AWS Lambda’s Cold start latency has long been a challenge in serverless computing, especially for Lambda functions. When invoked for the first time or after a period of inactivity, these functions must initialize their code, load dependencies, and configure their environment — a process that often results in significant delays, impacting user experience.
AWS Lambda SnapStart addresses this challenge by capturing a pre-initialized snapshot of the function’s memory and disk state when a new version is published, so that subsequent invocations can bypass the full initialization process. This innovative approach reduces cold start latency by up to 10x, achieving sub-second startup times with minimal developer intervention and paving the way for building highly scalable, low-latency serverless applications.
Problem Statement
Cold start latency occurs when a Lambda function’s execution environment is initialized for the first time, particularly when scaling or during idle periods, resulting in a delay before the function can start processing requests. While cold starts generally representing less than 1% of Lambda invocations, the delays can still be significant, especially in real-time applications like APIs or event-driven architectures, where responsiveness is crucial.
Even a slight delay—sometimes up to several seconds—can disrupt user experience or workflow efficiency.
To illustrate this challenge, consider the following , which simulates a 20-second initialization delay. This delay mimics time-consuming tasks like loading dependencies or configuring external resources, followed by 30 seconds of processing time, showing how cold start latency compounds the total execution time.
Code Link:
CloudWatch logs
- 08:09:11 → Invocation started as a cold start.
- 08:09:21 → Init phase times out after 10 seconds. Init phase retried, considering timeout as function timeout.
- 08:09:42 → Init phase completed; Invoke phase starts.
- 08:10:12 → Business logic executed; total execution time logged.
- 08:10:12 → Billed execution time: 50 seconds (including 20 seconds retry and init phase time and 30 seconds for business logic).
For subsequent invocations:
If the execution environment is destroyed and it’s a cold start, the process repeats, potentially leading to another timeout in the Init phase. In a warm start, only the 30 seconds of business logic is executed, and you are billed for 30 seconds.
For non-SnapStart or non-provisioned concurrency Lambda:
Warm starts aren’t guaranteed, the container is typically kept warm for 10-15 minutes.
Solution Procedure: Activating AWS SnapStart for Python
Architecture Design
AWS SnapStart mitigates this challenge by pre-initializing the function when a new version is published. It captures a snapshot of the initialized environment’s memory and disk state, encrypts it, and stores it for rapid retrieval. When Lambda scales and a new execution environment is needed, the function can restore this cached snapshot, resuming execution from the pre-initialized state. This reduces initialization time and improves overall performance.
This process leverages Firecracker microVM snapshotting for enhanced efficiency. Lambda functions run in secure, isolated environments, and the Init phase is where the runtime is bootstrapped.
To activate SnapStart for a function (console)
Open the Lambda console and select your function.
Navigate to Configuration > General Configuration and click Edit.
In the Edit basic settings section, choose Published versions under the SnapStart option.
Save your changes and publish a new function version.
CloudWatch logs
When publishing the version, Lambda automatically creates a snapshot of the function’s execution environment for optimized performance.
- 08:25:04 → Init phase started
- 08:25:26 → Init phase completed; took 21 seconds to create a snapshot of the Lambda environment. When you invoke a SnapStart-enabled Lambda, it boosts performance by resuming environments from a pre-created snapshot instead of starting from scratch. This snapshot, made during version publication, includes the runtime, dependencies, and initialization state. As shown in the Restore Report, the process starts with RESTORE_START, and in this case, restoration took just 594.60ms, highlighting how SnapStart reduces cold start latency for smoother performance.
- 08:29:12 → Restore phase started.
- 08:29:13 → Restore phase completed.
- 08:29:13 → Invocation started as a cold start.
- 08:29:13 → The initialization was detected as a cold start, with a time of 247 seconds, calculated using the global start time set during version publication. This reflects the setup and initialization time from the initial deployment before executing the business logic.
- 08:29:43 → Business logic executed; processing completed.
- 08:29:43 → Billed execution time: 31 seconds (including restore duration and business logic execution).
For the subsequent invocation:
If the execution environment is destroyed after some time, the restore phase will occur again, and you’ll be charged for 30 seconds of business logic plus the restore duration of 0.5 seconds, total time will be 31 seconds.
If it’s a warm start and the container is not destroyed, only 30 seconds of business logic will be executed, and you’ll be billed for 30 seconds.
Results and Business Outcomes
With the implementation of SnapStart, we have successfully reduced cold start times from 40 seconds to just 594 milliseconds.
This means that, with SnapStart enabled, the overall cold invocation time is now a combination of the restore duration and the execution duration, leading to a significant reduction in startup latency—from several seconds to sub-second performance.
Cost Savings: SnapStart reduces the time billed during cold starts, lowering costs, especially for applications with irregular usage.
Better User Experience: Reducing cold start times from 40 seconds to 594 milliseconds improves responsiveness, making apps faster and more satisfying for users.
Improved Reliability: Consistent sub-second performance ensures dependable service, boosting customer trust and satisfaction
Conclusion
AWS Lambda’s cold start latency can slow down applications, especially those requiring quick responses like APIs or event-driven systems. AWS SnapStart tackles this issue by using pre-initialized snapshots, allowing functions to skip the setup process and start almost instantly. This reduces cold start times by up to 10x, improving performance and scalability. While SnapStart has some limitations, it’s a powerful tool for building faster, more efficient, and reliable serverless applications.
