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Performance Best Practices Using Java and AWS Lambda: Conclusion and Referencesby@escholar
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Performance Best Practices Using Java and AWS Lambda: Conclusion and References

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This paper is [available on arxiv.org/pdf/2310.16510.pdf) under CC BY-SA 4.0 DEED license. Authors: Juan Mera Men´endez, Martin Bartlett, and D. Jackson. The goal is to show that Java can be used competitively with AWS Lambda without the need to resort to runtimes like Node.js.
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This paper is available on arxiv under CC BY-SA 4.0 DEED license.

Authors:

(1) Juan Mera Men´endez;

(2) Martin Bartlett.

Abstract and Introduction

Initial Application

Performance Tests

Best Practices and Techniques

Combinations

Discussion

Related Work

Conclusion and References

VIII. CONCLUSION

Performance is an aspect that should always be taken into account when creating Lambda functions, especially if you plan to combine them with Java. Once the performance improvements offered by these approaches for using Java with AWS Lambda have been quantified. It is evident that Java can be used competitively with AWS Lambda without the need to resort to runtimes like Node.js or Python (which usually report better performance).


Having tested various combinations of proposed strategies and demonstrated that the performance is similar to what can be achieved with the use of GraalVM, we recommend avoiding its usage. We consider it essential to profile the Java functions to select the optimal memory configuration and using AWS SDK v2. From there, optionally, the next step is to the rest of the techniques to achieve one of the proposed combinations. Additionally, following the general best practices such as initializing connections outside the handler or reduce the bundle size, among others, also contribute to optimizing Java functions.


The optimization strategies we propose are not the only ones available, there are many other techniques that can similarly yield excellent results.


It is important to highlight that the process of optimizing a function is linear in terms of difficulty. In other words, it’s relatively easy to obtain a significant improvement, but if you want to squeeze out the maximum performance, the process requires trial and error and greater effort. It’s also important to highlight that the percentage of improvement offered by each approach depends on the specific use case in which they are applied. This percentage can vary, either increasing or decreasing.

REFERENCES

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