Why Your Lambda Function Is Slow (And How to Fix It)

TL;DR: Your AWS Lambda isn’t slow because it hates you. It’s slow because of cold starts, bloated packages, bad VPC configs, and more. Here’s how to fix all that—fast.
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The Problem: “My Lambda is so slow!”

If you've ever yelled this into the void (or worse, into Slack), you’re not alone. AWS Lambda is an amazing tool for scaling backend workloads—until it randomly takes 2 seconds to do what should take 200 milliseconds.

You might think, “Is it AWS? Is it me?” Spoiler: it's mostly you. But also a bit of AWS. Let’s break it down.

Cold Starts: The #1 Culprit

Cold starts are what happen when AWS has to spin up a fresh container to run your function. These typically happen when:

1. A function hasn’t been invoked in a while
2. You're deploying a new version
3. Your concurrency suddenly spikes

Why It's Slow?

Each cold start involves:

• Booting up a container
• Initializing the runtime (e.g., Node.js, Python, etc.)
• Running your function’s initialization code

This can add 100ms–2s to your first call.

Fix It This Way

Use provisioned concurrency: This keeps Lambda “warm” all the time.

Keep your dependencies minimal: The larger your bundle, the slower your cold start.

Choose faster runtimes: Node.js and Go have quicker cold starts than Java or .NET.

Bloated Dependencies = Bigger Latency

If your Lambda package is huge (like 100MB+), you’re basically asking AWS to uncompress and boot a whale.

Why It's Slow? More dependencies mean:

• Slower cold starts
• Higher memory usage
• Slower file system access (especially if using /tmp)

Fix It by Bundling only what's needed. Use tools like esbuild or webpack.

Also, Externalize AWS SDK if you're on Node.js 18+. It's now available in the Lambda runtime and. Remove devDependencies from deployment packages.

VPC Configuration May Be a Black Hole

If your Lambda needs to access resources in a VPC (like RDS or ElastiCache), it can suffer a ~400ms delay just to attach an ENI (Elastic Network Interface).

Why It's Slow

Creating ENIs adds latency

It slows down every cold start

Solution

• Don’t run Lambdas inside a VPC unless you absolutely need to
• Use Amazon RDS Proxy to speed up DB connections
• Place resources outside the VPC when possible (e.g., S3, DynamoDB)

You're Not Reusing Connections

Opening a new DB or API connection on every invocation is a performance killer.

Reason it's not fast:

1. Connection handshake overhead
2. DB resource exhaustion
3. Timeouts on concurrent executions

Fix It

Reuse connections by creating them outside the handler function

// Bad
exports.handler = async (event) => {
  const db = new MySQLConnection();
  await db.connect();
  ...
}

// Good
const db = new MySQLConnection();
db.connect();

exports.handler = async (event) => {
  ...
}

Logging Too Much, or Synchronously

Are you dumping huge payloads into console.log? Worse: doing it synchronously?

Why It's Slow

• Logging slows down execution
• Especially bad if logging big objects or arrays
• JSON.stringify is often slow, too

So, minimize logs in performance-critical paths and use async loggers or external log aggregators. Also, avoid stringifying large payloads unless needed

You’re Not Testing in the Real Environment

Local runs are not a good representation of how your function performs in AWS.

1. Use AWS CloudWatch to view invocation durations
2. Enable X-Ray for tracing bottlenecks
3. Benchmark using artillery, autocannon, or serverless-artillery

Important Tips

Use layers wisely: Layers help reduce size, but don’t magically improve cold starts. Test their impact.

Keep function warm: Use a ping Lambda or a scheduler to keep your function alive.

Use async initialization: Lazy-load large modules or config if they’re not always needed.

Final Thoughts

Lambda functions can be lightning-fast—but only if you treat them like race cars, not cargo ships. Strip them down, warm them up, and give them the right track to run on.

Got questions or want a walkthrough on any part of this? Drop a comment or hit me up!