Serverless computing is a popular paradigm that allows you to run code without provisioning or managing servers. However, it also comes with some challenges, such as how to handle dependencies and versioning. In this article, you will learn some best practices and tools to manage these aspects in serverless environments.
Dependencies are the external libraries or modules that your code relies on to function properly. Versioning is the process of assigning a unique identifier to each release of your code or dependency. Both dependencies and versioning are important for ensuring the quality, security, and compatibility of your code. However, in serverless environments, they can also affect the performance, cost, and complexity of your deployments.
Managing dependencies in serverless environments can be challenging, due to slow cold starts, increased memory usage, and deployment limits. To avoid these issues, you should use a dependency manager, such as npm or pip, to specify and install the exact versions of the dependencies you need. Additionally, bundlers like webpack or rollup can reduce the size and complexity of your dependencies by removing unused code and combining multiple files. You can also use layers like AWS Lambda Layers or Google Cloud Functions Layers to separate your dependencies from your code and reuse them across multiple functions. Furthermore, native dependency compilers such as serverless-plugin-chrome or serverless-ruby-layer can compile and package dependencies that require native binaries or libraries.
For serverless projects, install packages locally using dependency managers such as npm or yarn, then commit the precise versions to source control. The code is stable in all environments thanks to vendor lock files. For deployment as a unified unit, containerize functions and dependencies. Use function runtime stacking to maximize package reuse. To examine interdependencies between functions and enforce versions during deployment, make use of orchestration services. Carefully assess the tradeoffs between embedding dependencies and employing layering for better cold start performance.
Managing versioning in serverless environments can be challenging, so you may need to implement strategies such as using a version control system, like Git or Mercurial, to store and manage code and dependency versions in a repository. Additionally, a semantic versioning scheme, such as MAJOR.MINOR.PATCH, can indicate the level of changes and compatibility of releases. A testing framework like Jest or Mocha can be used to write and run unit and integration tests for code and dependency versions. Deployment tools like Serverless Framework or AWS SAM can automate and simplify the deployment process to the cloud provider. Furthermore, a versioning feature such as AWS Lambda Versions or Google Cloud Functions Versions can create and manage immutable snapshots of code and dependency versions in the cloud provider. Last but not least, an alias feature like AWS Lambda Aliases or Google Cloud Functions Aliases can point to specific versions of code and dependencies in the cloud provider and enable easy switching and rollback.
Serverless components, which are frequently deployed independently, such as functions, databases, storage, API gateways, etc., require strict version control. At every logical transition, tag significant versions. To efficiently handle releases, updates, and deprecations, adhere to the semantic versioning rules. Before removing, keep earlier versions around for auditing and rollback purposes. Rigidly log versions against deployments to aid in issue diagnosis and reproduction. Utilizable built-in version control features are another feature of several serverless frameworks. Assign distinct versions to connected function groups that get updates simultaneously.
The final challenge of managing dependencies and versioning in serverless environments is how to monitor and update them regularly. Depending on the criticality and vulnerability of your code and dependencies, you may need to use tools such as a dependency checker, dependency updater, dependency locker, version tracker, or version switcher. For instance, npm audit or pip check can scan and report any security or compatibility issues with your dependencies. Dependabot or Renovate can automatically detect and create pull requests for updating your dependencies. To lock your dependencies to specific versions, you can use npm shrinkwrap or pip freeze. Additionally, Sentry or Datadog can be used to monitor and alert any errors or anomalies with your code and dependency versions in the cloud provider. Finally, AWS CodeDeploy or Google Cloud Traffic Splitting can be used to gradually and safely shift the traffic between different versions of your code and dependency versions in the cloud provider.