Posts Tagged SDLC

Operational Readiness Analysis

“Analysis: a detailed examination of the elements or structure of something, typically as a basis for discussion or interpretation.” — Google

Introduction

Recently, I had the opportunity, along with a colleague, to perform an operational readiness analysis of a client’s new application platform. The platform was in late-stage development, only a few weeks from going live. Being relatively new to the project team, our objective was to determine the amount of work remaining to make the platform operational, from a technical perspective. As well, we wanted to ensure there were no gaps in the project’s scope, as it related to technical operational readiness.

There were various approaches we could have taken to establish the amount of unfinished work and any existing gaps. We could have reviewed the state of the project in the client’s Agile project management system. We could have discussed the project’s state with the Product Owner, Project Manager, Team Lead, and Business Analyst. Neither of these methods on their own would have provided us with a complete picture.

The approach we ultimately took was what we’ve coined, an Operational Readiness Analysis, or our trendier title, the ‘State of the DevOps’. This approach is particularly effective and highly interactive. The analysis may be conducted at any stage of the Software Development Lifecycle (SDLC), to review a project’s operational state of readiness. The analysis involves five simple steps:

  1. Categorize
  2. Itemize
  3. Organize
  4. Prioritize
  5. Document

Grab Your Post-It Notes

We began, where all good ThoughtWorkers tend to begin, with a meeting room, whiteboard, dry-erase markers, and lots of brightly colored Post-It notes. ThoughtWorkers do love their Post-It notes. We gathered a small subset of the project team, including the Product Owner, Project Manager, and the team’s DevOps Engineer.

Step 1: Categorize

To start, we broadly categorized the operational requirements into buckets of work. In my experience, categorization typically takes one of two forms, either the use of role-based descriptors, like ‘Security’ and ‘Monitoring’, or the use of the ‘ilities’, such as ‘Scalability’ and ‘Maintainability’.

The ‘ilities’ are often referenced in regards to software architecture and the functional and nonfunctional requirements (NFRs) of a project. Although there are many ‘ilities’, project requirements frequently include Usability, Scalability, Maintainability, Reliability, Testability, Availability, and Serviceability. Although I enjoy referring to the ‘ilities’ when drafting project requirements, I find a broad audience more readily understands the high-level category descriptions.

We collectively agreed on eight categories, in addition to a catch-all ‘Other’ category, and distributed them on the whiteboard.

whiteboard-step-1

Role-based categories tend to include the following:

  • Security and Compliance
  • Monitoring and Alerting
  • Logging
  • Continuous Integration and Delivery
  • Release Management
  • Configuration
  • Environment Management
  • Infrastructure
  • Networking
  • Data Management
  • High Availability and Fault Tolerance
  • Performance
  • Backup and Restoration
  • Support and Maintenance
  • Documentation and Training
  • Technical Debt
  • Other

Step 2: Itemize

Next, each person placed as many Post-It notes as they wanted, below the categories on the whiteboard. Each Post-It represented an item someone felt needed to be addressed as part the analysis. Items might represent requirements currently in progress, or requirements still untouched in the project’s backlog. A Post-It note might contain a new requirement. Maybe there is a question about an aspect of the project’s relative importance, or there were concerns about how an aspect of the project had been implemented.

Participants placed an average of five to ten Post-It notes on the whiteboard. The end product was a collective mind-map of the project’s operational state (the following is only an example and doesn’t represent the actual results of any real client analysis).

whiteboard-step-2

Whereas categories tend to be generic in nature, the items are usually particular to the project, and it’s technology choices. The ‘Monitoring/Logging’ category might include individual items such as ‘Log Rotation Policy’ or ‘Splunk vs. ELK?’. The ‘Security’ category might include individual items such as ‘Need Password Rotation’ or ‘SSL Certificate Management’.

Participants often use one or two words to summarize more complex thoughts. For example, ‘Rollback’ might be stating, ‘we still don’t have a good rollback strategy for the database’. ‘Release Frequency’ may be questioning, ‘why can’t we release more frequently?’. Make sure to discuss and capture the participant’s full thoughts behind each Post-It, the during the Organize, Prioritize, and Document stages.

Don’t let participants give up too soon placing Post-It notes on the board. Often, one participant’s Post-It will spark additional thoughts other team members. Don’t be afraid to suggest a few items, if the group needs some initial motivation. Lastly, fear not, it’s never too late to go back and add missing items, uncovered in later stages of analysis.

Step 3: Organize

Quickly and non-judgmentally, review all items on the whiteboard. Group duplicates together. Ask for clarification on items where necessary. Move miscategorized items, if the author and team agree there is a more appropriate category.

Examine the ‘Other’ category. If there are items in the ‘Other’ category that are similar, consider adding a new category to capture them. Maybe the team missed identifying a key category, earlier. Conversely, there is nothing wrong with leaving a few stragglers in the ‘Other’ category; don’t overthink the exercise.

