Operations | Monitoring | ITSM | DevOps | Cloud

In 2022, we introduced Grafana Mimir, our open source, horizontally scalable, multi-tenant time series database (TSDB) designed for long-term storage of Prometheus and OpenTelemetry metrics. Over the years, Mimir has become a go-to metrics backend within the open source community, with 30 project maintainers and more than 4.7k GitHub stars.

IT infrastructure is vast, complex, and interdependent. At any point in time, businesses rely on thousands of servers running thousands of processes. Detecting server downtime is fairly easy—but true observability is when you know precisely which processes are working as intended and which are silently contributing to performance degradation. A failed database worker or a memory-leaking background service can silently drain resources until your most critical apps grind to a halt.

We're excited to announce one of our most frequently requested features: inverted DNS checks. This new capability allows you to detect when DNS records are created (whether they're planned infrastructure changes or rogue records) and prevent unwanted values from appearing in your DNS configuration.

Getting started with monitoring for Microsoft Azure environments can be a lengthy and manual process. Many tools require users to create app registrations, assign permissions, and enable log forwarding or telemetry data collection across multiple portals and scripts. These fragmented steps slow down onboarding and introduce opportunities for misconfiguration, making it harder for teams to quickly achieve full visibility.

When an application slows down or fails, pinpointing the cause isn’t always simple. Is it a backend regression, a misbehaving API, or a bottleneck somewhere deep in the network? Without full visibility, teams waste precious time troubleshooting across disconnected tools and layers. Datadog Synthetic Monitoring now supports Network Path to help you proactively identify whether user-facing issues stem from your code or from the underlying network.

Application configs change over time, often in small ways that are easy to miss. They may start simple — a few environment variables, one exporter, nothing unexpected. As your instrumentation grows, you add rules for filtering health check spans, adjust sampling based on attributes, or introduce environment-specific resource settings. Each change makes sense on its own. But months later, the picture can look different across dev, staging, and production.

Application Performance Monitoring (APM) means many things to many people. At its core, it enables developers to diagnose why their applications are slow and helps them provide a better experience to their users. Traditionally, this is accomplished by collecting a lot of data and displaying it in the form of dashboards and request traces. The problems you're trying to solve are generally known up front.

Microsoft Teams is one of the most popular tools for work communication today. Whether you're chatting with your team, jumping on a video call, or sharing files, it helps keep everyone connected. But let's face it – MS Teams isn’t perfect. You’ve probably run into issues like calls dropping, bad audio, or slow Teams performance. These problems can be frustrating, especially when you’re in the middle of an important meeting or deadline.

People often get confused between Monitoring and Observability, using the terms interchangeably in DevOps. However, they represent two distinct yet complementary concepts that play a crucial role in ensuring application reliability and performance. As modern applications evolve, over 90% of new digital services are built using microservices and cloud-native architectures. Traditional monitoring alone can’t provide full visibility into distributed systems.

Cloud network monitoring software is a type of software designed to monitor and manage the performance, availability, and security of networks and network devices in cloud environments. These tools use various techniques to gather information about network traffic, bandwidth utilization, application performance, and other metrics related to network health and availability.