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Cribl

How Cribl Helps the UK Public Sector Manage Challenges Around Growing Data Costs and Complexity

As the Data Engine for IT & Security, Cribl helps organisations overcome several challenges, including : In this first blog, we will concentrate on how Cribl can help the UK public sector deal with ever-rising data volumes whilst controlling costs.

Make Moves Without Making Your Data Move

How much of the data you collect is actually getting analyzed? Most organizations are focused on trying not to drown in the seas of data generated daily. A small subset gets analyzed, but the rest usually gets dumped into a bucket or blob storage. “Oh, we’ll get back to it,” thinks every well-intentioned analyst as they watch data streams get sent away, never to be seen again.

Security Has a Big Data Problem, and an Even Bigger People Problem

Got cybersecurity problems? Well, the good news is the same as the bad news — you’re not alone. The world of security has a big data problem and an even bigger people problem. Enterprise connectivity has drastically increased in the last decade, meaning every employee, contractor, and vendor has some level of access to corporate networks. To support this growth, companies monitor exponentially increasing infrastructure and traffic, producing a steadily rising volume of data.

How the All-In Comprehensive Design Fits Into the Cribl Stream Reference Architecture

In this livestream, Ahmed Kira and I provided more details about the Cribl Stream Reference Architecture, which is designed to help observability admins achieve faster and more valuable stream deployment. We explained the guidelines for deploying the comprehensive reference architecture to meet the needs of large customers with diverse, high-volume data flows. Then, we shared different use cases and discussed their pros and cons.

Cribl Stream's Replay vs Cribl Search's Send: Understanding the Differences

In today’s contemporary landscape, organizations produce more data than ever, which needs to be collected, stored, analyzed, and retained, but not necessarily in that order. Historically, most vendors’ analysis tools were also the retention point for that data. Still, while this may first appear to be the best option for performance, we have quickly seen it creates significant problems.

Performing Geolocation Lookups on IP Addresses to Use in Cribl Search

Are you tired of sifting through data without context? Cribl Search adds valuable depth to your data, making it much easier to understand and analyze. No more squinting at cryptic logs or puzzling over unknown IP addresses! ️ Some common examples of how Cribl Search can enrich your data are adding service names or matching to threat intelligence. Another popular data enrichment is adding geographical location to events based on IP addresses.

Looking at nth degree's Innovative Fractional Service Delivery Model

The nth degree team joins Cribl's Ed Bailey and Andrew Duca to discuss nth degree's innovative fractional service delivery model. This is a discussion anyone who has had to engage professional services should be interested in hearing. nth degree has developed a service delivery model that enables fast engagement and removes friction around service delivery and planning. Imagine not having to get an SOW reviewed by legal for every engagement. That alone solves a big problem for almost everyone.

Integrating Cribl Stream with the Built-in Tables of Microsoft Sentinel

Cribl’s integration catalog is ever-expanding. At Cribl, we constantly collect feedback on where to integrate next and channel it to deliver more high-impact integrations into our catalog. Whether it is Sources, Collectors, or Destinations, we constantly add new integrations to expand our reach in the IT security and observability ecosystem.

Generating and Comparing Statistics with Eventstats in Cribl Search

When exploring data, comparing individual data points with overall statistics for a large data set is often useful. For example, you might be interested in understanding when a performance metric rises above the historical average. Or possibly knowing when the variance of that metric increases past a certain threshold. Or maybe noting a change in the distinct number of IP addresses connecting to your public web portal.