Participants should leave this stage with a general understanding of each item on the whiteboard.

Step 4: Prioritize

With all items identified, organized, and understood, discuss each item’s status. Does the item represent incomplete requirements? Does everyone agree an item’s requirements are complete? Team members may not agree on the completeness of particular items. Inconsistencies may reflect unclear requirements. More often, I find, disagreements are a result of an inconsistent or incomplete implementation of requirements across environments — Development, QA, Performance, Staging, and Production.

Why are operational requirements frequently implemented inconsistently? Often, a story is played early in the development stage, prior to all environments being available. For example, a story is played to add monitoring to Development and QA. The story is completed, tested, and closed. Afterward, the Performance environment is created. Later yet, the Staging and Production environments are created. But, there are no new stories to address monitoring the new environments.

One way to avoid this common issue with operational requirements is an effective DevOps automation strategy. In this example, an effective strategy would mean all new environments would get monitoring, automatically. The story should broadly address monitoring, and not, short-sightedly, monitoring of specific environments.

Often, only one or two project team members are responsible for ‘all the DevOps stuff’. They alone possess an accurate perspective on an item’s current status.

Gain agreement from the Product Owner, Project Manager, and key team members on the priority of incomplete requirements. Are they ‘Day One’ must-haves, or ‘Day Two’ and can be completed after the application goes live? Flag all high-priority items.

If the status of an item is unknown, such as ‘why is the QA environment always down?!’, note it as an open question and move on. If the item simply requires a quick answer to resolve, like ‘do we backup the database?’, answer it (‘the database is replicated and backed up daily’) and move on.

whiteboard-step-4

Step 5: Document

Snap a picture of the whiteboard and document its contents. We chose the client’s knowledge management system as a vehicle to share the whiteboard’s results. We created a table with columns for Category, Item, Description, Priority, Owner, and Notes. Also, it’s helpful to have a column for the project’s corresponding Story ID or Defect ID. Along with the whiteboard, capture key discussion points, questions, and concerns, raised by the participants.

Step 5: Document

Snap a picture of the whiteboard and document its contents. We chose Confluence to share the whiteboard results, using a table with columns for Category, Item, Description, Priority, Owner, and Notes. We also bulleted all key discussion points, questions, and concerns, raised by the participants.

operational-readiness-spreadsheet

Make the analysis results available to all team members. Let the team ask questions and poke holes in the results. Adjust the results if necessary.

Next Steps

The actions you take, given the results of the analysis, are up to you. In our case, we ensured all high-priority items were called out on the team’s Agile board. Any new items were captured in the client’s Agile project management system. Finally, we ensured open questions and concerns were addressed in a timely fashion. We continue to track each item’s status weekly, throughout the launch and post-launch periods.

We anticipate conducting a follow-up analysis, thirty days after launch. The goal will be to evaluate the effectiveness of the first analysis and identify additional operational needs as the application enters a business-as-usual (BAU) application lifecycle phase.


Postscript: the ‘ilities

The ‘ilities’, courtesy of codesqueeze.com and en.wikipedia.org

  • Scalability
    The capability of a system, network, or process to handle a growing amount of work or its potential to be enlarged to accommodate that growth.
  • Testability
    The practical feasibility of observing a reproducible series of such counterexamples if they do exist.
  • Reliability (Resilience)
    The ability of a system or component to perform its required functions under stated conditions for a specified time.
  • Usability (Performance)
    The degree to which software can be used by specified consumers to achieve quantified objectives with effectiveness, efficiency, and satisfaction in a quantified context of use.
  • Serviceability (Supportability)
    The ability of technical support personnel to install, configure, and monitor computer products, identify exceptions or faults, debug or isolate faults to root cause analysis, and provide hardware or software maintenance in pursuit of solving a problem and restoring the product into service.
  • Availability
    The proportion of time a system is in a functioning condition. Defined in the service-level agreement (SLA).
  • Maintainability
    The ease with which a product can be maintained. Isolate and correct defects or their cause, prevent unexpected breakdowns, maximize a product’s useful life, maximize efficiency, reliability, and safety, meet new requirements, make future maintenance easier, and cope with a changed environment.

All opinions in this post are my own and not necessarily the views of my current employer or their clients.

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Building a Deployment Pipeline Using Git, Maven, Jenkins, and GlassFish (Part 2 of 2)

Build an automated deployment pipeline for your Java EE applications using leading open-source technologies, including NetBeans, Git, Maven, JUnit, Jenkins, and GlassFish. All source code for this post is available on GitHub.

System Diagram 3a

Introduction

In part 1, Building a Deployment Pipeline Using Git, Maven, Jenkins, and GlassFish (Part 1 of 2), we built the first part of our basic deployment pipeline using leading open-source technologies. In part 2, we will use Jenkins CI Server and Oracle GlassFish Application Server to complete our deployment pipeline.

