Operations | Monitoring | ITSM | DevOps | Cloud

Now available: Secure, real-time access to your observability data via Logz.io’s Model Context Protocol (MCP) Server. The Logz.io MCP Server brings your logs, metrics, and telemetry data into the Model Context Protocol (MCP), an emerging open standard that lets AI systems query real data securely and contextually, in real time. That means any MCP-compatible LLM, like Claude Desktop, Cursor, your own AI agent… can now connect directly to your Logz.io environment.

In today’s always-on digital world, even the best messaging platforms—like Apache Kafka and Apache ActiveMQ—can become blind spots that undermine resilience. This article exposes the “observability illusion” many organizations face, showing how limited visibility and manual processes lead to outages, high costs, and constant firefighting. Learn how meshIQ transforms reactive operations into proactive engineering through unified observability, automation, and self-service.

Ensuring digital services remain accessible, reliable, and secure is a high priority for any organization operating at scale. For the Department of Veterans Affairs (VA), this focus is central to its mission of providing quality care to veterans, their families, and caregivers. Often described as “the largest IT shop in the United States,” the VA manages 2.7 million pieces of equipment across a vast network of interconnected systems.

In September at.conf25, we announced how Splunk is shaping the future of digital resilience in the age of AI. Agentic AI is rewriting what it takes to build a leading observability practice. As vibe coding gains steam, applications will be built with less human involvement. At the same time, the rise of AI agents demands specialized telemetry to ensure models are performing as intended—aligned to their business purpose and cost.

Splunk is very excited to be sponsoring Kubecon North America once again, kicking off this week in Atlanta, GA. As many know, Splunk is one of the top contributors to the OpenTelemetry project. We’re happy to have sent many of the Splunkers who serve as project maintainers and contributors to lead SIG meetings and engage with the greater community in the OpenTelemetry Observatory, sponsored by Splunk.

Nowadays, AI agents are becoming more and more popular and often deployed as part of production systems. However, this rapid adoption brings unique observability challenges that require flexible solutions. On the one hand, AI agents are fundamentally just like any other software services that produce the same classic observability signals we’re familiar with: metrics, logs, and traces.

The age of dashboards is ending, as observability has only created more noise for network teams to sift through. Kentik SVP of Product, Mav Turner, lays out why true network intelligence requires a clean, contextual data foundation to finally create a network that thinks.

As we move toward 2026, observability is evolving from an engineering luxury to an operational necessity. Modern applications span microservices, containers, APIs, and data pipelines and when something breaks, users expect instant recovery. That urgency is fueling rapid market growth. According to Market.us, the Global Data Observability Market is projected to reach several billion dollars by 2033, growing at a CAGR exceeding 20% between 2024 and 2033.