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Python Recipes on Elastic Beanstalk

This recipe collection extends the core Python tutorial track with integration and platform customization patterns documented by AWS. Each recipe is designed for incremental adoption without assuming a production deployment.

Prerequisites

  • Completed core Python guide through deployment and configuration basics.
  • Familiarity with environment properties and .ebextensions files.
  • IAM permissions for related AWS services used in each recipe.

What You'll Build

You will build optional capabilities around a Python Flask application:

  • RDS connectivity with decoupled database lifecycle.
  • Secrets retrieval with AWS Secrets Manager.
  • Centralized configuration lookup with Parameter Store.
  • Instance profile-based AWS API access without static credentials.
  • DynamoDB-backed key-value data access.
  • ElastiCache Redis-backed caching in VPC contexts.
  • S3 object storage integration using instance profile permissions.
  • VPC endpoint connectivity for private service access.
  • Platform hook customizations and NGINX extension points.
  • Worker environment patterns using SQS and scheduled tasks.
  • Docker-based deployment alternative to native Python platform.
  • Custom CloudWatch metrics for app-level telemetry.

Steps

Choose recipes in this order if you want low-to-high operational complexity:

Order Recipe Primary Service Outcome
1 rds-integration.md Amazon RDS Externalized relational data
2 secrets-manager.md AWS Secrets Manager Runtime secret retrieval
3 parameter-store.md AWS Systems Manager Centralized configuration lookup
4 iam-instance-profile.md IAM Instance role-based AWS access
5 dynamodb.md Amazon DynamoDB Managed key-value storage
6 s3-storage.md Amazon S3 Durable object storage
7 elasticache-redis.md Amazon ElastiCache Low-latency cache layer
8 vpc-endpoints.md Amazon VPC Private AWS service connectivity
9 custom-platform-hooks.md Platform hooks Deployment lifecycle extensions
10 sqs-worker.md Amazon SQS Queue-driven worker tier
11 worker-environments.md Amazon SQS Async and scheduled processing
12 docker-multi-stage.md Docker Smaller runtime images
13 docker-deploy.md Docker on EB Containerized deployment path
14 cloudwatch-custom-metrics.md Amazon CloudWatch Application-specific telemetry 
flowchart TD
    A[Core Python Web Environment] --> B[RDS Integration]
    A --> C[Secrets Manager]
    A --> D[Parameter Store]
    A --> E[IAM Instance Profile]
    A --> F[DynamoDB]
    A --> G[S3 Storage]
    A --> H[ElastiCache Redis]
    A --> I[VPC Endpoints]
    A --> J[Custom Platform Hooks]
    A --> K[SQS Worker Patterns]
    A --> L[Docker Options]
    A --> M[CloudWatch Custom Metrics]

Verification

Before starting any recipe, run baseline checks:

eb status "$ENV_NAME"
eb printenv
eb logs --all

Recipe completion checks should include:

  • Service-specific connectivity validation.
  • Environment events and health review.
  • Configuration committed to source control.
  • No unmasked account IDs or sensitive tokens in docs output.

Suggested verification order for each recipe:

  1. Confirm environment state with eb status and eb health.
  2. Confirm configuration values with eb printenv.
  3. Confirm logs with eb logs --all.
  4. Confirm AWS service API visibility with targeted aws CLI commands.

Operational note from Elastic Beanstalk docs context:

  • Prefer decoupled managed services (RDS, ElastiCache, S3) for durability and replacement-safe operations.
  • Keep application versions immutable and traceable when testing recipe changes.
  • Use masked placeholders in shared command outputs (<account-id>, <db-password>).

See Also

Sources