# Best Practices **Performance Optimization** **Limit the region: **Restrict the lambda to the smallest area necessary to reduce compute costand time **Efficient algorithms: **Use vectorized operations where possible for better performance **Memory management: **Be mindful of memory usage when processing large datasets **Development Workflow** **Test on a sample: **Validate your code on a small subset before running it on the full dataset **Incremental development: **Start with simple logic and gradually add complexity **Error handling: **Include proper error handling for robust execution **Resource Management** **Reuse templates: **Start with VoxelSpace's built-in lambdas for common tasks; modify themrather than writing from scratch **Queue awareness: **Plan your processing and lambda jobs to avoid long queues, especially onthe free tier where concurrency is limited **Monitor usage: **Track your compute usage to stay within plan limits **Debugging and Validation** **Use logs: **Include log statements in your lambda to help diagnose issues and verifyintermediate results **Validate inputs: **Check that your data has the expected properties before processing **Test edge cases: **Consider what happens with empty regions, missing properties, or extremevalues