using the tools provided by the OpenShift Container Platform, and a template for not only integrating AppDynamics, but furthermore other useful toolsets that result a similar agent model.

    Resources

    The full source repository for fis-java-appdynamics is here: https://github.com/benemon/fis-java-appdynamics/tree/0.2-SNAPSHOT

    The full source repository for the FIS/Camel application based on the fis-java-appdynamics image is here:https://github.com/benemon/camel-cxf-cdi-java-example/tree/appdynamics

    The full source repository for the FIS/Camel application with the Java agent added using S2I is here:

    https://github.com/benemon/camel-cxf-cdi-java-example/tree/appdynamics-s2iPlease note branches and tags in these repositories.

    The post Exploring the AppDynamics Integration with OpenShift Container Platform appeared first on Application Performance Monitoring Blog | AppDynamics.



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