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

How LogicMonitor Delivers AI Cost Optimization

LogicMonitor delivers AI cost optimization by unifying infrastructure telemetry, AI-specific signals, and cloud financial data into a single workflow, so teams can move from visibility to continuous, operationalized cost control. In Cost Optimization for AI Workloads: From Visibility to Control, we explored why AI workloads introduce new layers of cost complexity—from GPU-heavy compute and token-based pricing to distributed infrastructure that obscures true spend.

Cost Optimization for AI Workloads: From Visibility to Control

ITOps teams can achieve cost management of AI workloads with an observability platform that connects AI usage and performance with cloud spend for clear visibility and predictability. Behind the buzz around artificial intelligence, or AI, many companies are discovering the hidden and compounding costs of AI adoption.

What feels different about enterprise IT operations today compared to even 3-5 years ago?

Speed isn’t the problem. Speed without shared visibility is. AI compressed release cycles, multiplied dependencies, and pushed accountability to teams who no longer own the full stack. The result? Faster change. Slower resolution. Higher risk. This is why MTTR is moving the wrong way...and why observability has to evolve. : Amit Rathi.

Release v2.9: OTEL Logs, Database Functions, SNMP Functions and more.

What’s New in Netdata v2.9 In this video, we walk through the biggest updates in Netdata v2.9, including: Top Tab Database Functions to analyze slow queries and performance bottlenecks without logging into your database SNMP Network Interfaces Function for real-time visibility into network interfaces Microsoft SQL Server Collector with richer MSSQL metrics OpenTelemetry Logs Ingestion to correlate logs and metrics in one place.

Nexthink Workspace - Where DEX Work Happens

Workspace is the new space for managing DEX inside the Infinity platform. It brings signals, analysis, guided actions, personalized answers, and chat history into one clean and intuitive full-screen experience. Workspace turns everyday questions into insight and action so teams can investigate faster and make better decisions without complexity or technical query languages. Its enhanced reasoning engine is fully NQL certified, delivering accurate explanations and deeper context across every investigation.

Identify untested code across every level of your codebase

As organizations scale their services and adopt AI-assisted coding, code changes are landing faster and in greater volume than ever before. While this powerful new practice is accelerating the pace of development, it is also increasing the likelihood that untested code may slip into repositories without detection. What makes this problem even worse is that most teams have no reliable way to know which code is covered by tests.

Is Your File Integrity Monitoring Outdated? Kubernetes Needs Runtime FIM

If your file integrity monitoring (FIM) still relies on scheduled scans… it was built for static servers — not Kubernetes. In cloud-native environments, traditional FIM creates detection delays, wasted CPU, excessive I/O, and alert noise. And if a malicious process modifies a file and exits before the next scan? You might miss it entirely. In this video, we break down: Modern runtime FIM works differently. Instead of scanning everything on a schedule, it.
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Forwarding Microsoft SCOM Alerts to the Service Desk

Modern IT operations rely heavily on monitoring solutions like System Center Operations Manager (SCOM) to detect issues across servers, applications, and services. While SCOM excels at generating alerts, organizations often struggle to ensure these alerts translate into actionable incidents in their IT Service Management (ITSM) platforms. Without proper integration, critical alerts may be missed, tickets may be created manually, and incident resolution can be delayed.

How to Make AI-Generated Code Reliable with Runtime Context

AI coding assistants like Cursor and Claude Code are driving massive productivity gains, yet they have introduced a critical validation gap in the software delivery lifecycle. While these tools excel at generating syntax, they lack visibility into live production environments. This article explains how Runtime Context, the missing nervous system of AI development, secures production by moving from probabilistic guessing to deterministic, live code validation.