AWS has announced that Lambda SnapStart is now available for functions packaged as container images. Previously, SnapStart was limited to managed runtimes for Python, .NET, and Java. This expansion addresses a significant trade-off faced by developers using Lambda.
Functions packaged as container images can be up to 10 GB in size, offering a substantial increase over the 250 MB limit for zip archives. However, until this update, choosing container images meant foregoing SnapStart, leading to startup times of several seconds while the Lambda environment initialized. SnapStart works by taking a snapshot of the initialized execution environment at deployment and resuming from it upon invocation, resulting in sub-second startup times.
This change is particularly relevant for applications with heavy dependencies, such as those using libraries like pandas and numpy. Developers previously had to choose between the larger size capacity of container images and the faster startup times provided by SnapStart. The update removes this constraint, allowing developers to use container images for large dependencies without incurring a cold start penalty.
The challenge of balancing dependency size and startup performance was evident in developer discussions, where teams resorted to stripping whitespace and docstrings from code to stay within the 250 MB zip archive limit. Alternative solutions, such as mounting EFS access points, were also considered to manage large libraries while retaining SnapStart. The new support for SnapStart in container images simplifies this decision for developers.
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AWS has extended Lambda SnapStart functionality to functions packaged as container images, which previously only supported managed runtimes. This change eliminates the startup latency penalty for Lambda functions that use container images to accommodate large dependencies, allowing them to achieve sub-second cold start times.