Cribl puts your IT and Security data at the center of your data management strategy and provides a one-stop shop for analyzing, collecting, processing, and routing it all at any scale. Try the Cribl suite of products and start building your data engine today!
Learn more ›Evolving demands placed on IT and Security teams are driving a new architecture for how observability data is captured, curated, and queried. This new architecture provides flexibility and control while managing the costs of increasing data volumes.
Read white paper ›Cribl Stream is a vendor-agnostic observability pipeline that gives you the flexibility to collect, reduce, enrich, normalize, and route data from any source to any destination within your existing data infrastructure.
Learn more ›Cribl Edge provides an intelligent, highly scalable edge-based data collection system for logs, metrics, and application data.
Learn more ›Cribl Search turns the traditional search process on its head, allowing users to search data in place without having to collect/store first.
Learn more ›Cribl Lake is a turnkey data lake solution that takes just minutes to get up and running — no data expertise needed. Leverage open formats, unified security with rich access controls, and centralize access to all IT and security data.
Learn more ›The Cribl.Cloud platform gets you up and running fast without the hassle of running infrastructure.
Learn more ›Cribl.Cloud Solution Brief
The fastest and easiest way to realize the value of an observability ecosystem.
Read Solution Brief ›AppScope gives operators the visibility they need into application behavior, metrics and events with no configuration and no agent required.
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Talk to an Expert ›November 21, 2022
Here at Cribl, we’re big on GoatFooding. We not only prepare but consume our own products, in our own products. Today we’ll pull back the curtains to shine a light on how we use Cribl products within our Cribl.Cloud service.
Cribl is a pioneer in the observability space, so what better way to use our products than by observing Cribl.Cloud? By GoatFooding AppScope in our service, before it was generally available, our Cloud development team was able to provide instant and useful feedback to the AppScope development team and collaborate on new features.
Similarly, we integrated Cribl Edge with Cribl.Cloud early on, and at a scale that tested the limits of its capabilities. Managing Fleets of thousands of Edge Nodes gave some critical insight into the problems that our customers face and helped us stay ahead of the curve.
The following rules helped establish the principles upon which our whole design system is built:
Cribl.Cloud Observability
Wherever possible, we use AppScope to integrate directly with our Stream observability cluster. The main advantage of this is that we immediately get access to all the pre-packaged metrics that AppScope gleans from its environment. In an HTTP server, this means we have instant access to latency, traffic, and error metrics. That’s three of the four Golden Signals covered without any work. Who else loves not doing work?
Within Stream, we don’t use global configuration. All configurations are contained within Packs. Additionally, sources deliver data directly to Packs rather than through global routes. This layout has the following advantages:
We maintain two Edge Fleets per environment: one for Leaders and one for Workers. Because each role has a different lifecycle and configuration, separating them in different Fleets enables cleaner management of configuration and improved ease of deployment.
We use Redis via AWS ElastiCache to store enrichment lookup data. Stream Collectors periodically load this lookup data from its source of truth. The Pipelines then use the data to enrich metrics and logs with additional dimensions or index time fields.
One example of this is within the metrics coming from Stream Leaders and Workers. We have a population of free and enterprise licensed organizations in the environment. Knowing the unique identifier of the organization the metrics are coming from allows us to look up the license and add it to the metrics as its own dimension. Dashboards and alerts can then be customized downstream to distinguish between the two populations.
Developing the Cribl.Cloud observability system while GoatFooding our own bleeding edge has been an eye-opening experience. There were times when we were unable to do what we needed because of missing features in one of our dependencies. However, moving forward in lockstep has allowed us to build a more cohesive system that just works and integrates seamlessly.
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Ryan Conway Apr 9, 2024
Brandon McCombs Mar 28, 2024