Operations | Monitoring | ITSM | DevOps | Cloud

Today marks an exciting milestone not just for Cortex, but for every organization looking to foster a culture of engineering excellence. Knowing who owns what is one of the hardest and most important challenges for engineering teams. Without clear ownership, incidents take longer to resolve, migrations stall, and enforcing standards becomes nearly impossible.

With over 50 built-in integrations, Cortex customers have an always-up-to-date, single interface for their engineering priorities, tools, and tasks. But large organizations have a lot of tools. And if you're running internally hosted tools, or for policy or security reasons would prefer to keep your access tokens private, that used to limit what was possible in your internal developer. Not anymore.

This is a guest post from Armin Ulrich, a fullstack developer, and founder of placid.app. He also created the MadeWith* network where he shares his projects and allows other developers to share theirs. There are many things I would rather do at 9pm than tracking down a mission-critical bug, but sometimes you don’t have a choice. Let me tell you the story about a slow query that led to a cascading failure–and how it could have been worse.

The internal DevOps team at JFrog needed to provision cloud resources, create environments, and manage infrastructure for our developers. Unfortunately, it involved wasting a significant amount of time on repetitive tasks, that was slowing down the pace of innovation and taking away our developers’ focus from building new features and industry leading products.

Grafana Alerting has evolved dramatically since the legacy dashboard-alert days. Today, Grafana-managed alerts power enterprise-scale monitoring in Grafana Cloud and on-prem installations. And over the last two years, we’ve added RBAC, state history, versioning, and much more. At the same time, our own monitoring at Grafana Labs relies heavily on Prometheus-style alerts—a situation that’s not uncommon for our users, too.

By Sara Miteva Sr. Product Marketing Manager, Checkly ‍ Modern applications are complex. Microservices, third-party dependencies, and continuous deployments all contribute to a flood of telemetry data—logs, metrics, traces—flying in from every direction.

To gain adequate visibility into your distributed applications, you need to observe those applications at different levels of granularity. This means that you need to be able to query collected telemetry data both at the level of the whole application and at the level of selected components. Thanks to the power of Datadog tagging, you can already do this by aggregating your metrics within any scope of your choosing.

After 12 years of faithful service, the TrackJS interface was starting to show its age. Not that it wasn’t working—it was still doing exactly what our customers needed it to do. But when you’re staring at Bootstrap styles from 2012 and a version of LESS that might be officially defunct, it’s probably time for a refresh.

IT operations have reached a breaking point. Hybrid cloud and modern software architectures have led to unprecedented increases in the scale, complexity, and fragmentation of IT infrastructures. In their attempts to manage this complexity, enterprises invest billions into observability tools, IT Service Management (ITSM) platforms, and outsourced Managed Service Providers (MSPs).

As artificial intelligence (AI) rapidly evolves from a research novelty to an enterprise essential, one often-overlooked component is under intense pressure: the network. AI’s hunger for data and real-time performance is forcing enterprises, cloud providers, and data center operators to rethink how they interconnect data centers. Enter Managed Optical Fiber Networks (MOFN) — a modern solution for modern DCI challenges.