​Kestra ​Performance – ​Benchmarks and ​Tuning

Learn how to measure and optimize Kestra’s performance. The Benchmark guide shows real-world execution metrics for both the Open Source and Enterprise editions, while the Performance Tuning guide explains configuration options for the Worker, JDBC backend, and Kafka backend to balance throughput, latency, and resource usage.

Measure and tune Kestra performance

Kestra Benchmarks – Orchestration Throughput and Latency

Kestra is an orchestration platform: you define a flow, and Kestra orchestrates it. Flows can range from lightweight tasks running in milliseconds to complex scripts in containers that run for tens of minutes.

Performance Tuning Kestra – Tune Workers, JDBC, Kafka

Not all workloads are the same, so Kestra is configured to balance throughput (the ability to process a lot of executions in parallel) and latency (the ability to process executions quickly) without using too many resources.

Size and Scale Kestra Infrastructure – Executors, Workers, Schedulers

Kestra is designed to scale from lightweight workflows to enterprise-scale orchestration with thousands of task runs per minute. Choosing the right infrastructure depends on your workload patterns, execution volume, and latency requirements. This page provides practical guidance on how to size your Kestra deployment, how many Executors and Workers you need, and how to scale and tune performance over time.