I wanted to start a serverless project, and one of the primary headaches aside from architecting the workflow and deciding which lambda functions need to be created is a simple and yet effective CICD workflow. Typical AWS’s suggestion is to use a combination of CodeCommit, CodeBuld, CodeDeploy, and glue everything together in CodePipeline. But I already have GitHub for other projects, so setting up CodeCommit will be unnecessary. The same applies to CodeBuild whose functions I currently perform with TravisCI, where I run both integration and feature specs. This will be a NodeJS project, and I am interested in fully testing my functions at the Build phase using Jest. I also know I can adapt TravisCI to perform CodeDeploy’s functions in deploying code changes to production. But I still want my serverless function run on AWS Lambda. So here is my plan; I use Github for my code repository, and for creating and deploying my functions to AWS while running the Build phase on Travis. The build phase on Travis will run Jest tests on the functions, if all tests pass, it deploys the code on AWS Lambda using the serverless CLI depending on the working branch. I will create two environments, one for staging and the other for production. The staging branch deploys to my staging env, while the master branch deploys to production. Other branches will only run Jest tests on the lambda code and will not deploy. Serverless Framework All code used on this . Alright then, here we go. hands-on is available here on Github Setting up the SLS functions and Github Repo Create a new repository for our project on Github. I call mine lambda-cicd . I will clone the repository to my local workspace with: $ git clone git@github.com: <project name>.git / < > github username Mine is $ git clone git@github.com:lekansogunle/lambda-cicd.git Next, create two serverless AWS functions. The concept is to be able to have multiple functions in the same project and each deploying as need be to AWS Lambda. I call my two functions init-user and create-post . Hypothetically, we can say the first function is to create a new user, while the second is used to create blog posts for our user. We will only stick to the boilerplate code mostly and not implement details of these functions. Install serverless CLI with: $ npm install -g serverless I will create my two functions with the . SLS CLI command for creating AWS Lambda services $ sls create --template aws-nodejs --path myService Replacing my myService with init-user and create-post for my two functions. $ sls create --template aws-nodejs --path init-user $ sls create --template aws-nodejs --path create-post Test My Services with JEST Now that we have all the functions, I will add the to the project and perform very simple testing of my functions. At the root of the project directory do: Jest testing framework $ yarn add --dev jest This adds a package.json at the root directory and installs Jest. For Jest to pick up our tests, we need to add a __test__ directory in both directories holding each service. And this test folder will hold test files ending in .test.js . For consistency, since our services are named handler.js by default from SLS, I will name the tests also handler.test.js . Next, I will go into the handler functions created for both services and change the message text to something different. For init user, I addHello from init user as a return message. My test will assert that the function returns this exact same output. Definitely, it gets far more complicated than this when the functions are fully implemented. My project file structure looks like this so far: ├── create-post
│   ├── __test__
│   │   └── handler.test.js
│   ├── handler.js
│   └── serverless.yml
├── init-user
│   ├── __test__
│   │   └── handler.test.js
│   ├── handler.js
│   └── serverless.yml
├── package.json
└── yarn.lock Before writing the tests, now will be a good time to make a commit. Add a file to the root of the project and write in there .We don't want to commit our . Make a commit and push the changes so far. From your root folder, run the tests and get two failures saying; .gitignore node_modules node_modules $ yarn run jest Your test suite must contain at least one test. I ended up having my create-post lambda function and it’s jest test look like; ; .exports.createPost = { { : , : .stringify(
      { : , : event,
      }, , ),
  };
}; 'use strict' module => event return statusCode 200 body JSON message 'Hello From Create Post!' input null 2 handler = ( );

test( , () => {
  expect(handler.createPost({ : })).toStrictEqual({ : , : .stringify(
      { : , : { : },
      }, , ),
  });