To review, the three main goals of our deployment pipeline are continuous integration, automated testing, and continuous deployment. Our objective is to automatically compile, test, assemble, and deploy our Java EE application to multiple environments, as the project progresses through the software development life cycle (SDLC).

Setting up Git Server

As I mentioned in part 1, as a part of a development team using Git, you would place your project on a remote Git Server. You and your team members would each clone the repository from the Git Server to your local development environments. You and your team would commit your code changes locally, then pull, merge, and push your changes back to the remote Git Server. Jenkins will pull the project’s source code from the Git Server.

In part 1 of this post, we just created a local Git repository. In part 2, we will properly set-up our project on a remote Git Server. First, we need to export our local repository into a new, bare repository on the Git Server. The Git term, ‘bare repository’, refers to a repository that does not contain a working directory. The repository has no working copies of your source files. You only use the bare repository to clone, pull from, and push to. The bare repository contains a .git extension (i.e. ssh://user@server:/git-repos/myproject.git).

From the root of your remote Git Server repository, execute the following command, substituting the path to your local project. If your Git Server is on a separate machine that your local project repository, you will need to copy the new bare repository to the remote Git Server. This involves a few simple steps, explained in this post, and at git-scm.com.

Export Local Project to New Bare Repository

Export Local Project to New Bare Repository

Once you have created the repository on the remote Git Server, I would recommend you clone the remote repository to your local machine and discard your original local repository from part 1 of the post. You don’t have to do this step, but cloning fresh from the server will make sure Git is working correctly. The screen grabs below illustrate an example of cloning a new repository to my local NetBeans Project folder.

Clone New Bare Server Repository - Screen 1

Clone New Bare Server Repository – Screen 1

Clone New Bare Server Repository - Screen 2

Clone New Bare Server Repository – Screen 2

Clone New Bare Server Repository - Screen 3

Clone New Bare Server Repository – Screen 3

Configuring Jenkins

The diagram below illustrates the deployment pipeline from Git Server to Jenkins to GlassFish in finer detail. It begins with an initial commit to the local Git project repository and ends with the deployment of the project’s WAR file to the GlassFish domain. We will walk through it step-by-step.

System Diagram 3c

Jenkins Plugins

Before we create our new Jenkins Jobs, we need to configure Jenkins properly. You will need a recent version of Jenkins installed, along with the following plugins:

  1. Build With Parameters Plugin
  2. Copy Artifact Plugin
  3. Jenkins GIT plugin (includes Jenkins GIT client plugin)
  4. Jenkins Parameterized Trigger plugin
  5. Maven Integration plugin
  6. Credentials Plugin (optional for use with Git Server if security is enabled)
  7. ThinBackup (optional to install supplied Jenkins jobs configuration files)

Global Security

Jenkins can be configured with or without Global Security. For this post, I have enabled Global Security, as it typical of most development environments. I chose to use ‘Jenkins’s own user database’ option for authentication. In larger development environments, authentication would normally be done against LDAP.

Jenkins' Configure Global Security

Configuring Global Security

The user I have set up, ‘jenkins’, will be the user that Git authenticates with when connecting to Jenkins (explained later). Set up your own user and note their API Token. Since Global Security has been enabled, we will need the token later to trigger the Jenkins build from Git. Your user’s unique api token will be different than in the example below.

Jenkins User API Token

Jenkins User API Token

Jenkins Jobs

We will set up two Jenkins ‘free-style software project’ jobs, ‘GitMavenGlassFish_Build’ and ‘GitMavenGlassFish_Deploy’. We won’t be using the obvious choice, a ‘maven2/3 project’. If you’re interested, here’s why. The first job, the build job, will be responsible for pulling the source code from the Git Server. The build job, with help from Maven, will compile, test, and assemble the application code. The second job, the deployment job, will pull the artifacts from the build job and deploy them to GlassFish. The build job will trigger the deployment job, once the build job completes successfully. This is explained in detail, to follow.

Why Two Jobs?

Following good modular design and Separation of Concerns (SoC) principles, separating the build from the deployment gains us several advantages, including:

  1. Modularity– Ability to change deployment methodology or deployment targets, without disrupting the build and test process. For example, we might move the application hosting from GlassFish to WebLogic, or decide to use Ant instead of Maven for deployment tasks. This can happen totally independent of the build and testing processes.
  2. Separation/Isolation – For any reason we are unable to deploy the artifacts as part of the deployment job, we won’t impact the continuous integration and automated testing processes, which are part of the separate build job.
  3. Support – Support is easier by having smaller pieces of functionality to troubleshoot and maintain.

In a larger enterprise environment, you would probably encounter further separation of concerns. Unit testing, performance testing, deployment validation, and documentation generation (javadocs) are often handled by separate jobs. Jenkins represents a smaller pipeline within our larger deployment pipeline.

