Supercharge AWS Lambda Functions With These 5 Performance Strategies
I talk about 5 valuable techniques you can implement right now to boost the performance and efficiency of your Lambda functions.
By default, Lambda functions are created with much performance and improvements left to be desired.
Using the default configuration leaves much space for improvement if your app requires scaling or more power (higher memory, faster cold starts, etc).
Let’s explore 5 strategies that will offer a measurable boost and help the performance and cost-effectiveness of your applications.
I’ll start off the list with Lambda Power Tuning.
Lambda Power Tuning
The Lambda Power Tuning is a tool (essentially an AWS step function) that runs your Lambda function with different configurations to detect how to optimize it best.
The tool aims to find the most optimal balance between cost and execution time.
You can choose from 3 different optimization modes:
Cost
Execution time
Balance between cost and execution time
The tool is straightforward to use and offers a simple and detailed guide on how to use it with your functions.
Ultimately, your functions will result from either a better performance, a better cost efficiency, or a solid balance between both.
Increasing Memory and CPU Allocation
Increasing the allocated memory of a Lambda function will improve the performance of the function. This can greatly reduce cold start times if you are affected by them.
However, increasing memory will increase the CPU power available to the function, leading to higher costs.
Therefore, finding the right balance between memory and cost is always important.
To increase the memory of your function, in your Lambda function, under the configuration tab, in General Configuration, click edit and specify how much memory you need.
You can choose anywhere between 128MB to 10GB of memory.
Provisioned Concurrency
Provisioned concurrency is a strategy used to keep your functions initialized and ready to execute requests.
This will reduce cold starts, improve performance, and provide lower latency for requests made to the function.
Provisioned concurrency is a great fit for applications that are latency-sensitive such as real-time chat or video conference applications.
To enable provisioned concurrency, you can do so in the configurations tab, under concurrency, and in the Provisioned concurrency Configurations section. There click on add configuration.
Use A Low Cold Start Runtime
When designing the architecture of your serverless solution, one important element to consider is whether or not cold start times are significant for your application.
If they are, choosing a runtime with a low cold start is critical.
Runtimes like Python and Node JS are very fast and offer insignificant cold start times.
Other runtimes like C# and Java suffer more from cold starts in Lambda.
Nevertheless, there are some optimizations available to use in these cases.
For example, in Java you can enable SnapStart to make your serverless code have significantly lower cold start times.
SnapStart caches the function for very fast executions after the function has initialized.
You can enable this in the concurrency configurations as we saw earlier.
For a list of the fastest runtimes supported by Lambda, I recommend you check out this article for a detailed breakdown.
Optimize Package Sizes
Smaller deployment packages will greatly improve your function startup time.
Smaller packages also make your Lambda functions more efficient by running for less time, costing you less.
You can also use Lambda Layers to share common libraries across multiple functions.
Lambda layers help reduce deployment sizes, make your code more reusable, and simplify dependency management.
For an in-depth article on Lambda Layers, read this guide.
Conclusion
By implementing these 5 strategies, you can significantly boost the performance and efficiency of your Lambda functions, leading to cost savings and improved scalability
While improving function concurrency and boosting memory is important for performance, finding the right balance between cost and performance is critical and should be considered carefully.
👋 My name is Uriel Bitton and I’m committed to helping you master Serverless, Cloud Computing, and AWS.
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Thanks for reading and see you in the next one!