Cribl Search is agnostic, allowing administrators to now query Snowflake datasets as they can dozens of other Lakes, Stores, Systems & Platforms. The data that IT and security teams rely on to monitor network operations continues to grow at a 28% CAGR, and it’s stressing many organizations’ ability to analyze all this data effectively. In fact, in some cases, less than 2% of it ever gets looked at.

The Batch Processor in the OpenTelemetry project is used in both the SDKs and the OpenTelemetry Collector. What exactly is this processor, and what does it do? And, how can you use the OTLP Logs, OTLP Metrics, and OTLP Traces Functions in Cribl Stream and Cribl Edge to build batches like a boss?

Managing and storing vast amounts of data is no small feat, and can be a real drain on resources. Organizations often need to retain data for extended periods — sometimes up to seven years — to comply with regulations. It’s a common dilemma: data volumes keep skyrocketing, but budgets don’t follow suit. IT and security teams face immense pressure to handle this data deluge while navigating procurement pitfalls.

IT and security teams dealt with massive changes a few short years ago. New deployment environments added to the monitoring toil, while architectural shifts complicated IT operations’ cost and performance effectiveness. On the security side, the protected perimeter expanded exponentially. These factors resulted in a huge increase in data volumes and complexity, leading teams to turn to tooling and platforms to cope with their data.

Dynamic Application Security Testing (DAST) is a type of security testing that actively exercises and inspects a web application for security vulnerabilities. A DAST scanner sends an assortment of payloads to the target application, typically through HTTP requests for web applications, then analyzes the responses and behavior to detect vulnerabilities. DAST is language and framework agnostic, allowing for security scans against any web application with careful configuration.

The SIEM market attracts attention for a variety of reasons. First, it is dominated by a number of large players but there are a range of smaller companies vying for market share. It is also a market generally accessible to new entrants. There’s always a new company pitching a different spin on SIEM, whether it’s a new architectural model in the cloud, faster analytics from running on a third-party data warehouse, or leaning into new, undefined terms like a security data fabric.

Integrations are the bread and butter of building vendor-agnostic software here at Cribl. The more connections we provide, the more choice and control customers have over their unique data strategy. Securing these integrations has challenges, but a new class of integrations is creating new challenges and testing existing playbooks: large language models. In this blog, we are going to explore why these integrations matter, investigate an example integration, and build a strategy to secure it.

In modern IT environments, logging has become an integral part of application development and operations. Logs, metrics, and traces allow organizations to alert on events, monitor performance, and troubleshoot issues effectively. However, as applications scale and generate an increasing volume of logs year over year, managing them efficiently becomes a daunting task for engineering teams and budget makers.

Cribl is a customer first company. Building high value, secure-by-design software for security and IT teams has been by far the most gratifying experience of my professional career. As a security professional that deeply believes in Cribl’s product and mission, I share the excitement of changing forever how our customers operate and enabling them to protect their organizations; working at Cribl has been my greatest calling.

Being a Managed Security Service Provider (MSSP) or delivering a Managed Detection and Response (MDR) service is hard. You’re doing the jobs that are so hard that large swaths of organizations turn to you to handle those complex jobs for them. MSSP/MDR tech stacks are dynamic and highly customized, allowing for competitive offerings at competitive prices.