Operations | Monitoring | ITSM | DevOps | Cloud

Here we go with another update of ODBC, our reliable and high-performance tools for connecting to popular databases and cloud services from ODBC-compatible tools. This release features enhanced performance, essential new options, expanded capabilities, and much more. This time, the spotlight is on our ODBC Driver for Jira, which has been significantly optimized in terms of data retrieval.

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.

The telecom industry is at the forefront of digital transformation, driven by rapid technological advancements, evolving customer demands, and an increasingly competitive market. Digital transformation in telecom is not just about adopting new technologies; it’s about redefining business models, enhancing operational efficiency, and improving customer experience.

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!

Not long ago, AI was largely experimental, but today it’s a strategic imperative. Enterprise AI adoption has surged to record levels, with over three-quarters of organizations now using AI in at least one function . In Deloitte’s latest global study, almost all organizations reported measurable ROI from AI, and 74% said their most advanced AI initiatives meet or exceed ROI expectations .

Agentic AI - the term has stirred much interest since being mentioned for the first time. And why not? The business world is still basking in the comfort, ease, and speed GenAI has brought since its democratization. Agentic AI promises to propel this leap in growth further. It promises more time freed up for strategic work, for finding new avenues of development, and a complete freedom from mundane work.

We’re all looking for ways to improve on our incident response. We investigate various metrics and methodologies—all in the name of making sure our customers see the reliable and performant systems we’ve sought to build. In fact, all these efforts are leading us, as an industry, to finally realize the power of surprising anomalous events in our systems. They give us an opportunity to reexamine our expectations and see how our models of the sociotechnical system differs from reality.