Right-Sizing with AWS Lambda Power Tuning
Learn to find the optimal memory setting that minimizes cost, latency, or both using the AWS Lambda Power Tuning tool.
Right-Sizing with AWS Lambda Power Tuning is a free Serverless AWS Lambda Development lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Serverless AWS Lambda Development learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Memory is the Only Dial
Lambda gives you one performance dial: memory. CPU and network scale with it, so memory tuning controls both speed and cost.
The Non-Obvious Tradeoff
More memory costs more per millisecond but often finishes faster. Sometimes a higher memory setting is cheaper overall.
Two Optimization Goals
You usually optimize for one of:
- Lowest cost (minimize GB-seconds).
- Lowest latency (fastest response).
The best memory for each can differ.
Enter Power Tuning
AWS Lambda Power Tuning is an open-source Step Functions tool that runs your function at several memory sizes and charts cost vs speed.
How It Works
You give it the function ARN and a list of memory values. It invokes each many times, measures duration and cost, and recommends the best setting.
{
"lambdaARN": "arn:aws:lambda:us-east-1:123:function:orders",
"powerValues": [128, 256, 512, 1024, 1536],
"num": 50,
"strategy": "balanced"
}Reading the Results
The output gives the optimal power value and shows the cost/latency curve. A "balanced" strategy weighs both equally.
{
"power": 512,
"cost": 0.0000071,
"duration": 95
}The Sweet Spot
For CPU-bound code, raising memory until duration stops improving usually finds the sweet spot. Beyond it you pay more for no speed gain.
I/O-Bound Functions
If the function mostly waits on the network or a database, extra memory barely helps. Keep memory low to save cost.
Set the Chosen Value
Apply the recommended memory to the function configuration.
aws lambda update-function-configuration \
--function-name orders \
--memory-size 512Retune After Changes
Tuning reflects current code and dependencies. Re-run power tuning after major code changes or new library versions.
Combine with ARM
Switching to the arm64 (Graviton) architecture often improves price-performance further. Tune memory after migrating architectures.
Quick Check
Test your tuning knowledge.
Recap
You learned to right-size memory with Lambda Power Tuning, choosing for cost or latency, recognizing I/O vs CPU-bound behavior, and combining tuning with arm64.
Frequently asked questions
Is the “Right-Sizing with AWS Lambda Power Tuning” lesson free?
Yes — the full text of “Right-Sizing with AWS Lambda Power Tuning” is free to read here on the web, and the Serverless AWS Lambda Development course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Serverless AWS Lambda Development course, upgrade to CoddyKit PRO.
What will I learn in “Right-Sizing with AWS Lambda Power Tuning”?
Learn to find the optimal memory setting that minimizes cost, latency, or both using the AWS Lambda Power Tuning tool. You practise Serverless AWS Lambda Development with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Serverless AWS Lambda Development?
No prior experience is required. Serverless AWS Lambda Development on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Right-Sizing with AWS Lambda Power Tuning” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Serverless AWS Lambda Development lesson?
Yes. Every Serverless AWS Lambda Development lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Cold Starts and Provisioned Concurrency
- Memory Allocation and Performance Tuning
- Cost Management for Lambda
- Right-Sizing with AWS Lambda Power Tuning