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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.
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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 central access to all IT and security data.
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The fastest and easiest way to realize the value of an observability ecosystem.
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Learn more ›AppScope gives operators the visibility they need into application behavior, metrics and events with no configuration and no agent required.
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Hold my beer: lessons from one team’s data pipeline journey
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Talk to an Expert ›When I was still writing code, our Splunk license only had enough capacity to monitor our Production environment. So we stood up a self-managed Elastic cluster for our lower environments. This quickly became unmanageable as we started logging more and adding additional environments. As I spend more time in the field, I see this pattern repeated over and over. Development teams approach the Operations team for centralized logging and it’s either too expensive, or they don’t have enough resources so they stand up their own shadow logging system. While they’re fun to stand up for a day, no developer wants to spend their time managing an Elastic cluster. These become incredibly expensive (especially if you are running them on cloud virtual machines), are rarely managed correctly, and are probably a few versions behind.
This is a new pattern to get 100% application log observability with no overhead outside of setup and built-in cost control. You only pay a small amount for log routing and compute for the queries to find the data. The pattern is very simple: Use Cribl.Cloud to selectively route logs to compressed blob storage with different retention periods. Then, use Cribl Search to find issues as they arise.
In my experience, application logs create 10x the volume of security logs. I have worked with customers who logged ~70M of the exact same Exception in a 10-minute period. Debug logs are incredibly valuable when trying to find the root cause of a service degradation or code issue, but it’s cost prohibitive to send these logs to a traditional log aggregation solution like Splunk or Elastic. Most customers only need Debug logs for 24 hours, but also want Error logs for 15-30 days for deeper forensic investigations.
In this example, I set up S3 buckets in AWS each with a different lifecycle.
Each of my environments in my SDLC needs different retention periods, similar to the following:
Next, I use Cribl.Cloud to connect my S3 buckets to HTTP endpoints. That way, I can route logs from each environment and log level to their respective destinations.
Overall, the pattern looks like this.
You can see in this diagram that DEBUG logs from all environments are being sent to an S3 bucket and are only retained for 24 hours. Not only are you moving logs to cheap blob storage, but these logs are also compressed using gzip so you will see up to a 90% reduction in storage.
Pro Tip: Use rolling file appenders to store DEBUG logs on the local file system for 1-day retention and never send logs anywhere! Cribl Search can use a common query language to federate searches across clouds and file systems.
In this example, I set up a quick .NET application to generate some transactions, with Serilog as the logging framework. Most logging frameworks will allow you to add additional appenders without modifying the code. This is an easy way for your operations team to easily route logs without having to engage the dev team to make changes. In this instance, I added an HTTP Appender that points to my Cribl.Cloud HTTP endpoint and added a property called env
that can be modified by your deployment framework.
Here you can visually see the logs flowing through Stream. These logs contain PII/PHI data so I can use our Masking functions to scrub and sensitive data before writing it out to blob storage.
ProTip: Use Sampling/Aggregation to reduce Exception count while still maintaining full observability.
Using Cribl Stream Cloud plus Cribl Search is a new way to aggregate logs while controlling costs and maintaining full observability. Our unified search capabilities enable you to use the same queries in your local development environment that you do in production. We’re so confident that you’ll love it, that we offer up to 1/TB per day for free to get started. Sign up for a free Cribl.Cloud account today!
 
Cribl, the Data Engine for IT and Security, empowers organizations to transform their data strategy. Customers use Cribl’s suite of products to collect, process, route, and analyze all IT and security data, delivering the flexibility, choice, and control required to adapt to their ever-changing needs.
We offer free training, certifications, and a generous free usage plan across our products. Our community Slack features Cribl engineers, partners, and customers who can answer your questions as you get started. We also offer a hands-on Sandbox for those interested in how companies globally leverage our products for their data challenges.
Experience a full version of Cribl Stream and Cribl Edge in the cloud with pre-made sources and destinations.
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