Lambda Function Performance¶

Lambda Function Configuration¶

• RAM
  • From 128 MB to 10GB in 1MB increments
  • The more RAM you add, the more vCPU credits you get
  • At 1,792 MB, a function has the equivalent of one full vCPU
  • After 1,792 MB, you get more than one CPU, and need to use multi-threading in your code to benefit from it.
• If your application is CPU-bound (computation heavy), increase RAM
• Timeout: default 3 seconds, maximum 900 seconds (15 minutes)

Lambda Execution Context¶

• The execution context is a temporary runtime environment that initializes any external dependencies of your lambda code
• Great for database connections, HTTP clients, SDK clients...
• The execution context is maintained for some time in anticipation of another Lambda function invocation
• The next function invocation can "re-use" the context to execution time and save time in initializing connections objects.
• The execution context includes the /tmp directory.

Initialize outside the handler¶

BAD¶

import os

def get_user_handler(event, context):
    DB_URL = os.get_env("DB_URL")
    db_client = db.connect(DB_URL)
    user = db_client.get(user_id = event["user_id"])

    return user

The DB connection is established at every function invocation.

GOOD¶

import os

DB_URL = os.get_env("DB_URL")
db_client = db.connect(DB_URL)

def get_user_handler(event, context):
    user = db_client.get(user_id = event["user_id"])

    return user

The DB connection is established once and re-used across invocations.

Lambda Functions /tmp space¶

• If your Lambda function needs to download a big file to work
• If your Lambda function needs disk space to perform operations
• You can use the /tmp directory
• Max size is 512MB
• The directory content remains when the execution context is frozen, providing transient cache that can be used for multiple invocations (helpful to checkpoint your work)
• For permanent persistence of object (non temporary), use S3