Zabezpieczanie i skalowanie API produkcyjnego

A microservice that runs is not the same as one ready for real traffic. Production demands authentication, scaling limits, environment separation, and guardrails against abuse.

Protect your endpoints with a JWT or Cognito authorizer so only valid tokens reach your business logic. Public endpoints should be the exception, not the default.

For partner access, issue API keys tied to usage plans that enforce per-client throttling and monthly quotas.

Set account- and method-level throttles so a traffic spike or a misbehaving client cannot overwhelm downstream resources or blow up your bill.

Reserved concurrency caps how many instances a function can use; provisioned concurrency keeps instances warm to remove cold starts on critical paths.

Lambda can scale faster than a relational DB can accept connections. Use RDS Proxy or DynamoDB to absorb concurrency without exhausting connections.

Separate dev, staging, and prod stages with their own variables and resources, so testing never touches production data.

Reject malformed requests at API Gateway with request validators and models, so invalid input never even invokes your Lambda — saving cost and reducing attack surface.

Attach AWS WAF to block common attacks (SQL injection, bad bots) and to add IP-based rate rules in front of your API.

Each function should have a least-privilege execution role: grant only the specific actions and resource ARNs it needs, never broad wildcards.

Before going live confirm:

• Auth on every non-public route
• Throttling, quotas, and WAF in place
• Concurrency limits and a scalable data layer
• Separate prod stage and least-privilege IAM

You learned to harden a serverless API:

• Authenticate callers; use API keys and usage plans
• Throttle, set quotas, and add WAF
• Control concurrency and protect the data layer
• Separate stages and apply least-privilege IAM