Operations | Monitoring | ITSM | DevOps | Cloud

Debugging during development is easy. You've got a debugger, stack traces, and logs right in front of you. But once your Godot game is in the hands of players, things get trickier. Most won’t report bugs, and if they do, you’re lucky if they include anything more than “it crashed”.

We’re thrilled to release NiCE Active 365 Management Pack 4.4 for Microsoft SCOM. The new 4.4 release is packed with powerful new enhancements driven by customer input and evolving needs. It especially focuses on improving monitoring capabilities for Azure-based services and ensuring compatibility with Microsoft’s evolving ecosystem.

We are pleased to announce the general availability of SystemEDGE 6.5. For customers using DX NetOps, SystemEDGE is a key component for gaining a comprehensive view of server infrastructure health. It functions as an agent that resides on systems like physical servers or virtual machines. SystemEDGE collects fundamental performance and status information and delivers reports via SNMP.

Now available: Secure, real-time access to your observability data via Coralogix’s Model Context Protocol (MCP) Server. AI agents are only as powerful as the context they’re given. Today, we’re excited to announce the launch of the Coralogix MCP Server, which enables third-party AI agents to connect directly to your observability data across production, staging, and other environments.

The Uptrace team is thrilled to announce the release of v2.0—our biggest update yet! This release represents a complete reimagining of how observability data should be stored, queried, and managed. With multi-project support, revolutionary JSON-based storage, powerful data transformations, and a host of developer-friendly features, Uptrace v2.0 is designed to scale with your growing infrastructure needs.

LLM-powered agents are reshaping software, but when they fail, troubleshooting is guesswork. Lumigo’s new AI Agent Observability, now in beta, gives you visibility into the entire lifecycle of your agents, from prompt to response to internal decision logic. Built for modern AI workloads, this feature is designed to help engineers monitor, debug, and optimize agents running on platforms like OpenAI, Anthropic, and open-source models.

As organizations begin to scale their observability strategy, point and click methods of management become increasingly unworkable. This is why Coralogix has now fully released the Coralogix Operator for Kubernetes. Kubernetes operators are control loops that allow users to declare their desired state in their Kubernetes clusters, and the operator is responsible for resolving this state.

We’re going beyond notifications — and building the most powerful, flexible, and team-first on-call experience on the market. When we launched Signals, it was because alerting and on-call desperately needed a reset. Legacy tools hadn’t evolved with the way modern teams work — they were individual-centric, inflexible, and wildly overpriced. Signals changed that.

AI is changing how we build software — but debugging code still comes down to having context. One minute the model’s performance is cruising. The next, you’re hit with a KeyError from a tool you forgot existed, triggered by a model that silently timed out, and a retrieval call that returns... nothing, or 11 “Let me try this a different way" messages before failure. You’re stitching together LLM calls, agents, vector stores, and custom logic. Then hoping it holds up in prod.