I do have numerous functions with similar functionality in my codebase, these will usually cold-start in sub seconds time and will take below than 100ms in warmed up state. My lambda is very simple it only save a object into a data base. Try to use some other technology but Java for that. So in the case you describe above, most definitely yes. Meaning that basically all your code that reacts to HTTP calls should be in a technology like JavaScript/TypeScript/NodsJS or let's say Python. In my experience I would recommend to use a more lightweight runtime environment for functions that directly interface with uses. In my experience the cold starts usually hit you the hardest when you start getting invested in Lambda, because then you typically have small non-continuous workloads there such that your functions get evicted from memory on a regular basis, resulting in a situation where your users will also experience cold starts on a regular basis. This together with the fact that a JVM typically takes a bit more time to start compared to more lightweight environments, one would say Java is not the best option if you need or want to avoid cold starts of a few seconds. There are certain popular parts of the Spring framework which just naturally take a bit of time to launch: database connections, messaging on a MQ etc. The downsides of Spring Cloud Functions and the Spring framework are, that its inherent mechanism of dependency injection can quickly take quite some time during startup time. With this setup, there is no need to increase the memory and the timeout settings too much.This is a question which is very difficult to answer in the short. The first request is still significantly longer than the rest, but this is less pronounced. The green line shows a lot less variability in response times. The green line is with deferred initialization. The red line is the original configuration, compiling everything as soon as possible. I ran some tests on the openapi-backend project and the results clearly show the contrast in behaviors. This brings down the cold start times to an acceptable level. The best practice here is to do as little as possible and distribute the work to subsequent requests, also called lazy loading or deferred execution. Also, cold starts are visible to users, as it happens as part of a request and not in a separate process. Serverless, a.k.a hyper-ephemeral computing, is built on short-lived instances and that means initialization happens fairly often as the execution units are small and the need for new capacity is instantaneous. By compiling all schemas during initialization the openapi-backend project followed this best practice. When the instance is started, it is ready to serve requests at full throttle. The best practice is to do as much initialization as possible, such as populate the caches and even sending a dummy request (called a warmup request) to execute some code paths. If you use load-balanced EC2 instances that start and stop rarely, you want to do everything as soon as possible. But that also increases costs for fast requests. ![]() They can be made faster by allocating more memory that (due to the Lambda resource model) increases the CPU power available to the function. First, they might be just too long and that leads to bad UX. While most requests will be fast as they go to warm instances, some will trigger cold starts. The result is that there will be occasional slow responses when you deploy your code as Lambda functions. It does not help that it has to be done only once. The former is especially pronounced in Java as the JVM needs to do quite a bit of work to load the classes. ![]() Worse still, the code is “cold”, which means that the execution environment hasn’t done loading and optimizing the function’s code and all the variables are uninitialized. This is the basis of Lambda scalability: start an instance when needed, then stop it when it’s idle for too long.Īs a result, the first request needs to wait until the startup process is finished. In the case of AWS Lambda, it happens when all the current instances are busy. When a backend instance is initialized, the execution environment deploys the code to a new machine and starts routing requests to it. Remove duplication of validation, routing, and parameter handling with an OpenAPI-based backend framework The problem: cold starts
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