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Latest Posts

Goats on the Road: What Customers Are Telling Us

The best part of my job is talking with prospects and customers about their logging and data practices. I love to talk about everything they are currently doing and hope to accomplish so I can get a sense of overall goals and understand current pain points. It’s vital to come up with solutions that provide broad value across the enterprise and not just a narrow tactical win with limited impact.

How to Leverage Cribl and Exabeam: Parser Validating

Organizations leverage many different cybersecurity and observability tools for different departments. It’s common to see the IT department using Splunk Enterprise, while the SOC uses Exabeam. Both of these tools use separate agents, each feeding different data to their destinations. Normally this isn’t a problem unless you’re talking about domain controllers. Domain controllers only allow a single agent, meaning you can’t feed two platforms with data.

Cribl.Cloud Simplified with Consumption Pricing

One year ago, we launched Cribl.Cloud as a cloud-hosted option for our industry-leading data pipeline product, Cribl Stream. Customers had a choice of either deploying on-premises with a subscription-based tiered license model or opting for our cloud service with a similar tiered billing model. Fast-forward one year, and Cribl is now a multi-product company with several unique observability products (Stream, Edge, AppScope, and soon Search) to offer our customers.

Exporting Splunk Data at Scale: See a Need, Fill a Need

The Core Splunk platform is rightfully recognized as having sparked the log analytics revolution when viewed through the lenses of ingest, search speed, scale, and usability. Their original approach leveraged a MapReduce approach, and it still stores the ingested data on disk in a collection of flat files organized as “buckets.” These immutable buckets are not human-readable and largely consist of the original raw data, indexes (.tsidx files), and a bit of metadata.

Masking PII: Minimize Your Risk and Stay Out of Trouble

Consumers expect their personal information to be safe in your hands as they use your apps, services, and stores. Even in-person retailers collect customer data for loyalty programs, shopping history, and more. In addition, regulators and auditors — and while we’re at it, let’s add investors, board members, and partners to the list of people who expect all customer data to be secure at all times.

No Startup Is a Startup Forever - How to Navigate Scaling Your Company

In the last five years, Cribl has gone from 3 employees to more than 400 employees — it’s been an incredible, crazy, difficult, tiring, fucking awesome ride. It’s also been an emotional roller coaster with all the ups and downs, but despite all the challenges, things have been trending upwards.

Cribl Named as a Big Data Emerging Vendor by CRN

Although we’ve encouraged employees to take plenty of time off this summer to relax, recharge, and enjoy time with family, Cribl certainly hasn’t been on a summer holiday as a company. After the big announcement in late May with Cribl Search and our Series D funding round, we moved right into the announcement of Cribl Stream 3.5, Cribl Edge 3.5, massive upgrades to Cribl.Cloud, and the launch of our Cribl Certified Observability Program.

Empowering Security Engineers With the Cribl Pack for CrowdStrike

CrowdStrike is a class-leading endpoint monitoring solution. It collects a wealth of activity data from each managed endpoint that can be fairly voluminous. This includes network connectivity, DNS request, process activity, health checks, and the list goes on. In fact, there are over 400 event types reported by CrowdStrike! These events are a gold mine for threat hunters and blue teams looking for unusual or malicious activity. It can be extremely costly to place all this data in a SIEM.

Cribl Search Unlocks The Value of ALL Data

We announced Cribl Search in May, and customer reaction has been incredibly positive. We’ve heard for some time that organizations have data everywhere. They have data in their observability lakes, analytics tools, object stores, and at the edge. The big challenge facing enterprises is that existing search models require you to take all of this data that you don’t know is valuable or not, move it into one place, and then make decisions about whether this is valuable?

Unpopular Opinion: OKRs Are the Worst

One of the things about Silicon Valley culture is the obsession around the technology that gets created and the idea of the engineer as the hero of the story. You see the same kind of thing with other professions — like with finance executives in New York, celebrities in Hollywood, or firefighters and police officers in different areas across the US.