AWS LAMBDA COLD START

AWS

Introduction (What is Cold Start)

When a serverless function is running, it stays in an active state only as long as it is in the running state.
Containers also remain in an active state only during this duration of time.
After some time these containers become inactive if no activity is there.
Functions will go in an inactive state if no execution is there.
Inactivation of our functions or containers is done by the cloud provider that we are using say for example – AWS or GCP.
When we invoke an inactive serverless function that start is called a Cold Start.
Delay occurs because the function or the container is in an inactive state, and it takes some time for the cloud provider to restore their state.
Spinning up a new container after it has been in an inactive state causes the delay.
This is how cold start affects the execution time of a serverless function.
In short, we can say that cold start results in a longer execution time of the serverless functions resulting in the overall delay of the application.

In the above diagram, the first two steps are the cold start duration.
Firstly, the download of our code happens then a new environment is set up.
Although we are not charged for this time duration it causes a delay in the execution of our function.
Once the execution is completed, the execution environment is frozen for a certain period of time.
If another request arrives for the same function, the service may reuse the environment that is frozen to avoid latency and for better performance.
This use of the previous environment is called a warm start as it doesn’t download your code and set up the environment again.
According to research cold start invokes only under 1% of the invocations.
The duration of cold start varies from 100ms to up to 1 sec.

Whenever the function is updated or changed there will always be a cold start as it reloads the code and creates a new environment.
When the function is not invoked frequently.
If the programming language in which lambda is used has a higher latency or more dependencies.

Provisioned Concurrency can be used if we need a predictable function start time.
It means to increase the amount of concurrency during high demand and decrease it at the time of low demand.
It can be done through AWS CLI and no need to make any changes to your code.
Deciding the right memory size can also be helpful in reducing the cold start.
Monitoring the performance of the lambda and setting up the configuration according to that only will also help.
Caching can be used if the invocation is not very frequent or the data is not getting updated very frequently.
Low Latency languages can be used to avoid delay while the execution.

Cold Start is something that will take place.
We need to understand our needs and define our configuration according to that.
Provisioned Concurrency is one of the best ways to optimize the cold start.
Better memory management is also very helpful.

https://aws.amazon.com/blogs/compute/operating-lambda-performance-optimization-part-1/

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