I intentionally left out notification for brevity. At minimum, you would want to be notified when the build or deployment jobs failed. Additionally, with continuous deployment, the deployment would trigger a notification to the stakeholders of that environment, such as the Testers. This lets them know the new software is ready to be tested. Notifications often include a list of bug fixes and feature enhancements that need to be tested. This can easily be pulled from Git into Jenkins and out to the end user.

Both Jenkins jobs definitions are available as xml files on gist.github.com. Using Jenkins’ ThinBackup Plugin, you can save both gists locally, and then restore them to your Jenkins server. The build job gist is here and the deployment job gist is here. This may save you some configuration time.

Jenkins Build Job

Both the build job and the deployment jobs require an input parameter. This property represents the targeted environment (GlassFish domain) for deployment, such as ‘testing’.. How this parameter is passed to Jenkins is discussed later in the Git Hooks section, below.

Reviewing the below screen grab of the build job’s configuration, you will observe the following steps:

  1. Build Request – A build request is received by the job (explained later). The request contains an input parameter indicating the ‘environment’. The parameter must be one of the choices listed in ‘Choices’.
  2. Maven Dependencies – Based on the pom file, Maven retrieves all the required dependencies from the remote Maven repository, if the dependencies are not already contained in the workspace’s local repository. Note the setting ‘User private Maven repository. This creates a local repository for project dependencies within the project’s workspace.
  3. Pull from Git – Jenkins pulls the code from the Git Server using the supplied repository configuration information. Note my Git Server does not require authentication. If it did, we would set-up and use the proper credentials.
  4. Build – Jenkins builds the project using the Maven command ‘clean install -e’. The pom file contains the necessary configuration information.
  5. Unit Test – The above Maven ‘install’ command also calls JUnit to execute the unit tests. The results of these tests are published and displayed as part of the build job’s details.
  6. Assemble WAR – The above Maven ‘install’ command also assembles the project’s WAR file.
  7. Archive Artifacts – Based on the success of the build and unit tests, Jenkins archives specific artifacts needed by the deployment job. Jenkins uses the input parameter in #1 to define which properties file and password file to archive.
  8. Trigger Deployment Job – Based on the success of the build and unit tests, Jenkins triggers the ‘downstream’ deployment job, passing it the same environment parameter.
Jenkins Build Job Configuration

Jenkins Build Job Configuration

Jenkins Deployment Job

Reviewing the below screen grab of the deployment job’s configuration, you will observe the following steps:

  1. Build Request – A build request is received from the upstream build job. The request contains the input parameter indicating ‘environment’.
  2. Copy Artifacts – Jenkins copies the artifacts from the build job that called the deploy job.
  3. Read Properties – Maven executes the command ‘mvn properties:read-project-properties glassfish:redeploy -e’. The first half of this command instructs Maven to read the appropriate properties file, as indicated by the environment parameter, ‘glassfish.properties.file.argument=${environment}’.
  4. POM – Maven substitutes the key ‘glassfish.properties.file.argument’ in the pom file with the environment value. This tells Maven the name of the properties file, which supplies all the remaining property values to the pom file.
  5. Maven Dependencies – If the dependencies are not already contained in the workspace’s local repository, Maven retrieves all the required dependencies from the remote Maven repositories, based on the pom. Note the setting ‘User private Maven repository’ checked in the screen grab below. This option instructs Jenkins to creates a local repository for project dependencies within the project’s workspace.
  6. Deployment – The last half of the command in #3 deploys, or more accurately redeploys the application’s WAR file to GlassFish. The ‘glassfish:redeploy’ works only if the WAR file has already been initially deployed to the GlassFish domain using the ‘glassfish:deploy’ command. For this process, I am assuming the initial deployment was already done directly through the GlassFish Administration Console, NetBeans, or command line.
Jenkins Deploy Job Configuration

Jenkins Deploy Job Configuration

Git Hooks

To achieve continuous integration, we want to automatically build and test our job after each change to our code. We have a number of choices to make this happen. The obvious choice is letting Jenkins poll the Git Server. Although polling would simplify configuration, polling is frowned upon in many environments. Even the creator of Jenkins, Kohsuke Kawaguchi, frowns upon polling in his post, ‘Polling Must Die‘.

Why is polling bad? It adds unnecessary activity and delay. Let’s say Jenkins’ polling frequency is set to every 2 minutes, but you only have an average of 5 pushes to your remote Git Server project repository per day. Based on these stats, in just one day, Jenkins will poll Git 720 times to discover only 5 pushes. That’s 144 times per push. Also, based on the polling frequency, when you do push, you could wait up to 2 minutes for Jenkins to queue the build job. The longer you wait for feedback on your changes, the greater chance your defects could be pulled down by other developers. You should expect immediate and continuous feedback.

