Opportunity Cost

As Seth Godin knows opportunity cost just went up. Building and delivering software is getting more complicated, so keep your human mind free to focus on the interesting bits and leave the boring, repetitive stuff to the machines.

What’s the best way to do this? Build your CD pipeline first, setup the infrastructure (preferably serverless) from the start and then get into the flow of development. Add more checks and balances as you go. Run automated tests. Deploy to the cloud.

Secure DevOps Kit for Azure

AzSK ARM Template Checker

This is a very useful open source tool used internally by Microsoft to validate that best practices are being followed in their Azure ARM templates.

This short post shows how to incorporate the AzSK ARM Template Checker into your Azure YAML Pipeline.

If you want to use a Linux build agent, you can use the PowerShell task to run AzSK.

- task: PowerShell@2
          inputs:
            targetType: 'inline'
            script: |
              Set-PSRepository -Name "PSGallery" -InstallationPolicy Trusted
              Install-Module AzSK
              Import-Module AzSK
              Get-AzSKARMTemplateSecurityStatus -ARMTemplatePath $Env:BUILD_SOURCESDIRECTORY/arm-templates
            failOnStderr: true

Otherwise if you are using a Windows build agent, you can use the Azure Extension

Counting word frequency using map.merge

Imagine we want to produce a Map with each unique word as a key and it’s frequency as the value.

Prior to Java 8 we would have to do something like this:

Map<String, Integer> map = new HashMap<>();
for(String word : words) {
    if(map.containsKey(word)) {
        int count = map.get(word);
        map.put(word, ++count);
    } else {
        map.put(word, 1);
    }
}

However with the map.merge method we can now do:

Map<String, Integer> map = new HashMap<>();;
for(String word : words) {
    map.merge(word, 1, Integer::sum);
}
return map;

Pretty nice eh?

Email is dead, long live Slack

Here are some great reasons to stop using email for team communication and instead switch to Slack

  • By default email messages are private – only available to the recipients. Slack messages are by default available to the whole team. Simply join the channel you’re interested in (or leave if not). How many times have you had to forward an email to someone who wasn’t on the original? or worse that other person never got to give their valuable contribution because they were never on the list?
  • Build a knowledge base – with email when someone leaves your company their account is deactivated and along with it all their sent emails. Imagine how useful this info could be if preserved and made searchable! Key decisions, how-tos and historical context can be available throughout the project and made available to all especially new comers.
  • Marketplace of apps – Slack has LOTS on fantastic integrations, like Git, Jenkins and JIRA which help to keep task communications flowing. Eg. see when a code review is required and openly discuss.
  • Self service – No need to request mailing lists from your email admin for topics or projects, simply create a channel and invite the relevant team members. E.g. Just developers working on project X
  • Multimedia – Call a video conference and screen share from within a shared channel without having to mess around with other conferencing apps. You can even give others control over your desktop (useful if it’s going to take too long to explain a technical task)
  • Sync and Async – Conversations are much closer to real-time than email, but still have the option of being asynchronous if you don’t want to be distracted.
  • Connection – Remote team mates feel more connected with Slack. You can see who’s online. You can see other work happening even if you’re not directly involved with the project or you can simply have a bit of banter with fellow employees easily without worrying about who should I CC in this email.
  • Strangers are friends – Other companies can be given access to a specific Slack channel and feel part of the team.
  • Don’t repeat yourself – No huge email chains with reply to all that require you to scroll through pages of crap to find the context on the conversation.

Continuous Integration, Continous Delivery, Continous Deployment.

Within DevOps the terms Continuous Integration, Continuous Delivery and Continuous Deployment get thrown around a lot. Here is the simplest definition I could come up with to quickly explain each to a non techie like a project manager.

Continuous IntegrationRunning unit and other tests on every branch on every commit and merging to master every day
Continuous DeliveryAs above but each commit CAN be pushed to production
Continuous DeploymentAs above but each commit IS pushed to production

Serverless Continuous Deployment for Java AWS Lamba using AWS CodePipeline

This post shows step by step how to deploy your serverless Java AWS Lambas continuously to production. Moving from pull request, merge, build, deploy and finally test.

Overview


Project Setup

For our project we are going to assume a standard Maven Java project structure, with Cloudformation and build specification config in the root of the project.

Within the Maven pom.xml file, you must include the lambda core libraries.

