This is the first of a planned series of blog posts that explain how the Cribl SRE team builds, optimizes, and operates a robust Observability suite using Cribl’s products, Cribl.Cloud operates on a single-tenant architecture, providing each customer with dedicated AWS accounts furnished with ready-to-use Cribl products. This provides our customers with strict data and workload isolation but presents some interesting and unique challenges for our Infrastructure and operations.

Remember when you used to jot down passwords on sticky notes? Well, those days are long gone. In today’s world of data pipelines, secrets, similar to API keys, are like digital VIP passes. They open doors to critical systems and keep sensitive info on lockdown. At Cribl, we’re all about top-notch data security, and that means guarding your secrets like treasure. Let’s dive into our game plan for keeping secrets safe throughout the entire software development lifecycle (SDLC).

The greatest innovations are often the simplest. They address fundamental needs and make life easier in the most direct way. Cribl Lake was just announced as the winner of CRN’s 2024 Tech Innovators Award for Data Information Management. We are so happy and honored by this recognition, which solidifies our belief that the best innovations are indeed the simplest.

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?

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.

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.