The latest News and Information on Log Management, Log Analytics and related technologies.
In this livestream, Jackie McGuire and I discuss the harmful effects of data debt on observability and security teams. Data debt is a pervasive problem that increases costs and produces poor results across observability and security. Simply put — garbage in equals garbage out. We delve into what data debt is and some long term solutions. You can also subscribe to Cribl’s podcast to listen on the go!
The Cribl team just wrapped up the 2023 AWS Summit in Washington, DC, and we were thrilled to spend a few days chatting with public sector organizations looking to gain the freedom and flexibility our products offer.
OpenTelemetry (also abbreviated as OTEL) is an increasingly popular open-source observability platform under the Cloud Native Computing Foundation (CNCF), which is currently the most active project in the CNCF after Kubernetes. It was created to establish a unified and vendor-agnostic way for instrumenting, collecting, and exporting telemetry data for your system and application across traces, logs, and metrics.
Cribl has a unique position right in the middle of the observability market, giving us a distinct view of all things security, APM, and log analysis. Observability as a concept has exploded into specialized areas over the past two years, and making sense of the players and market forces, particularly in a difficult macro environment, can be tricky. Let’s break it down.
Fintech companies operate in a complex technological and regulatory environment. They rely heavily on cloud-native technologies and microservices architectures to handle financial transactions and data, often at a massive scale. To maximize application reliability, fintech companies need full visibility into their software systems and applications. An agile monitoring solution like observability is crucial to improving performance and user experience.
We recently launched several new Cloud Monitoring features to improve your visualization and troubleshooting experience.
The State of DevOps Report finds a clear link between documentation quality and an organization’s ability to meet its performance goals.
If you work with large amounts of log data, you know how challenging it can be to analyze that data and extract meaningful insights. One way to make log analysis easier is to normalize your log messages. In this post, we’ll explain why log message normalization is important and how to do it in Graylog.
