What is AWS Lambda? Serverless Computing for Applications

Running backend code traditionally means provisioning servers, scaling resources, and handling uptime.
With AWS Lambda, you can run code without managing any infrastructure, paying only for what you use.

What is AWS Lambda?

AWS Lambda is a serverless compute service from Amazon Web Services.
Instead of running applications on dedicated servers, you write functions that execute in response to events such as:

• HTTP requests through Amazon API Gateway
• File uploads to Amazon S3
• Database updates in Amazon DynamoDB
• Scheduled tasks (cron jobs) via Amazon EventBridge or Amazon CloudWatch Events

Your code runs inside ephemeral containers managed entirely by AWS.
You simply provide the function code and configuration; Lambda handles the rest.

Why use AWS Lambda?

• No Server Management → No provisioning, patching, or scaling of servers.
• Automatic Scaling → Instantly runs as many instances as needed, from one request to thousands per second.
• Pay-as-You-Go → Billed only for the compute time (milliseconds) and requests, not idle time.
• Multiple Language / Environment Support → Node.js, Python, Java, Go, Ruby, .NET, and custom runtimes.
• Easy Integration → Works seamlessly with Amazon S3, Amazon DynamoDB, Amazon SNS, Amazon API Gateway, and other AWS services.
• Built-in High Availability → Runs across multiple Availability Zones for fault tolerance.

Common Use Cases

• Web APIs → Combine Lambda with Amazon API Gateway to build serverless REST or GraphQL APIs.
• File Processing → Process images, videos, or documents automatically after Amazon S3 uploads.
• Scheduled Jobs → Replace cron servers with Amazon CloudWatch Events or Amazon EventBridge to run periodic tasks.
• Chatbots and Microservices → Run lightweight, event-driven backend logic at scale using services like Amazon SNS or Amazon SQS.

AWS Lambda vs Traditional Servers

• Traditional Servers → Require provisioning, monitoring, and scaling for peak load using services like Amazon EC2.
• AWS Lambda → Completely managed, scales automatically, and charges only for execution time.

Limitations and Considerations

• Cold Starts → Functions that haven’t been invoked recently may experience a short delay (a “cold start”) when AWS spins up a new container.
• Timeouts → Each invocation has a maximum execution time (currently 15 minutes). Long-running tasks may need a different service such as Amazon ECS or Amazon EC2.
• Memory and CPU Limits → Memory allocation tops out at a few GB (currently 10 GB), with CPU proportional to memory. Heavy compute workloads can hit these caps.
• Ephemeral Storage → The default /tmp storage is limited (512 MB by default, expandable to 10 GB), so large temporary files require external storage like Amazon S3 or Amazon EFS.
• Vendor Lock-in → Deep integration with AWS services can make migrating to another cloud provider more difficult.
• Networking Constraints → Accessing resources inside a VPC adds setup complexity and may increase cold-start latency.
• Debugging Complexity → Local debugging and tracing can be harder compared to a traditional server environment.

Conclusion

AWS Lambda enables developers to build event-driven applications without managing servers.
Whether you need a quick backend for a web app, a real-time file processor, or a data pipeline, Lambda delivers on-demand compute that scales automatically.