Ways to Improve Lambda Performance

✒️Reuse the Execution Context

what is the execution context? Lambda invokes your function in an execution environment (an isolated runtime environment). The execution context is a temporary runtime environment that initializes any external dependencies of your Lambda code.

🏋️‍♂️Explanation Exercise:

Create a testLambda with a 3 sec timeout limit:

Bad Practice:

import json
import os
import time

def connect_to_db():
    time.sleep(3)

def lambda_handler(event, context):
    connect_to_db()
    return os.getenv('ENVIRONMENT_NAME')

Test with sleep 3 sec, no timeout as it is within the 3 sec limit we set. But everytime we call this lambda, it will always take 3 sec because it is trying to connect to the database everytime we run. This way of writing is not efficient.

Also, let's say if the connection to database took more than 3 sec, example 5 sec:

import json
import os
import time

def connect_to_db():
    time.sleep(5)

def lambda_handler(event, context):
    connect_to_db()
    return os.getenv('ENVIRONMENT_NAME')

We will faced this timeout issue:

Good Practice for Better Performance:

So a Good Practice is to put the connection code outside of the lambda handler function:

import json
import os
import time

def connect_to_db():
    time.sleep(3)

# shift this out of handler
connect_to_db()

def lambda_handler(event, context):
    return os.getenv('ENVIRONMENT_NAME')

So even though the initial run will likely take 3 sec but subsequent run only took 1.64 ms, which is much more efficient! This is because it is re-using the execution context of the previous invocation.