Operations | Monitoring | ITSM | DevOps | Cloud

Our amazing user community is growing so fast that we want to give you more resources to learn and share your knowledge and experience with others. So…today we launch Cribl Curious! Curious is a Q&A site for asking and answering technical questions about Cribl Stream, Cloud, Edge, Packs, and AppScope. Goat a question about how something works in Cribl? Come on over to see how your peers have solved similar problems. Checked the docs and it’s just not clicking for you?

In this blog post, we will walk you through how to develop a continuous performance management playbook for your business to effectively integrate and manage performance as an integral part of your development process – enabling you to build fast experiences faster than your competition. Let’s dive in!

Today, IT and site reliability engineering (SRE) teams face pressure to remediate problems faster than ever, within environments that are larger than ever, while contending with architectures that are more complex than ever. In the face of these challenges, artificial intelligence has become a must-have feature for managing complex application performance or availability problems at scale.

Spring Boot is a very popular microservice framework that significantly simplifies web application development by providing Java developers with a platform to get started with an auto-configurable, production-grade Spring application. In this blog, we will walk through detailed steps on how you can observe a Spring Boot application, by instrumenting it with Prometheus and OpenTelementry and by collecting and correlating logs, metrics, and traces from the application in Grafana Cloud.

Today, I'm excited to share the release of a long-planned and requested feature - our new Check Overview Page. Until now, Checkly enabled you to troubleshoot single alerts, but a deep dive into the long-term performance trends was limited. That is not the case anymore. In the new Check Overview, we’re introducing the enhanced analytics in four distinct categories: The update is focused on two important outcomes.

As the adtech industry continues to expand and the volume of ads sold and served grows exponentially, the only way to manage the business is through programmatic advertising. This approach utilizes data insights and algorithms to automatically serve ads to the right user, at the right time, on the right platform, and at the right price. The speed and scale of online advertising means that adtech companies need to collect, analyze, and act upon immense datasets instantaneously, 24 hours a day.

Any significant shift in an organization’s software engineering culture has the potential to feel tectonic, and observability (o11y for short)—or more specifically, Observability Driven Development—is no different. Leaning into observability, which calls for tool-enhanced investigation, hypothesis testing, and data richness can be cumbersome even for the most veteran of teams.

When security analysts choose technology, they approach the process like a mechanic looking to purchase a car. They want to look under the hood and see how the product works. They need to evaluate the product as a technologist. On the other hand, the c-suite has different evaluation criteria. Senior leadership approaches the process like a consumer buying a car.