Operations | Monitoring | ITSM | DevOps | Cloud

Are you tired of getting kicked offline in the middle of an important call or losing your connection during a critical task? Do you wish there was a way to ensure your network stays up and running smoothly? Look no further, because we've got the inside scoop on network connectivity monitoring! Whether you're a tech pro or a business user, monitoring your network's connectivity is essential to keeping your connections strong.

This post is part of an ongoing series about troubleshooting common issues with microservice-based applications. Read the previous one on intermittent failure. Queues are an essential component of many applications, enabling asynchronous processing of tasks and messages. However, queues can become a bottleneck if they don’t drain fast enough, causing delays, increasing costs, and reducing the overall reliability of the system.

We are caught in a whirlwind of rapid data change. As more engineers, services and sophisticated practices are helping generate an astronomical amount of digital information, there’s a growing challenge of the data explosion. Coralogix offers a completely unique solution to the data problem. Using Coralogix Remote Query, the platform can drive cost savings without sacrificing insights or functionality.

Grafana Tempo 2.1 is out and comes with a host of TraceQL improvements. Tempo 2.1 comes with some nice incremental improvements to TraceQL and likely some breaking changes. There’s a section down below about those, too.

At ObserabilityCON 2022, we announced a limited private preview program for Grafana Cloud Frontend Observability, our hosted service for real user monitoring. Today we are excited to introduce a public preview program that makes Frontend Observability accessible to all Grafana Cloud users, including those in our generous free-forever tier. Simply look for Frontend under Apps in the left-hand navigation of the Grafana Cloud UI and click through to set up the feature. (Not a Grafana Cloud user?

Cost optimization has been one of the hottest topics in observability (and beyond!) lately. Everyone is striving to be efficient, spend money wisely, and get the most out of every dollar invested. At Logz.io, we recently embarked on a very interesting and fruitful data volume optimization journey, reducing our own internal log volume by a whopping 50%. In this article, I’ll tell you how exactly we achieved this result.