A vastly more efficient and configurable method of continuous integration between Git and Jenkins is Git Hooks. Git Hooks allow us to execute scripts based on specific Git actions. In our case, when a developer completes a successful push to the remote Git Server project repository, we want to call Jenkins to build, test, and deploy the modified project code. Using hooks means we only call Jenkins when a successful push is completed. Furthermore, we can be assured Jenkins will immediately queue our request to build and deploy the job when a push occurs.

Post-Receive Hook

There are several types of Git Hooks. They include ‘post-commit’, ‘pre-push’, ‘update’, ‘pre-rebase, and so forth. I recommend this post on kernel.org for a good explanation of the hook types and thier purposes. Git also includes sample hook files inside the ‘hooks’ subdirectory of each new repository .git folder.

For our pipeline, we will employ the ‘post-receive’ hook. Whenever a successful push is received by Git Server’s project repository, the ‘post-receive’ hook will be called. The script commands, contained in the post-receive hook file, will be executed. Hooks can language agnostic; they can be almost any scripting language, such as Perl, Shell, Bash, or Ruby.

To create the hook, create a new file, ‘post-receive’, in the hooks sub-directory of the Git Server’s project repository. Add the below code to the file. Change the command to match your local file path. Also, change the API Token to match your user’s token from Jenkins. Note the command requires cURL to be installed on the Git Server. If installing cURL is not an option, there are other options available to execute the http post call from the hook’s script.

NetBeans and Git Hooks

Now some slightly bad news. As with any integration, there is always trade-offs; that is the case with NetBeans and Git. Although NetBeans works well with Git, there are a few features that have not been implemented. Unfortunately, this lack of complete integration effects NetBeans’ ability to make use of Git Hooks. Only after three hours of troubleshooting and research on the Internet, did I realize this limitation. The hooks fire fine if a git push command is executed from a command prompt or from within a Git application like Git Gui or Git Bash. However, from NetBeans, the Team -> Remote -> Push… does not cause the hooks to be called.

Example Post-Receive Hook - Works from Command Prompt

Post-Receive Hook Working from a Windows Command Prompt

Git Hooks do not work with NetBeans because NetBeans does not use a command line client for Git. NetBeans uses a pure java implementation of the Git client, Java GIT, known as JGit. I understand that other IDE’s also share this limitation. There are several discussions on StackOverflow and on the NetBeans bug tracking site about the issue and workarounds.

So what does this mean? You can use NetBeans to perform all of your local tasks. However, when it comes time to push your code back to the remote Git Server repository, you must use a command prompt, Bash shell, or a command line based tool. I recommend Git Gui. Git ships with built-in GUI tools, including git-gui and gitk. It can be downloaded from git-scm.com.

Git Gui Graphical User Interface for Git

Git Gui Graphical User Interface for Git

Push Files Using Git GUI Instead of NetBeans

Push Files Using Git GUI Instead of NetBeans

Pushing changes to the remote Git Server using Git Gui instead of NetBeans may seem inconvenient at first. However, the more advanced your needs become with Git, the more you will find you need the additional functionality of Git Bash, Git Gui, and gitk. Tasks like resetting the branch to a previous revision, compressing the Git repository database, and visualizing repository history, can all be done with tools like Git Gui and gitk. I have Git Gui running when I am working in NetBeans or other IDEs; it becomes second nature.

Using Git Gui and gitk Used to Examine Repository

Using Git Gui and gitk to Examine and Modify the Project Repository

Deploying to GlassFish

At this point we have configured the Git Server, created the Jenkins build and deploy jobs, and configured our Git hook. We are ready to test our deployment pipeline. First, make sure your GlassFish domains are running. Also, recall we are assuming that an initial deployment of the application has occurred. This might be directly through the GlassFish Administration Console, through NetBeans, or via the command line. Recall, Jenkins will be only be executing a re-deploy.

Check and Start GlassFish Domains

Check and Start GlassFish Domains

To test the system, make an innocuous change to the Project. Commit the change to your local Git repository. Following that, push the change back to the remote Git Server repository using Git Gui. If the hook fired, you will see output to the Git Gui terminal window, echoed from the post-receive hook as it executed its script.

Push with Git Gui Triggering Jenkins Build

Push with Git Gui Triggering Jenkins Build

The post-receive hook executes the cURL command, which posts an HTTP request to Jenkins via the Jenkins Remote API. You should observe is the Jenkins build job queued and running.

Jenkins Build Job Running

Jenkins Build Job Running

When the build completes, review the Parameters menu option in the left navigation menu. It shows that the environment parameter was passed from the post-receive hook to the build job. The build results window also provides test results, Git Build Data, and the changes pushed to Git that triggered the CI build.

Jenkins Build Job Results

Jenkins Build Job Results

The console output from the build provides a detailed view of the build process. Using the ‘-e’ for echo with the Maven command, increases the level of output detail. You see the details of Maven copying the required dependencies from the remote repository to the local workspace repository, prior to compilation. You see the unit tests being executed. Finally, you see the WAR file assembled and the required artifacts archived.

