Productionisation Checklist

Project readiness checklist

Ensuring that your project adheres to the following RFCs is a good first step as these will be referenced further below:

1. General requirements

  • 1.1 Application source code hosted with a Git VCS service
  • 1.2 Adhere to project coding standards
    • 1.2.1 Provides a style guideline
    • 1.2.2 Enforce coding standards (e.g. automated linter on code changes)
  • 1.3 .editorconfig as per RFC 011
  • 1.4 Makefile as per RFC 012
  • 1.5 README.md as per RFC 013
  • 1.6 README.md to also include references for all 3rd party service integrations
  • 1.7 Local development seeds from production-like data (similar sized datasets - to assist with debugging and for diagnosing unusual performance regressions):
    • 1.7.1 Seed a specific item (for example, a product in an ecom system)
    • 1.7.2 Seed a specified number of items in batch
    • 1.7.3 Seed full catalogue of items
  • 1.8 Local development seed fixtures (for example, using Faker or AutoFixture)
  • 1.9 Install an application profiler for the development environment so that metrics such as page render times, database query times can be used to make performance improvements
  • 1.10 Decision making process documented using Architecture Decision Records (ADRs)

2. Testing

  • 2.1 Test code coverage of 90% minimum
  • 2.2 Unit tests that run in under 30 seconds
  • 2.3 End-to-end tests that run in under 5 minutes

3. Environments

  • 3.1 Application has corresponding environments and hosting for:
    • 3.1.1 testing should only be accessed by those within delivery teams
    • 3.1.2 staging for external reviews and high level end-to-end testing in a production-like infrastructure
    • 3.1.3 production for live usage and showcasing to customer

    Note: All environments should have the same setup, however staging/testing can operate at a smaller scale (less/smaller infrastructure) than production

4. Database

  • 4.1 Production database has:
    • 4.1.1 Automatic failover
    • 4.1.2 Daily automatic backups
    • 4.1.3 If feasible with provider, enable transaction log backups for PIT (Point in Time) restore ability

5. Pipeline

  • 5.1 Continuous Delivery pipeline configured to:
    • 5.1.1 Automatically test pull requests
    • 5.1.2 master branch to run code checks
      • 5.1.2.1 Code standard checks (linting)
      • 5.1.2.2 Tests
    • 5.1.3 Automatic deploy to staging environment
    • 5.1.4 Manual step to deploy to production environment
    • 5.1.5 Zero downtime (e.g. blue/green environment) deployment step to all environments
  • 5.2 All pipeline steps are defined in code within repository for chosen pipeline service

6. Application logging

  • 6.1 Remote logging service installed and configured as remote application logger for:
    • 6.1.1 Main application
    • 6.1.2 Background workers
  • 6.2 Appropriate log level configured:
    • 6.2.1 production set to INFO
    • 6.2.2 staging set to DEBUG
    • 6.2.3 testing set to DEBUG
  • 6.3 Tagged logging configured to include:
    • 6.3.1 (Sub)domain of request
    • 6.3.2 Application environment (production, staging or testing)
    • 6.3.3 UUID of request
    • 6.3.4 Session ID
  • 6.4 Ensure HTTP requests are condensed to a single line log output including:
    • 6.4.1 IP address of originating request
    • 6.4.2 HTTP method
    • 6.4.3 HTTP parameters
  • 6.5 Ensure sensitive parameters are filtered from logs

7. Exception tracking

  • 7.1 Remote exception tracking service installed and configured for exception capture for all non-development environments
  • 7.2 Alerts sent to relevant instant chat channel
  • 7.3 Alerts sent to relevant team email address
  • 7.4 UUID of request is sent as additional user data
  • 7.5 Reported exceptions are resolved within a week Exceptions that have been thrown but not caught or handled safely could lead to larger problems for applications and teams. It’s good for teams to have the discipline of regularly checking, or acting upon reported exceptions as they occur during development to prevent these from accruing. If code changes have been made to handle these, the exceptions should be marked as resolved in the tracking service. No reported exceptions in the past week is a positive sign of well managed exceptions.

8. Infrastructure monitoring and scaling

To be applied if infrastructure has been orchestrated and provisioned specifically for the project. Hosted PaaS solutions don’t require infrastructure related monitoring at present.

  • 8.1 Sub-organisation created under parent organisation for each customer
  • 8.2 Monitoring agent be installed on all production infrastructure
  • 8.3 Monitoring agent could be installed on non-production infrastructure if necessary
  • 8.4 Monitoring agent hostname configured according to proposed RFC 008 - Server naming convention (this does not apply to serverless)
  • 8.5 Infrastructure to implement auto-scaling for production
  • 8.6 Monitors configured in infrastructure monitoring service for (warn/alert):
    • 8.6.1 Inode usage (80% / 90%)
    • 8.6.2 CPU load (75% / 85% average over 2 minutes)
    • 8.6.3 Disk usage (80% / 90%)
    • 8.6.4 Memory usage (60% / 70% average over 2 minutes)
    • 8.6.5 Host stopped reporting
    • 8.6.6 NTP sync
  • 8.7 Monitors configured to alert via:
    • 8.7.1 Slack channel
    • 8.7.2 Team email address

9. Application performance management

  • 9.1 APM service configured to monitor
    • 9.1.1 App performance
    • 9.1.2 Request time

10. Vulnerability alerts

  • 10.1 Configure either VCS hosting service or Continuous Delivery pipeline to detect and alert on vulnerable dependencies

11. Dependency upgrade alerts

  • 11.1 Configure a dependency upgrade notification service to submit pull requests to VCS service repository with alerts

Platform specific

Suggested services

  • VCS hosting - Github
  • Central logging - Papertrail, CloudWatch
  • Exception tracking - Sentry
  • Infrastructure monitoring - Datadog, CloudWatch
  • Security vulnerability scanning - Github
  • Dependency upgrade notifications - Dependabot

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