Cribl Packs have always provided a powerful way to package and share configurations across Cribl Stream environments. From pipelines to lookups, knowledge objects to functions—Packs make telemetry pipelines simple and portable. Now, we’re excited to announce a game changing expansion: Sources and Destinations can now be included in Cribl Packs!
This enhancement turns Cribl Packs into true end-to-end bundles of a telemetry pipeline, enabling teams to develop, test, share, and deploy with unprecedented ease. Let’s dive into the power this new capability unlocks.
End-to-End Telemetry Pipelines in Packs
The new ability to include Sources and Destinations in your Packs allows you to configure an entire data processing pipeline from ingestion to delivery inside a single reusable unit. You can now:
Ingest data from a source, whether it's Syslog, HTTP stream or Kafka topic.
Route that data through pipelines included in the same Pack for transformation, enrichment, and filtering.
Deliver the data to a destination like a SIEM, observability tool, or low cost object storage like Amazon S3.
This means teams can now create “batteries included” Packs that encapsulate a fully functional use case, making it trivial to replicate, test, and deploy proven configurations across environments. We hope this news makes you feel like a kid on Christmas morning (minus the tears because your parents didn’t have the right batteries to get your Furby working).
Portable Configurations That Just Work
Migrating a known good configuration from Cribl development workspaces to staging and production is even more efficient. With Sources and Destinations in Packs, you can now port an entire working pipeline, from input to output, between Worker Groups or Cribl Workspaces. Once you assemble your new Pack with all of the essential Sources, Event Breakers, Routes, Pipelines, and Destinations you can clone that Pack via the UI or API across different Worker Groups or Fleets. Then all you need to do is commit/deploy and start sending the data. Then your Pack just works. This drastically reduces time-to-value, increases consistency across deployments, and boosts confidence in the reliability of your telemetry workflows.
Git Integration for Collaborative Development and CI/CD
Cribl Packs’ integration with external Git repositories becomes even more powerful now that Sources and Destinations are supported. In this release you can now push changes directly from the Cribl UI to the repository. Your entire end to end configuration bundle lives in Git, enabling:
Branch-based development to isolate and iterate on changes without disrupting production.
Pull request workflows that ensure code reviews, testing, and approvals are part of the change lifecycle.
Seamless collaboration with teammates who can contribute without stepping on each other’s changes.
This means your telemetry workflows are version-controlled, auditable, and traceable—just like any other modern software project (and your commit history…I’m looking at you Aren).
Automate Deployment with GitHub Actions and CI/CD Runners
By leveraging GitHub Actions or other Git runners, you can automate the rollout of Pack changes across environments. For example:
Automatically promote tested changes from staging to production.
Distribute updated Pack bundles to multiple Worker Groups or Workspaces.
Integrate Pack deployments into your existing CI/CD pipelines.
This level of automation unlocks enterprise-scale observability governance, empowering teams to deliver incremental updates safely and rapidly. For more information regarding Git automation check out the previous blog post, Time to GIT Serious: Automate Your Cribl Pack Deployments.
The Future of Telemetry Packs is Here
The addition of Sources and Destinations in Cribl Packs transforms them into complete, portable telemetry pipelines. Whether you’re standardizing log ingestion across worker groups/fleets, building reusable pipeline templates, or scaling telemetry pipelines as a service– this feature is a game changer!
Ready to build your first end-to-end Pack? Explore the documentation, try it out in your dev environment, and see how Cribl is helping teams unlock the full power of their data engines on their terms.
