Cribl’s suite of products excel at collecting and organizing your IT and security event data. Did you know it can also help with IoT data collection and analysis? If you can get the text of the data into Cribl, in most cases, we can process it, transform it, and send it to where you want it to go. A few years ago, I bought a weather station. I immediately hooked up some home automation gear to show me the temperature, humidity, and air quality. But the geek in me wants more.

It’s not new news that organizations are producing more data than ever. But, in order to take advantage of this data, it needs to be collected, stored, retained, and then, at some point, analyzed. Most analysis tools also act as the retention point for this data. While this may (at first) appear to be the best option for performance, it quickly creates significant problems. First, those systems were never designed for the scale of today’s growing volume of data, currently at a 28% CAGR.

Are you drowning in data from disparate sources? Are you struggling to analyze it efficiently, sift through different formats, and catch crucial signals? You’re not alone. Cribl Search and Cribl Stream is a powerful combo that lets you unlock insights from vast data volumes – regardless of their source or format. Say goodbye to siloed searches and hello to holistic analysis.

As an organization, you likely have many choices on where to store, analyze, and correlate your data. Those choices may change or iterate over time, so having an easy way to route data is needed. Enter Cribl Stream, which can route your data where it needs to go and save some effort, time, and money. It can help with organizational-wide initiatives like migrations and consolidations but can also help with smaller-scale initiatives and your day-to-day tasks of simply getting data in.

In the swiftly changing digital realm of the finance and insurance sectors, sustaining operational resilience while complying with rigorous regulatory mandates is paramount. The Digital Operational Resilience Act (DORA) marks a significant regulatory milestone designed to ensure entities within the financial services sector are equipped to withstand, respond to, and recover from all types of ICT (Information and Communication Technology) related disruptions and threats.

A couple of years ago, I wrote another blog on how Oracle Cloud Infrastructure (OCI) Object Storage can be used as a data lake since it has an Amazon S3-compliant API. Since then, I’ve also fielded several requests to capture logs from OCI Services and send them through Cribl Stream for optimization and routing to multiple destinations. There are two primary methods to achieve this.

First, when I mention Loki, I’m not talking about one of my favorite TV shows to binge-watch or the lead character played by Tom Hiddleston, who has arguably become one of my favorite characters in the Marvel universe. I’m talking about the Loki, which is a highly available, cost-effective log aggregation system that was inspired by Prometheus. While Prometheus is focused on metrics, Loki is focused on collection of logs.

Data lakes are everywhere! With data volumes increasing, cost-effective storage is becoming a greater need. With Cribl Stream, you can route data to an Amazon S3 data lake and replay or search that data at rest. But nothing is more frustrating than something not working and those blasted error logs that pop up. In this blog, some common errors for your S3 sources or destinations are highlighted, and some potential root causes and solutions are highlighted.

Windows events provide a wealth of security-relevant information, especially when they are correlated and analyzed within a SIEM like IBM Qradar. Whether you rely on MITRE ATT&CK, NIST, or another security framework, Windows Events are likely one of your higher volumes (EPS – Events Per Second) and represent your largest-sized events (Gigs per day – Storage and Archive).

So, you finally have Cribl Edge collecting Logs, Metrics, and Events from your Kubernetes clusters and scraping your Prometheus endpoints. This post will guide you in enriching your events and metrics to help you identify and spot trends or anomalies in the performance of your containers.