Regarding Maven Dependencies, you will only see the dependencies copied on the first build to an empty workspace. Maven does not re-pull dependencies if they already exist in the workspace’s local repository. To see the difference, empty your workspace and build the job, then immediately rebuild the job. Compare the console outputs of both jobs. You will see a significant difference in the Maven dependency activities.

Jenkins Build Job Console Results

Jenkins Build Job Console Results

Once the build job has completed successfully, you should notice the Jenkins deployment job running, triggered by the build job. When complete, note the detail that lists the exact build job that called the deployment job, and its build number. For example, the upstream build job #45 triggered the downstream deployment job #33. This linkage between upstream and downstream jobs is retained in the job’s history.

As before, review the Parameters menu option in the left navigation menu. It shows that the environment parameter was passed from the post-receive hook to the build job, and then on to the deployment job.

Jenkins Deployment Job Complete

Jenkins Deployment Job Complete

A review of the console output will confirm that the artifacts were copied from the build job and the WAR file was deployed to the ‘testing’ GlassFish domain.

Jenkins Deployment Job Console Output

Jenkins Deployment Job Console Output

GlassFish

If the hook fired, and both the Jenkins build and deployment jobs ran successfully, you should observe that the project’s WAR files, containing your recent change, was deployed to the testing GlassFish domain.

Application Installed on GlassFish Server Testing Domain

Application Installed on GlassFish Server Testing Domain

You can verify this by calling the application’s RESTful ‘resources/helloWorld’ URI, from your browser. Repeat the process by changing the output string, commit the change, and push. See if you see your change deployed.

Application Running on GlassFish Server Testing Domain

Application Running on GlassFish Server Testing Domain

Jenkins Workflows

Using our deployment pipeline, we have two distinct workflow options:

  1. Continuous– Use Git hooks to build, test, and deploy the WAR file to the domain(s) of choice when changes are pushed. Any time a change is pushed, a build, test, and deploy, should occur. This would be just for development at first. Once the project enters the testing phase of the SDLC, then it would include deployments to testing.
  2. Semi-Automated – Start the Jenkins build manually in the Jenkins browser-based Administration Console. This is more typical for a release to Production. Most teams are not comfortable extending the continuous deployment functionality into Production. Often, a deployment team will deploy the project artifacts in a controlled and staged approach. The Jenkins build and/or deployment jobs both allow this feature, along with the ability to provide the environment parameter both jobs needs.

Conclusion

In part 1, we learned how to create a simple Java EE web application project in NetBeans using Maven. We learned how to integrate JUnit for unit testing, and how use Git to manage our source code.

In part 2, we learned how to configure a remote Git Server, how to configure Jenkins CI Server to clone our project from the Git Server, build, test, and assemble it. If the build was successful, we learned how to configure Jenkins to deploy our project to a specific GlassFish domain, based on the project’s stage in the SDLC. We achieved our goals of continuous integration, automated testing, and continuous deployment.

Going Forward

To extend and enhance our deployment pipeline, you might consider adding the following features: 1) further separate the Jenkins jobs by function, 2) add build and deploy notifications, 3) add the ability to deploy to multiple environments simultaneously (i.e. development and testing), 4) add additional testing to confirm the deployment to GlassFish, 5) configure a versioning and naming scheme for the deployed artifacts, and 6) add error handling if a parameter is not received or is not one of the expected values.

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Building a Deployment Pipeline Using Git, Maven, Jenkins, and GlassFish (Part 1 of 2)

Build an automated deployment pipeline for your Java EE applications using leading open-source technologies, including NetBeans, Git, Maven, JUnit, Jenkins, and GlassFish. All source code for this post is available on GitHub.

System Diagram 3a

Introduction

In my earlier post, Build a Continuous Deployment System with Maven, Hudson, WebLogic Server, and JUnit, I demonstrated a basic deployment pipeline using leading open-source technologies. In this post, we will demonstrate a similar pipeline, substituting Jenkins CI Server for Hudson, and Oracle’s GlassFish Application Server for WebLogic Server. We will use the same NetBeans Java EE ‘Hello World’ RESTful Web Service sample project.

The three main goals of our deployment pipeline will be continuous integration, automated testing, and continuous deployment. Our objective is to automatically compile, test, assemble, and deploy our Java EE application to multiple environments, as the project progresses through the software development life cycle (SDLC).

Building a reliable deployment pipeline is complex and time-consuming. To make it as easy as possible in this post, I chose NetBeans IDE for development, Git Distributed Version Control System (DVCS) for managing our source code, Jenkins Continuous Integration (CI) Server for build automation, JUnit for automated unit testing, GlassFish for application hosting, and Apache Maven to manage our project’s dependencies. Maven will also manage the build and deployment process to GlassFish, along with Jenkins. The beauty of NetBeans is its out-of-the-box, built-in integration with Git, Maven, JUnit, and GlassFish. Likewise, Jenkins has plugin-based integration with Git, Maven, JUnit, and GlassFish. Also, Maven has plugin-based integration with GlassFish.

