Kestra—Build Data Workflows That Don't Break at Scale
Open-source [16k+ stars]
Working on a data pipeline is not simple:
Jobs fail, but there’s no clear retry logic.
Logs are scattered across systems, making debugging a nightmare.
Downtime during maintenance disrupts everything.
Kestra is an open-source, event-driven orchestration platform (with 16,300+ stars on GitHub) that helps teams automate complex workflows without the headaches of traditional tools like Apache Airflow.
Let’s dive in to learn more!
The problem
There’s a reason top companies heavily invest in workflow orchestration:
Scaling data operations is hard.
Ensuring reliability across distributed systems is harder.
Keeping everything running without failure? That’s the real challenge.
Traditional orchestration tools like Apache Airflow or Prefect help, but they come with their own trade-offs:
Managing workflows at scale gets complicated fast.
Debugging workflows across multiple cloud services is painful.
Scaling requires additional infrastructure overhead.
Kestra solves these challenges.
About Kestra
Kestra is built for teams who need scalability, reliability, and ease of use—without managing unnecessary complexity.
Key features:
Event-driven & highly scalable → Run millions of executions with event-based triggers (no manual scheduling required).
Workflows-as-code → Define workflows in YAML for version control, collaboration, and easy deployment.
Seamless integrations → Works with AWS, GCP, Azure, Snowflake, Databricks, and more.
Real-time monitoring & analytics → Custom dashboards and centralized logs make debugging painless.
No-code editor → Build and edit workflows visually, so non-engineers can contribute too.
The latest release—Kestra 0.21 made it even better.
Kestra 0.21
The latest enhancements to Kestra make workflow automation smoother, debugging easier, and maintenance less painful.
A no-code flow editor to simplify plugin navigation.
Log shipper to forward logs efficiently across your infra.
Custom dashboards to track logs, metrics, and execution states.
A “finally” flow property to execute cleanup tasks if previous steps fail.
A maintenance mode to safely upgrade your instances without disrupting workflows.
This YouTube video by Kestra covers these updates in more detail →
Conclusion
Building scalable, reliable data pipelines isn’t just about moving data.
Instead, it’s about orchestrating complex workflows without manual oversight.
However, most workflow orchestration tools aren’t built for scale:
Managing logs across distributed systems is a nightmare.
Downtime during upgrades can halt critical operations.
No-code solutions often lack power and flexibility.
Kestra’s open-source event-driven orchestration platform solves all these problems ✨!
The team also has a YouTube channel you can subscribe to. It is full of tutorials and helpful content for getting started with Kestra and orchestrating workflows at scale without any challenges.
They are solving a big problem with workflow orchestration and we are eager to see how they continue.
Thanks to Kestra for showing us their latest updates and working with us on this post!
Thanks for reading!