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The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.

The Cognitive Ceiling: Why Modern Environments Outgrew Human Interpretation

For more than a decade, organizations invested in tools and telemetry with the belief that more visibility would create more control. Monitoring expanded across cloud, application, network, and infrastructure layers. Observability platforms entered the mainstream. Automation tools promised faster detection and improved coordination. Yet despite these advancements, incidents are not easier to understand. War rooms still fill with conflicting interpretations. Signals generate more questions than answers.

Architecting Log Management for Privacy and Scale without the Headache

As companies grow, they inevitably hit a wall: observability data explodes while privacy requirements become stricter. For years, engineers have faced a painful tradeoff—either ship petabytes of sensitive data to a central cloud (incurring egress costs and compliance risks) or manage a complex self-hosted stack that is painful to scale.

Unifying Telemetry in Battery Energy Storage Systems

Battery energy storage systems (BESS) play a critical role in modern energy infrastructure. Utilities rely on these systems to balance renewable generation, stabilize grid operations, and respond to changing electricity demand. As deployments scale in size and complexity, operators require continuous insight into battery health, system performance, and grid interaction. Operators rely on telemetry generated across several operational platforms.

What Engineers Want from AI in Observability... According to the 2026 Observability Survey Report

The results show strong interest in AI for forecasting, root cause analysis, onboarding, and generating dashboards, alerts, and queries. But when it comes to autonomous action, practitioners are more cautious — and 95% say AI needs to show its work to earn trust.

Bridging the Gaps in Modern Operations: How Real-Time Messaging Improves System Reliability

In modern IT environments, reliability is no longer defined solely by system uptime or infrastructure resilience. It is equally shaped by how effectively systems, teams, and processes communicate under pressure. As architectures become more distributed and operations more complex, the gaps between tools, teams, and data streams have become one of the most persistent challenges in maintaining consistent performance.

Network Monitoring as Code

Tangling DNS, TCP handshake failures, packet loss: your network has blind spots that application-level dashboards miss. In this session, Daniel Paulus (VP Engineering, Checkly) sets up DNS, TCP, and ICMP monitors from scratch and deploys them as code using the Checkly CLI. You'll see how to import checks from the UI to a code project, use coding agents to build monitors, and debug network failures with Rocky AI, trace routes, and packet captures.

Product Update - March 2026

IncidentHub's latest product updates focus on improving the public status page, adding integrations with ticketing systems, private status page ingestion, and making the notifications more useful to the end user. Some of these improvements are driven by user feedback. Feedback is what makes the product better, and I am personally grateful to all our customers who have shared their feedback with us.

Flow State in an AI Workplace - Digital Friction 1:1 with Mike Lovewell

Tom welcomes Mike Lovewell to explore how digital friction continues to shape the modern workplace. From early days of low awareness to today’s complex, AI-influenced environments, Mike shares how friction has evolved in scale rather than cause. They discuss the growing importance of flow state, the measurable business impact of small disruptions, and why adoption—not just technology—is the key to success. AI emerges as both a solution and a new source of friction, depending on trust and usability.

Monitor schema health with engine.schema_fields: Structure, Drift, and Volatility

If you’ve worked with an observability pipeline, you’ve probably experienced schema problems: a field disappears, a type shifts from string to number, or a new label quietly appears. The causes are everywhere. Different teams adopt different naming conventions. A dependency upgrade changes the shape of a library’s log output. Over time, these small, reasonable decisions compound into schema sprawl: dashboards break, alerts misfire, and teams scramble to find out what happened.