Maven is a powerful tool for managing modern software development projects. This post will only draw upon a small part of Maven’s functionality and plug-in architecture extensibility. Specifically, we will use the Maven GlassFish Plugin. According to the Java.net website, which host’s the plug-in project, ‘the Maven GlassFish Plugin is a Maven2 plugin allowing management of GlassFish domains and component deployments from within the Maven build life cycle.’

 Requirements

To follow along with this post, I will assume you have recent versions of the following software installed and configured on your Windows OS-based computer (the process is nearly identical for Linux):

  1. NetBeans IDE. Current version: 7.4
  2. JUnit. Current version: 4.11 (included with NetBeans 7.4)
  3. GlassFish Server. Current version: 4.0 (included  with NetBeans 7.4)
  4. Jenkins CI Server. Current version: 1.538
  5. Apache Maven. Current version: 3.1.1
  6. cURL. Current version: 7.33.0
  7. Git with Git Gui and gitk. Current version: 1.8.4.3
  8. Necessary system environmental variables:
    M2_HOME, M2, JAVA_HOME, GLASSFISH_HOME, and PATH

GlassFish Domains

To simulate a simple deployment pipeline, we will create three GlassFish domains, simulating three common software environments, Development, Testing, and Production. A typical software project is promoted through these environments as it moves from development, to testing, and finally release to production. Each environment has distinct stakeholders with specific roles to play in the software development life cycle, including developers, testers, deployment teams, and end-users. Larger-scale, enterprise software development often includes other environments, such as Performance and Staging.

Create the domains from the command line using ‘asadmin’ commands such as the ones below. Note I have a ‘GLASSFISH_HOME’ system environment variable set up. The ports are your choice, but make sure they don’t conflict with existing installations of other applications, such as Jenkins, Tomcat, IIS, WebLogic, and so forth.

As part of the creation process, you’re prompted for an admin account and a new password. I kept the ‘admin’ username, but added a new password for each domain created. This password is the same as one used in the separate password files (explained below).

Add the GlassFish domains to NetBeans’ Services -> Server tab, and start them.

Create New GlassFish 4.0 Production Domain - Screen 1

Create New GlassFish 4.0 Production Domain – Screen 1

Create New GlassFish 4.0 Production Domain - Screen 2

Create New GlassFish 4.0 Production Domain – Screen 2

Create New GlassFish 4.0 Production Domain - Screen 3

Create New GlassFish 4.0 Production Domain – Screen 3

Create New GlassFish 4.0 Production Domain - Screen 4

Create New GlassFish 4.0 Production Domain – Screen 4

Setting Up the Project

To set up our NetBeans project, you can clone the repository on GitHub or build your own project from scratch and copy the files into the project. I will not spend a lot of time explaining the code since we have used it in earlier posts. This post is about the deployment pipeline system, not the project’s code.

If you choose to create a new project, first, create a new Maven ‘Project from Archetype’. Select the Archetype for a ‘web application using Java EE 7’ (webapp-javaee7).

New Maven Project - Screen 1

New Maven Project – Screen 1

New Maven Project - Screen 2

New Maven Project – Screen 2

I recommend you create the project inside of your local Git repository folder.

New Maven Project - Screen 3

New Maven Project – Screen 3

Maven will execute a series of commands to create the default NetBeans project with dependencies.

Git

As a part of a development team using Git, you place your project on a remote Git Server. You and your team members each clone the repository on the Git Server to your local development environments. You and your team commit your code changes locally, then pull, merge, and push your changes back to the Git Server. Jenkins will pull the project’s source code from the remote Git Server.

In part 2, we will properly set-up our project on the Git Server, exporting our existing repository into a new, bare repository on the Git Server. However, for brevity in part 1 of this post, we will just create a local Git repository. To start, create a new Git repository for the project. In NetBeans, select Team -> Git -> Initialize Repository… Choose the new Maven project folder.

Initialize New Git Repository

Initialize New Git Repository

The initial view of the Maven project should look like the below screen grabs. Note the icons and the green files show that the project is part of the Git repository.

Initial Projects Tab View of New Maven Project

Initial Projects Tab View of New Maven Project

Initial Files Tab View of New Maven Project

Initial Files Tab View of New Maven Project

Perform an initial commit of the project to Git to make sure everything is working.

Initial Commit of New Maven Project to Git

Initial Commit of New Maven Project to Git

Next, copy the supplied HelloWorldResource. java and NameStorageBean.java classes into the project. The package classpath will be refactored by NetBeans. Copy all the remaining files and folders, including the (3) files in the WEB-INF folder, properties folder with (3) properties files, and passwords folder with (3) password files.

