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How to Set Up a Continuous Deployment Pipeline for Your Serverless App
Dec 23rd, 2024|
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ServerlessContinuous deployment (CD) is a software development practice that automates the release of code changes to production, ensuring updates are delivered reliably and efficiently. It’s about being able to reliably release software to production at any time, using automation to streamline the build, test, and release process. When done right, CD leads to reduced deployment risk, faster time-to-market, and higher product quality. Serverless architectures, known for their flexibility and scalability, are an excellent fit for these principles, as they’re designed to handle dynamic workloads and evolve quickly.
However, one key aspect of CD that often lags behind is database schema management. While code changes can easily integrate into pipelines, database modifications frequently remain a manual, error-prone process that slows the pace of innovation. Applying CD principles to both your application code and your database schema ensures your entire system—front to back—can iterate rapidly without breaking data integrity or introducing regressions.
In this post, we’ll explore how to set up a continuous deployment pipeline for a serverless app that doesn’t just handle code deployments effortlessly, but also smoothly manages database schema updates. We’ll also highlight how modern databases like Fauna enable frictionless schema changes in a CI/CD workflow.
Why Continuous Deployment Matters for Serverless Apps
Serverless computing lets development teams build and run applications without managing servers. Yet, even though you’ve offloaded infrastructure concerns, the speed at which you can safely update and improve your application still hinges on the efficiency of your deployment process. A continuous deployment pipeline ensures that:
- You deliver new features faster: No waiting on manual approvals or tedious deploy steps.
- Your changes are always tested and validated: Automated tests catch issues before they hit production.
- Deployments become routine: Continuous deployments reduce stress by making releases a normal, low-risk event rather than a major, high-stakes happening. This streamlined approach helps your serverless stack scale confidently, responding to user needs at the pace your business demands.
The Database Challenge in Continuous Deployment
While serverless platforms handle scalability on the compute side, databases introduce unique hurdles. Databases are stateful systems and schema changes can have far-reaching consequences. A new table structure, a revised index, or an updated field type can break queries and cause data inconsistencies if not orchestrated carefully.
Traditionally, teams have handled database updates manually—logging into production environments, running ad-hoc migrations, and hoping for the best. This approach is risky, slow, and entirely at odds with the automation-centric philosophy of continuous deployment.
Traditionally, database changes often happened outside the application’s standard change management pipeline—operations teams would manually connect to production systems, run migrations with ad-hoc scripts, and trust their memory and notes to avoid mistakes. This process isn’t just slow; it’s extremely error-prone and one slip can be catastrophic. Recovery might be possible if you’ve rigorously tested backups and disaster recovery policies, but that’s a best-case scenario after the damage is already done. The manual approach stands in stark contrast to modern automation and continuous deployment practices, where changes are vetted, tested, and deployed through repeatable, controlled pipelines—greatly reducing the chance of human error.
To make database schema changes fully compatible with a serverless continuous deployment pipeline, you need:
- Programmatic schema management: Treat database schemas like code—versioned, reviewed, and deployed automatically.
- Integration with CD tools: Seamlessly incorporate schema changes into your CI/CD pipeline.
- Transactional changes and rollbacks: Apply updates safely and revert them cleanly if something goes wrong.
- Automated validations and tests: Confirm schema changes work with existing data and queries before they hit production.
- Zero-downtime migrations: Move from one schema version to the next without impacting availability.
Step-by-Step: Setting Up a Continuous Deployment Pipeline
Let’s break down the key steps for implementing a continuous deployment pipeline for your serverless app—from code to schema.
1. Choose the Right Tools and Frameworks
- Serverless Framework or AWS SAM: These help define and deploy your serverless application resources as code.
- CI/CD Services: Use platforms like GitHub Actions, GitLab CI, or CircleCI to automate builds, tests, and deployments.
- Serverless-Friendly Database: Pick a database that supports automated schema changes. For example, Fauna’s Schema as Code approach allows you to define, version, and apply schema changes alongside application code.
