Operations | Monitoring | ITSM | DevOps | Cloud

After months of development, testing, and community feedback, we’re excited to announce the general availability (GA) release of InfluxDB 3 Core and InfluxDB 3 Enterprise. This release brings us closer to our vision for InfluxDB: a time series database that helps developers solve the problem of collecting, analyzing, monitoring, and acting on data across sensors, networks, servers, and applications. We view time series as a way to analyze, monitor, and act on data through time.

Managing multiple systems that each generate their alerts and logs can quickly become overwhelming. The challenge of scattered logs is a real headache, especially in the fast-paced world of DevOps. Log consolidation is not just a convenience—it's an essential practice that can save you from chaos and improve your operational efficiency. This guide covers everything you need to know about log consolidation, from understanding what it is and why it matters, to practical steps for making it work.

Keeping your Postgres databases healthy is non-negotiable if you care about application performance and reliability. But monitoring Postgres the right way? That’s where things get tricky. Between the sheer volume of metrics and the noise that comes with them, it’s not always obvious what to pay attention to—or when. This guide breaks things down with a focus on what matters in real-world production setups.

Serverless computing is a modern cloud-based application architecture in which the application’s infrastructure and support services layer are completely abstracted from the software layer. While every application still relies on physical servers to run, serverless applications shift that responsibility to cloud service providers like Amazon Web Services (AWS).

Risk assessment requires context. One of the primary challenges with protecting cloud environments is understanding how certain activity can lead to risk. Risky behavior can be categorized as any activity or action that increases the likelihood of an attack in your cloud environment. While certain activity may not be malicious on its own, it can expand an environment’s attack surface or indicate post-compromise behavior.

Cloud adoption has reached a tipping point — 98% of U.S. organizations have already migrated at least some business operations to the cloud. Global cloud spending is projected to reach $1.3 trillion by 2025 as companies rapidly embrace off-premise solutions, with 63% of IT decision-makers reporting accelerated cloud migration plans over the past 12 months.

Traditional monitoring approaches have served IT operations for decades, providing basic visibility into system health through predefined metrics and thresholds. However, these conventional methods face significant limitations when confronted with modern, complex environments: Static Thresholds and Rules Traditional monitoring relies heavily on manually defined thresholds and rules.

Switching from one network management system (NMS) to another is a big decision for IT teams and MSP businesses. An NMS is the central hub for everything from network troubleshooting deep dives to planning hardware refresh cycles and enabling quarterly business reviews (QBRs). And even if a different platform is clearly a better fit for your organization than your current NMS, it’s important to consider the operational overhead of actually making the switch.

Seems like you can’t throw a rock without hitting an announcement about a Model Context Protocol server release from your favorite application or developer tool. While I could just write a couple hundred words about the Honeycomb MCP server, I’d rather walk you through the experience of building it, some of the challenges and successes we’ve seen while building and using it, and talk through what’s next. It should be pretty exciting, so strap in!