JUnit

Next, right-click on the NameStorageBean.java class and select Tools -> Create Tests. Replace the contents of the new NameStorageBeanTest.java file’s NameStorageBeanTest class with the contents of the supplied NameStorageBeanTest.java file. These are two very simple unit tests that will show how JUnit provides automated testing capabilities.

Create JUnit Tests - Screen 1

Create JUnit Tests – Screen 1

Create JUnit Tests - Screen 2

Create JUnit Tests – Screen 2

Project Object Model (POM)

Copy the contents of the supplied pom file into the new pom file. There is a lot of configuration in the supplied pom. It will be easier to copy the supplied pom file’s contents into your project then trying to configure it from scratch.

Basically, beyond the normal boilerplate pom configuration, we have defined (3) properties, (3) dependencies, and (5) build plugins. The three dependencies are junit, jersey-servlet, and javaee-web-api. The five plugins are maven-compiler-plugin, maven-war-plugin, maven-dependency-plugin, properties-maven-plugin, and the maven-glassfish-plugin. Each plugin contains individual plug-in specific configuration. The name of the plugin should be sufficient to explain their primary purpose.

When complete, right-click on the project and do a ‘Build with Dependencies…’. Make sure everything builds. The final view of the project, with all its Maven-managed dependencies should look like the two screen grabs shown below. Make sure to commit all your new code to Git.

Final Projects Tab View of Project

Final Projects Tab View of Project

Final Files Tab View of Project

Final Files Tab View of Project

Maven and Properties Files

In part 2, will be deploying our project to multiple GlassFish domains. Each domain’s configuration is different. We will use Java properties files to store each of the GlassFish domain’s configuration properties. The ability to use Java properties files with Maven is possible using the Mojo Project’s Properties Maven Plugin. I introduced this plugin in an earlier post, Build a Continuous Deployment System with Maven, Hudson, WebLogic Server, and JUnit.

Each environment (Development, Testing, Production), represented by a GlassFish domain, has a separate properties file in the project (see the Files Tab view above). The properties files contain configuration values the Maven GlassFish Plugin will need to deploy the project’s WAR file to each GlassFish domain. Since the build and deployment configurations are required by the project, including them into our Git repository and automating their use based on the environment, are two best practices.

In our project’s particular workflow, Maven accepts a single argument (‘glassfish.properties.file.argument’), which represents the environment we want to deploy to, such as ‘development’. The property value tells Maven which properties file to read, such as ‘development.properties’. Maven replaces the keys in the pom file with the values from the ‘development.properties’ file.

The properties file also tells Maven the full path to the separate password file, containing the admin user password, such as ‘pwdfile_development’. In an actual production environment, we would store encrypted password files on a secured file path. For simplicity in our example, we have included them unencrypted, within the project’s main directory.

System Diagram 3b

There are other Maven capabilities that also would achieve our deployment goals. For example, you might consider the Maven Release Plugin, as well as look at using Maven Build Profiles.

Testing the Pipeline

Although we have not built the second half of our deployment pipeline yet, we can still test the system at this early stage. All the necessary foundational elements are in place. To test the our system, right-click on the Maven Project icon in the Projects tab and select Custom -> Goals… Enter the following Maven Goals: ‘properties:read-project-properties clean install glassfish:redeploy -e’. In the Properties text box, enter the following: ‘glassfish.properties.file.argument=testing’ (see screen grab below). This will execute a number of Maven Goals and associated commands, visible in the Output tab.

With this one simple command, we are asking Maven to 1) read in our Java properties file and password file, 2) clean the project, 3) pull down all our project’s dependencies, 4) compile the project’s code, 5) execute the unit tests with JUnit, 6) assemble the WAR file, and 7) deploy it to the ‘testing’ GlassFish domain using asadmin. The terse nature of the command really demonstrates the power of Maven to manage our project and the deployment pipeline!

Run Maven within NetBeans to Test Pipeline

Run Maven within NetBeans to Test Pipeline

If successful you should see a message in the Output tab, indicating as much. Reviewing the contents of the Output tab will give you complete insight into the Maven process under the NetBeans hood. We used the ‘-e’ (echo) argument with Maven and the ‘Show Debug Output’ to further provide information to us about the process. The output contains all calls to Maven and subsequently to asadmin (GlassFish). You can learn a lot about using Maven and asadmin (GlassFish) by studying the Debug Output.

Conclusion

In the first part of this post, we learned how to create a simple Java EE web application project in NetBeans, using Maven. We learned how to integrate JUnit for automated testing, and how use Git to manage our source code.

In the second half of this post, we will learn how to configure Jenkins CI Server to retrieve our project from the remote Git repository, build, test, and assemble it into a WAR file. If these steps are successful, Jenkins will deploy our project to a GlassFish domain or multiple domains, based on the project’s stage in the software development life cycle. We will demonstrate how to automate Jenkins to achieve true continuous integration and continuous deployment.

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