In recent years serverless architectural patterns have gained a lot of traction. AWS offers several serverless services and AWS lambda is one of the popular ones and an example of a Function as a Service(FaaS) serverless architecture.
What is AWS Lambda?
AWS Lambda is a serverless compute service to let you execute your code to do a specialized task without having to provision or manage servers. You can upload your code to AWS and define the runtime configuration, CPU and memory requirements, and an event on which your function should be executed. AWS is responsible for booting up servers and required runtime environments to execute the code you provided as soon as the triggering event takes place.
Lambda function workflow diagram:
Cost consideration and breakdown
- The Non-expiry free tier includes 1M invocations and 400,000 GB-seconds of compute per month.
- Charges are based on 1 ms increments, ensuring you only pay for what you use
- You never pay for idle resources, making it ideal for sporadic workloads.
- AWS Pricing Calculator can help estimate costs based on your workload."*
Pros of AWS Lambda:
AWS Lambda offers several distinct advantages over maintaining your own servers in the cloud:
Pay Per Use: With AWS Lambda, you only pay for the compute time your functions use and any network traffic generated. This billing model is especially cost-effective for workloads that vary significantly based on time of day or demand.
Fully Managed Infrastructure: AWS handles all aspects of the underlying infrastructure, such as operating system updates and network management. This eliminates the need for operational tasks, saving time and reducing complexity.
Automatic Scaling: Lambda automatically scales your functions to handle varying loads, creating instances as requests come in. There’s no need to predefine scale levels or manage scaling settings, your functions simply scale up or down based on demand, and you only pay for runtime.
Seamless Integration with AWS Services: Lambda integrates tightly with other AWS products, such as DynamoDB, S3, and API Gateway, enabling you to build complete applications with minimal effort. This integration streamlines workflows and simplifies the development of serverless applications.
Cons of AWS Lambda
While AWS Lambda has many advantages, there are also some limitations to consider:
Cold Start Latency: Functions not used in the last 15 minutes may experience a cold start introducing a 5-10 second delay, making Lambda unsuitable for latency-critical applications.
Execution Time Limits: Lambda functions have a maximum runtime of 15 minutes, which cannot be extended. This limitation makes it unsuitable for long-running tasks like video rendering or large-scale data processing.
Resource Constraints: Functions are limited to 10GB of memory, 6 vCPUs, and 10GB of ephemeral storage. These constraints can hinder tasks requiring high computational power or large datasets.
Stateless Nature: Lambda functions are stateless by design, requiring external services like DynamoDB or S3 for state management. This can add complexity for workflows that require persistent in-memory data.
Cost at Scale: Although cost-efficient for low-to-moderate workloads, Lambda's pay-per-use model can become expensive for high-frequency or resource-intensive workloads, where EC2 or ECS may be more economical.
Conclusion:
AWS Lambda is a powerful serverless tool when used in the right scenarios. By understanding its strengths and limitations, you can harness it to build scalable, efficient, and cost-effective applications. Have you used Lambda in your recent projects? It would be nice to hear your experiences!
Some useful resources:
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