⚡ Performance Optimization Guide

Techniques to improve the speed, efficiency, and cost-effectiveness of your BCE Lambda functions.

🚀 Jump to Optimization Strategies

Understanding Performance in Serverless

Serverless functions execute on-demand, offering elastic scalability but requiring careful optimization. Key performance factors include execution time, memory allocation, and cold starts.

⏱️

Execution Time

Directly impacts cost and user experience.

💾

Memory Allocation

Higher memory gives more CPU, but increases cost.

❄️

Cold Starts

Cold starts delay initial executions of functions.

Top Optimization Strategies

1. Optimize Resource Configuration

🚀

Find the optimal combination of memory, CPU, and timeout settings for your function. BCE Lambda allows granular control over these parameters.

{
  "MemorySize": 512,
  "Timeout": 15,
  "Environment": {
    "Variables": {
      "PERF_OPTIMIZED": "true"
    }
  }
}
                        

Recommended: Start with 128MB for simple functions and increase by 64MB increments while monitoring performance.

2. Use Provisioned Concurrency

🔥

Prevent cold starts by keeping a specified number of function instances always running in the background.

Cold Start Rate: 0.02%
Provisioned Instances: 15
$ bcl update-function my-function --provisioned-concurrency 20
                        

Note: Provisioned concurrency costs increase with the number of instances.

3. Asynchronous Processing

Use event-driven architecture to process tasks in parallel, reducing overall execution time for complex workloads.

300%

Processing Speed

-65%

Execution Time

async def process_events(events):
    results = await asyncio.gather(
        *[handle_event(event) for event in events]
    )
    return results
                        

Monitoring & Diagnostics

Real-Time Metrics

Shows execution time trends over the last 15 minutes
🔗 View Metrics in BCE Console

Performance Insights

98.2%
Success Rate
450ms
Avg Latency
3.2%
Error Rate

Performance Best Practices

Minify & Bundle

Reduce deployment package size by minifying code and using bundlers like Webpack or esBuild.

npm install --save-dev webpack esbuild-bundle

Use Caching Layers

Implement caching strategies using BCE Redis or in-memory caches for frequently accessed data.

import bcl.cache

Optimize Dependencies

Regularly audit dependencies using the BCE Dependency Scanner to remove unused or redundant packages.

bcl dependencies scan

Use Layers for Shared Code

Reuse common utility code across functions using BCE Lambda Layers to reduce duplication.

bcl layer create utils

🔄 Related Documentation