}); const require '../handler' 'correctly create post' foo 'bar' statusCode 200 body JSON message 'Hello From Create Post!' input foo 'bar' null 2 Notice I changed the function name from to , removed from the function for now. In the test, I am using as dummy event. Then I am asserting the exact response from our function with a . Running the test now will pass with a hello createPost async {foo: 'bar'} strictEqual Setup two AWS IAM account For the next step, we will have to create two AWS IAM accounts. One for the staging environment and the other for our production environment. Here is a to creating IAM users. You will have to namespace the accounts with the environment they belong to (production and staging) respectively so as to clearly identify the accounts in the future. For example, production-user and staging-user. Also, follow the guide to make sure you give correct access rights. As you proceed, carefully note both Access Key Id and Secret Access Key for each user. Save these credentials in a secure place to be used in the coming steps. guide Configure TravisCI Before we configure TravisCI, we will commit everything we have and create a new branch. Call it staging and push this branch to Github. This branch will be used to create a staging deployment to AWS from TravisCI. If you do not already have an account, create an account with TravisCI and install the Github App Integration into your Github account. Then visit . Here, we are able to connect our GitHub repositories to Travis for running continuous integration jobs. Then click on settings as shown from below https://travis-ci.com/account/repositories The most important section here is the environment variables section. There you will notice we can set , , and for each credential. name value branch For example, staging we set the name as , set value as the value noted in the previous section from our AWS IAM staging user, and then we select the branch as . AWS_ACCESS_KEY_ID AWS_ACCESS_KEY_ID staging We do this for all four credentials. SLS CLI will automatically pick up these variables as the setup credentials when present in the job machine. Then we add another variable, to let serverless know what stage we are deploying to. The value is for the staging branch and for the master branch. We will then have a total of 6 env vars like below STAGE_NAME staging production Next, we create a file at the root of our project. Then we create a bin directory, in there we create a deploy bash script. The file will hold our TravisCI specific configurations and our script will hold the SLS deploy script commands. The and files will have the following .travis.yml .travis.yml bin/deploy .travis.yml bin/deploy language: node_js node_js: - "10" cache: directories: - node_modules - ${SERVICE_PATH}/node_modules install: - yarn global add serverless - travis_retry yarn install - cd ${SERVICE_PATH} - travis_retry yarn install - cd - script: - yarn run jest jobs: include: - name: "Deploy User Init API" env: - SERVICE_PATH="init-user" - name: "Deploy Create Post API" env: - SERVICE_PATH="create-post" deploy: provider: script script: bash bin/deploy on: all_branches: true condition: $TRAVIS_BRANCH =~ ^(master|staging)$ serverless deploy -s - #!/usr/bin/env bash cd ${SERVICE_PATH} ${STAGE_NAME} cd Next, make sure our deploy script is executable with the following $ chmod u+x bin/deploy Most important parts of our file specify install commands to be run both globally and in the separate function directories. It also installs the serverless CLI globally for deploying. The section allows us to run Jest tests in our build and the output will determine if Travis proceed to deploy the build. If the test fails, TravisCI will not proceed to deploy. .travis.yml script Otherwise, the build will be deploy after the test passes. Here, we include two sections under so as to allow TravisCI to create two separate build jobs, one for each function. That is why we specify different env var as the name of the two lambda directories in our project. In the section, we specify a strategy and mention which script command to run when TravisCI is ready to deploy our functions to AWS. Lastly, Travis checks all branches and deploy only the ones matching the condition that their branch name is either master or staging. job SERVICE_PATH deploy script _BRANCH =~ ^(master|staging)$ $TRAVIS The deploy script changes directory to the specified for each build job. Runs serverless deploy command and changes directory back out to the root directory. SERVICE_PATH Configure Serverless Next, we will change some things in the . First, we add serverless.yml custom: stage: ${opt:stage, self:provider.stage} This is to tell serverless to take in the stage option as specified when running the CLI command and then set this stage when deploying. If not present, it uses the default provided under which is . provider.stage dev Next, you will want to confirm the runtime value under the provider to be we will keep this uniform with what we have in our TravisCI. Lastly, we will change the handler from to and in the appropriate file. The init-user looks like this: nodejs10.x handler.hello handler.initUser handler.createPost serverless.yml serverless.yml service: init-user frameworkVersion: '2' provider: name: aws runtime: nodejs12.x functions: hello: handler: handler.initUser Finally, Launch Lambdas 🚀 Commit what we have and push to the staging branch. You will notice a new build started on Travis with two jobs. The jobs should pass, then I will create a pull request and merge into the master branch to deploy our production lambdas. Wait for the master branch to be green and deploy the production lambdas. And on AWS, you will be able to see both your staging and production lambda functions deployed. All the code for this project is available on and . If you have come this far, I hope this follow-along has helped you smoothly create a lambda CICD workflow. Let me know how the process works for you! GitHub here TravisCI builds are available here Also published at https://medium.com/@OlalekanSogunle/create-a-ci-cd-pipeline-for-nodejs-lambdas-on-aws-using-jest-serverless-framework-github-and-d4c68dc77793

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