The Serverless Standard
February 09, 2019
The Serverless Standard
Score 10 out of 10
Vetted Review
Verified User
Overall Satisfaction with AWS Lambda
The engineering and data science teams at my organization use AWS Lambda to rapidly deliver features that are easy to maintain. We use Lambda with the Serverless framework, API Gateway, and DynamoDB to build managed micro-services that are easy to scale. We use Lambda with AWS Step Functions and S3 to build background jobs.
- AWS Lambda is fully-managed. It is easy to build and manage functions and related resources with the Serverless framework.
- AWS Lambda integrates well with other AWS products. It is easy to use S3, SNS or DynamoDB events to invoke functions.
- For some use-cases, AWS Lambda is very inexpensive. Sub-second metering is great. Lambda is great for infrequently-used or bursty services.
- Managing development, staging, and production environments with Lambda is an open question. Some organizations use separate AWS accounts for different environments, but that is not feasible for teams that use ephemeral, per-feature or per-team development environments.
- AWS Lambda integrates well with other AWS products, and it is natural to build distributed systems from them. It can be difficult to test features that use Lambda functions end-to-end. LocalStack and moto can help.
- Lambda functions have very limited access to disk space.
- Container cold-starts can be problematic and difficult to foresee.
- AWS Lambda has allowed our data science team to rapidly deliver RESTful APIs for machine learning features without engineering support
- AWS Lambda and API Gateway allow our developers to rapidly develop background jobs and services without configuring and maintaining infrastructure, application servers, reverse proxies, etc.
- Lambda integrates well with other AWS products; we don't have to implement as much "glue" code.