Archive and search your tweets and liked tweets using AWS Lambda, DynamoDB and Elasticsearch.

Note: this project is primarily being used a test bed for figuring out best practices with AWS Lambda



Make sure you have the following installed before you proceed


Twitter API key setup

Set up a Twitter Developer account. Once you are signed up, create an app.

Add the credentials to SSM Parameter Store:

aws ssm put-parameter --name /tweeter/twitter/consumer_key --value <your consumer key value> --type SecureString --overwrite aws ssm put-parameter --name /tweeter/twitter/consumer_secret --value <your consumer secret value> --type SecureString --overwrite aws ssm put-parameter --name /tweeter/twitter/access_token --value <your access token value> --type SecureString --overwrite aws ssm put-parameter --name /tweeter/twitter/access_token_secret --value <your access token secret value> --type SecureString --overwrite

Elastic Cloud setup

Elastic Cloud is not free

Set up an account with Elastic Cloud. Create a deployment and then an Elastic App Search engine. Retrieve the private key from the Credentials section.

Add the private key to SSM.

aws ssm put-parameter --name /tweeter/es/private_key --value <your password> --type SecureString --overwrite

Also, update the configuration in ui/src/config/engine.json, specifically the values of endpointBase and searchKey.

Deploy the backend

Build and deploy your application for the first time by running the following commands in your shell:

make build make deploy.guided

The first command will build the source of your application within a Docker container. The second command will package and deploy your application to AWS. Guided deploy means SAM CLI will ask you about the name of your deployment/stack, AWS Region, and whether you want to save your choices, so that you can use make deploy next time.

Deploy the frontend

In the ui directory, deploy the application with AWS Amplify.

amplify publish

Use the SAM CLI to build and test locally

Whenever you change your application code, you'll have to run build command:

make build

The SAM CLI installs dependencies defined in poller/requirements.txt, creates a deployment package, and saves it in the .aws-sam/build folder.

Test a single function by invoking it directly with a test event:

make invoke.poller make invoke.indexer

Working with localstack

Validate DynamoDB was populated using Localstack:

docker-compose up -d make invoke.poller aws --endpoint-url=http://localhost:4566 dynamodb scan --table-name TweetsTable --max-items 10

An event is a JSON document that represents the input that the function receives from the event source. Test events are included in the events folder in this project.

Fetch, tail, and filter Lambda function logs

To simplify troubleshooting, SAM CLI has a command called sam logs. sam logs lets you fetch logs generated by your deployed Lambda function from the command line. In addition to printing the logs on the terminal, this command has several nifty features to help you quickly find the bug.

NOTE: This command works for all AWS Lambda functions; not just the ones you deploy using SAM.

sam logs -n TweeterPoller --stack-name tweeter --tail

You can find more information and examples about filtering Lambda function logs in the SAM CLI Documentation.

CI/CD with GitHub


Create a user github with the following policy:

Create secrets with AWS.



Follow the AWS Amplify console to configure the frontend.


  1. Set StreamModeEnabled to false in samconfig.toml the first time you run the poller to get all tweets.
  2. Twitter apparently only allows access to a user's most recent 3,240 tweets with this method.
  3. This probably isn't the best use case for Lambda, which has a timeout of 15 minutes. Ideally we should be calling Fargate for long running task. That said, in practice, because of the limitations of Twitter's API, getting all the available tweets is well within that limit.

Appendix: Powertools


Tracer utility patches known libraries, and trace the execution of this sample code including the response and exceptions as tracing metadata - You can visualize them in AWS X-Ray.


Logger utility creates an opinionated application Logger with structured logging as the output, dynamically samples 10% of your logs in DEBUG mode for concurrent invocations, log incoming events as your function is invoked, and injects key information from Lambda context object into your Logger - You can visualize them in Amazon CloudWatch Logs.


Metrics utility captures cold start metric of your Lambda invocation, and could add additional metrics to help you understand your application KPIs - You can visualize them in Amazon CloudWatch.



GitHub - ksindi/tweeter: Archive tweets and make them searchable
Archive tweets and make them searchable. Contribute to ksindi/tweeter development by creating an account on GitHub.