Observability is a methodology that you incorporate into your enterprise architecture to provide greater visibility into what is happening. It helps us determine the states of the system from their external outputs and allows technicians to identify bottlenecks, predict issues and mitigate them. As the architectures of IT systems are becoming more complex and distributed we use observability to meet the need to measure their internal states.

Many developers don’t know what instrumentation really is, and those who do don’t really understand the black magic that takes an application and makes it emit telemetry, especially when automatic instrumentation is involved. On top of that, each programming language has its own tricks. I wanted to unwrap this loaded topic on my podcast, OpenObservability Talks. For this topic I invited Eden Federman, CTO of Keyval, a company focused on making observability simpler.

When we began the week, we had zero awards from Comparably. As we end the week, we now have a three-peat of awards. Cribl was recognized among 70,000 companies out of 15 million ratings – winning top honors for Happiest Employees, Best Compensation, and Best Perks and Benefits. We’re thrilled to be recognized by Comparably, and we’re looking forward to continuing our pursuit of being the best place to work.

In my last blog post, Building a Cost-Effective Full Observability Solution Around Open APIs and CNCF Projects, we introduced using ChaosSearch in combination with the most popular open source front- and back-ends in the application observability space. In case you missed it, the TL;DR version is that you can use a variety of open source projects and open API-based components to build the best-of-breed observability stack of your choice rather than relying on expensive, all-in-one solutions.

Observability is a hot topic in the IT world these days. It is oftentimes discussed through the lens of the “three pillars of observability”: Logs, Metrics and Traces. Indeed these telemetry signal types help us understand what happened, where it happened and why it happened in our system.

Depending on your business, MTTR stands for mean time to repair or mean time to recovery – but it can also mean resolution, resolve, or restore. No matter how you define it, the basic measurement is the same: it’s the time it takes from when something goes down to when it is back and fully functional. This includes everything from finding the problem to fixing it. For ITOps teams, keeping MTTR to an absolute minimum is crucial.

Since introducing BindPlane OP earlier this year, we’ve received a lot of feedback asking for the enterprise features you require to deploy in production. With functionality like SSO, RBAC, and Audit reporting all surfacing to the top of that list. Today we’re launching BindPlane OP Enterprise in beta, which introduces support for LDAP and AD authentication. We’d love for you to try it out and let us know what you think.

Building modern, cloud-native applications introduces new challenges to teams and organizations. As these systems grow and scale, struggles abound: inconsistent performance monitoring experiences across siloed tools, wasteful performance management practices with duplicated efforts, and mounting frustration from colleagues and customers. Surmounting these challenges requires multiple sources of data and truly unified observability.

Monitor Oracle DB in Google Cloud Platform with the Google Ops Agent. The Ops Agent is available on GitHub, and makes it easy to collect and ship telemetry from dozens of sources directly to your Google Cloud Platform. You can check it out here! Below are steps to get up and running quickly with observIQ’s Google Cloud Platform integrations, and monitor metrics and logs from Oracle DB in your Google Cloud Platform.

We all know that observability is a must-have for operating systems in production. But we often neglect our own backyard — our software release process. We noticed we made that mistake here at Logz.io. We were wasting time and energy in handling failures in the CI/CD pipeline, and made our Developer-on-Duty (DoD) shifts tedious. That’s why it’s critical to incorporate your observability practices into your CI/CD pipeline.