Tired of manually handling batch processing in AWS Lambda? Wanna scale like a boss without worrying about timeouts? Let’s talk about auto-calling Lambda functions and how they can supercharge your workflows! 💪
The Problem
When dealing with large datasets in Lambda, processing everything in one go can lead to timeouts and memory issues. We need a better way—one that leverages asynchronous execution and auto-invocation to scale effortlessly.
Why This Matters
Imagine you have a list of resources in your database, and each needs AI-driven analysis, file complex generation or a high math effort. Running all of them in a single function execution? Not ideal. Instead, we’ll trigger the function recursively, allowing it to handle each resource independently, in parallel. No more memory bloat, no more slow executions. Just pure efficiency. 🫡
Lambda Sample:
#Lambda name autocalling-lambda-sample
import json
import boto3
import random
def get_waifu_list():
return ["Asuna", "Rem", "Hinata", "Zero Two", "Nezuko", "Mikasa", "Kurisu"]
def custom_ai_analysis(name):
personality_traits = {
"Asuna": "Brave, Loyal, Strong-willed",
"Rem": "Devoted, Kind, Fierce when needed",
"Hinata": "Shy, Gentle, Loving",
"Zero Two": "Mysterious, Playful, Protective",
"Nezuko": "Cute, Silent, Deadly when angered",
"Mikasa": "Stoic, Determined, Fierce",
"Kurisu": "Smart, Witty, Tsundere"
}
return {"name": name, "personality": personality_traits.get(name, "Unknown")}
def lambda_handler(event, context):
lambda_client = boto3.client('lambda')
function_name = context.function_name
waifu_list = get_waifu_list()
if 'waifu_index' in event:
waifu_name = waifu_list[event['waifu_index']]
analysis_result = custom_ai_analysis(waifu_name)
print(f"Processed: {json.dumps(analysis_result)}")
return {'statusCode': 200, 'body': json.dumps(analysis_result)}
else:
for i in range(len(waifu_list)):
lambda_client.invoke(
FunctionName=function_name,
InvocationType='Event', # Asynchronous invocation
Payload=json.dumps({'waifu_index': i})
)
print(f"Triggered async invocation for waifu {waifu_list[i]}")
return {'statusCode': 200, 'body': json.dumps('Waifu analysis triggered!')}Don forget:
Adding to your lambda the rights to auto call him with a custom policy like this:
Debug:
Enable your CloudWatch logs to see how your lambda was called n times and enjoy !
Why This Is Awesome 😎
✨ Scales Automatically – Each invocation only processes a single resource, preventing timeouts.
✨ Parallel Execution – Multiple Lambda instances run at the same time.
✨ Cost-Efficient – Pay only for what you use, avoiding unnecessary execution time.
✨ Works on Any Dataset – Whether you have 10 or 10 million resources, this approach just works.
And That's It!
💬 Got questions or improvements? Drop a comment below!
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