2. Store Everything in Version Control
Keep both your application code and your database schema definition files in a single repository. By doing so:
- Unified Review Process: Code reviewers can comment on both app changes and schema updates.
- Traceability: You can quickly see which schema version corresponds to a given release of your app.
- Rollback Safety: Reverting to a previous commit also reverts to the prior schema state.
3. Automate Builds and Tests
Set up your CI pipeline to automatically run whenever you push changes to your main branch or open a pull request:
- Build: For whatever framework you may be running (Node.js, Python, Go, etc.), install dependencies and compile if necessary.
- Unit Tests: Run tests against your application code to ensure logic changes are sound.
- Integration Tests: Spin up a test environment (often a temporary serverless stack) and apply the schema changes. Validate that your application works with the updated database schema. This automated test cycle verifies that both your code and schema changes are compatible and ready for production.
4. Apply Schema Changes as Part of Your Deployment
When your tests pass, your CI pipeline should trigger the CD pipeline. This pipeline should:
- Deploy Infrastructure Updates: Using your serverless framework, apply infrastructure changes (like new functions, event triggers, etc.).
- Deploy Schema Updates: Use your database’s CLI or API to apply the schema changes defined in your repository. Tools like Fauna’s CLI can automatically apply changes in a transactional manner, ensuring consistency. This integration ensures that app changes and schema modifications roll out together, so your code isn’t expecting one schema while the database still runs another.
5. Ensure Zero-Downtime Migrations
A robust approach to schema migration helps ensure no downtime. Techniques include:
- Gradual Migrations: Update your schema incrementally, ensuring old and new versions can coexist temporarily.
- Data Transformation Automation: Execute data migrations within the pipeline so that when your new schema is active, the data already fits the updated structure.
- Rollback on Failure: If something goes wrong, revert to the previous schema version and code release automatically, minimizing impact. With transactional support and validation features, databases like Fauna can help streamline these zero-downtime transitions.
6. Add Observability and Monitoring
After deployment, continuously monitor your production environment:
- Metrics and Logs: Keep tabs on function performance, query latency, and error rates.
- Alerts: Set up alerts for schema-related errors or slow queries.
- Performance Testing: Regularly run performance tests to ensure that scaling your serverless app doesn’t degrade user experience. Observability closes the loop in your continuous deployment pipeline, providing feedback that informs your next iteration.
How Fauna Simplifies CD for Serverless Database Schema
Modern databases like Fauna align naturally with CD principles. Fauna’s distributed, serverless architecture and its Schema as Code approach help you:
- Version Control and Code Reviews: With Fauna Schema Language (FSL), define your schema as code, store it in Git, and review changes just like application code.
- CI/CD Integration: Automate schema deployments right alongside app deployments using Fauna’s CLI within your build pipeline.
- Zero-Downtime Migrations: Fauna’s transactional model ensures that schema changes don’t require service interruptions or manual interventions.
- Built-In Validation: Fauna validates schema changes against existing data, ensuring no surprises at runtime.
By choosing a serverless database that embraces CD practices, you remove a key barrier to continuous deployment and keep your entire stack—code and data—moving at the speed of innovation.
Conclusion
Setting up a continuous deployment pipeline for your serverless app involves more than automating code releases; it requires extending CD principles to your database schema. By applying programmatic schema management, transactional changes, automated validations, and zero-downtime migrations, you ensure that every release is reliable, scalable, and risk-free.
Tools like Fauna make it possible to manage both code and schema in the same CI/CD pipeline, bridging the historical gap between application and database deployments. Embrace these strategies, and your serverless stack can evolve rapidly and confidently, delivering the features your users need—exactly when they need them. For more information on Fauna, If you're interested in exploring Fauna's approach further, check out the docs and schedule a demo if you'd like to see it in action or have any questions.
If you enjoyed our blog, and want to work on systems and challenges related to globally distributed systems, and serverless databases, Fauna is hiring
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