  • <dependencies>
  •       <dependency>
  •           <groupId>com.amazonaws</groupId>
  •           <artifactId>aws-lambda-java-core</artifactId>
  •           <version>1.2.0</version>
  •       </dependency>
  • And also include the AWS SDK Java BOM
  • <!–https://aws.amazon.com/blogs/developer/managing-dependencies-with-aws-sdk-for-java-bill-of-materials-module-bom/–>
  •    <dependencyManagement>
  •        <dependencies>
  •            <dependency>
  •                <groupId>com.amazonaws</groupId>
  •                <artifactId>aws-java-sdk-bom</artifactId>
  •                <version>${com.amazonaws.version}</version>
  •                <type>pom</type>
  •                <scope>import</scope>
  •            </dependency>
  •        </dependencies>
  •    </dependencyManagement>
  • Next you also need to ensure that the JAR artifact is built flat
  • <build>
  •       <plugins>
  •           <plugin>
  •               <groupId>org.apache.maven.plugins</groupId>
  •               <artifactId>maven-shade-plugin</artifactId>
  •               <version>3.1.0</version>
  •               <configuration>
  •                   <createDependencyReducedPom>false</createDependencyReducedPom>
  •               </configuration>
  •               <executions>
  •                   <execution>
  •                       <phase>package</phase>
  •                       <goals>
  •                           <goal>shade</goal>
  •                       </goals>
  •                       <configuration>
  •                           <transformers>
  •                               <transformer
  •                                     implementation=”com.github.edwgiz.mavenShadePlugin.log4j2CacheTransformer.PluginsCacheFileTransformer”>
  •                               </transformer>
  •                           </transformers>
  •                       </configuration>
  •                   </execution>
  •               </executions>
  •               <dependencies>
  •                   <dependency>
  •                       <groupId>com.github.edwgiz</groupId>
  •                       <artifactId>maven-shade-plugin.log4j2-cachefile-transformer</artifactId>
  •                       <version>2.8.1</version>
  •                   </dependency>
  •               </dependencies>
  •           </plugin>

Build Pipeline using AWS CodePipeline

Source Step

The first step in the AWS CodePipeline is to fetch the source from the S3 bucket

  • Action Name: Source
  • Action Provider: S3
  • Bucket: <your release bucket>
  • S3 Object Key <path of your application>.zip
  • Output Artifact: MyApp

Build Step

Next step in the pipeline, you need to configure a CodeBuild project.

Set the current environment image to aws/codebuild/java:openjdk-8

Use the following buildspec.yml in the root of your project:

  • version: 0.2
  • phases:
  • build:
  •   commands:
  •     – echo Build started on `date`
  •     # Unit tests, Code analysis and dependencies check (maven lifecycle phases: validate, compile, test, package, verify)
  •     – mvn verify shade:shade -B -Dorg.slf4j.simpleLogger.log.org.apache.maven.cli.transfer.Slf4jMavenTransferListener=error
  •     – mv target/MyApp-1.0.jar .
  •     – unzip MyApp-1.0.jar
  •     – rm -rf target tst src buildspec.yml pom.xml MyApp-1.0.jar
  •     – aws cloudformation package –template-file main.yaml –output-template-file transformed_main.yaml –s3-bucket myapp-prod-outputbucket-xxxxxxxx
  • cache:
  • paths:
  •   – ‘/root/.m2/**/*’
  • artifacts:
  • type: zip
  • files:
  •   – transformed_main.yaml

Staging Step

After the artifact is built, we now want to create a change set using CloudFormation.

  • Action mode: Create or replace a change set
  • Template: MyAppBuildOut::transformed_main.yaml
  • Stackname: <name of your created stack here>

Define your Lambda function using Java (using serverless format), in your Cloudformation config file, placed in the root of your Maven project.

LambaFunctionName:
     Type: AWS::Serverless::Function
     Properties:
       Handler: au.com.nuamedia.camlinpayment.handler.MenuHandler
       Runtime: java8
       Timeout: 10
       MemorySize: 1024
       Events:
         GetEvent:
           Type: Api
           Properties:
             Path: /menu
             Method: get

Deploy Step

The ChangeSet can then be executed and the changes automatically rolled out to production safely. Any problems encountered and an automatic rollback occurs.

  • Action Mode: Execute changeset
  • Stackname: <name of your created stack here>
  • Change set name: <change set name from previous step>

Outcome

Congratulations! you now have your Java AWS Lamba functions deploying to production using Continuous Deployment. AWS CodePipeline is easily configurable via the UI and can also be defined as code and stored in version control.

The Four Tendencies

Gretchen Rubin says a useful way to think about people’s behavior is by considering how willing they are to meet or resist expectations on them. Expectations can either be external, like your boss asking for a project to be completed or internal, like exercising regularly.

From these she identifies the four combinations labelled as The Four Tendencies.

External Expectation
Internal Expectation
Upholder (tick) (tick)
Questioner (warning) (tick)
Obliger (tick) (warning)
Rebel (warning) (warning)

(tick) Meets (warning) Resists

This could provide you with more empathy when considering your colleagues, friends or family and make you a more effective communicator. Maybe try thinking about members of your software development team and which tendency they seem to exhibit.

Which one are you? Take the quiz and find out.

Does your Kanban maturity level match your team’s ?

A Kanban board seems at first site like something easy to implement. You draw some columns on a wall, put headings for backlog, in progress and done and then stick postit notes all over it to represents tasks, easy right?

Well kind of 🙂

I’ve been promoting the use of Kanban at our company, we have been using it for about 6 months now. I knew it was an incremental approach and that we should introduce something simple and build from there with the attitude of continuous improvement (Kaizen).

However, alot of the Kanban guides push you in at a quite advanced level, talking about limiting Work In Progress (WIP) and pulling work through the system.

For immature teams (which I guess is the majaority first adopting Kanban) this is too much early on and could lead to the team rejecting the kanban system.

After reading David J Anderson’s excellent book I’ve come to realise that the best way is to evolve Kanban into an organisation gradually, being aware of the maturity of your team and matching that to the sophistication of the Kanban system in use.

This is a great article on doing just that:

http://anderson.leankanban.com/kanban-patterns-organizational-maturity/