Mastering AWS Lambda: FAQs and Best Practices for High-Traffic Applications

AWS Lambda is a powerful serverless computing service, but understanding its capabilities and limitations is essential for designing scalable and efficient applications. Let’s dive into some commonly asked questions about AWS Lambda and its concurrency model and explore how it compares to EC2.

1. Can AWS Lambda Handle Multiple APIs in a Single Function?

Yes! AWS Lambda can handle multiple APIs within a single function by using a router or framework (e.g., Flask for Python or Express for Node.js). You can route requests based on the HTTP method (GET, POST, PUT, etc.) and path.

However, all APIs within a single Lambda share the same concurrency limit, which could lead to resource contention if one API is heavily used.

Best Practice: If APIs are tightly coupled (e.g., CRUD operations for the same resource), grouping them in one Lambda is fine. For independent APIs or high-traffic scenarios, separate them into different Lambda functions.

2. What Is Concurrency in AWS Lambda?

Concurrency refers to the number of requests that a Lambda function can handle simultaneously. Each concurrent request is processed in its own isolated execution environment (container).

• Default Limit: AWS provides a default concurrency limit of 1,000 concurrent executions per region, shared across all Lambda functions in your account.
• Scaling: If 1,000 requests arrive at the same time, Lambda will create up to 1,000 execution environments. If another 1,000 requests arrive while the first batch is still running, they’ll be throttled unless your concurrency limit is increased.

3. Does the 1,000 Concurrency Limit Apply to Each API?

No. The 1,000 concurrency limit applies to the entire Lambda function, not individual APIs. If multiple APIs (e.g., GET, POST, PUT) are implemented in one Lambda, they all share the same concurrency pool.

Example:

• 600 GET requests, 300 POST requests, and 100 PUT requests arriving at the same time will consume all 1,000 concurrent executions.
• If 1,000 GET requests arrive alone, POST and PUT requests will be throttled until capacity is freed.

4. Can I Increase the 1,000 Concurrency Limit?

Yes! AWS allows you to request an increase in the concurrency limit.

Steps to Increase Concurrency:

1. Go to the Service Quotas Console in AWS.
2. Select AWS Lambda and request a higher concurrency limit.
3. Provide justification, such as expected traffic patterns and criticality of your application.

5. What Happens When Lambda Is Throttled?

If Lambda reaches its concurrency limit, additional requests are either delayed or dropped, depending on the invocation type:

• Synchronous Invocations (e.g., API Gateway):
• Asynchronous Invocations (e.g., S3, SNS):
• Stream-Based Invocations (e.g., Kinesis, DynamoDB Streams):

6. How Can I Prevent Dropped Requests?

To avoid losing requests, implement these best practices:

1. Use Dead-Letter Queues (DLQ): Capture failed events for later reprocessing.
2. Leverage SQS or Kinesis: Queue incoming requests and process them gradually to avoid spikes.
3. Request a Concurrency Limit Increase: Scale your limits to match your workload.
4. Enable Provisioned Concurrency: Pre-warm Lambda environments to handle predictable traffic spikes.
5. Optimize Execution: Minimize Lambda’s execution time to free up concurrency faster.

7. When Should I Choose Lambda vs EC2?

AWS Lambda and EC2 serve different purposes. Here’s a quick comparison:

FeatureAWS LambdaAWS EC2CostPay-per-execution (serverless)Pay for uptime (fixed pricing)ScalingAutomaticManual or auto-scalingRuntimeLimited to 15 minutesUnlimitedEnvironment ControlLimited (managed by AWS)Full control (OS, software, etc.)StateStatelessStatefulBest ForEvent-driven, short-lived tasksLong-running, compute-intensive workloads

8. Real-World Use Case Example

Scenario: You’re building an API backend with multiple endpoints (e.g., GET, POST, PUT).

• If Traffic is Sporadic: Use a single Lambda function with a router to handle all APIs. Leverage API Gateway for request routing.
• If Traffic is Heavy: Separate APIs into individual Lambda functions and assign reserved concurrency to critical endpoints.
• For Long-Running Tasks: Offload background jobs to EC2 instances or use Step Functions to orchestrate workflows.

Key Takeaways

• AWS Lambda’s 1,000 concurrent executions limit applies to the entire function, not individual APIs.
• You can increase this limit by submitting a service quota request.
• To prevent dropped requests, implement retries, use DLQs, and leverage queuing services like SQS.
• Choose Lambda for event-driven, short-lived tasks and EC2 for long-running, compute-intensive workloads.

By understanding Lambda’s concurrency model and designing with scalability in mind, you can build robust, cost-effective applications capable of handling high traffic without dropping requests.

What are your thoughts on this? Are you using Lambda or EC2 for your workloads? Let’s discuss in the comments!