Operations | Monitoring | ITSM | DevOps | Cloud

The latest News and Information on APIs, Mobile, AI, Machine Learning, IoT, Open Source and more!

Predictive Maintenance Strategies for Commercial Avionics Systems

Nothing hurts an airline more than a broken plane. A single grounded aircraft costs thousands per hour. Passengers get bumped to later flights. Crews run out of legal duty time. The domino effect spreads across the whole network. Old maintenance methods waited for things to fail. Then mechanics scrambled to fix the mess. That reactive approach is fading away. A smarter strategy has taken its place. It is called predictive maintenance. Let us explore how this changes the game for modern aviation.

Top AI Agent Development Companies for Enterprise Automation in 2026

The era of chatbots has come to an end. In 2026, the era of Artificial Intelligence (AI) agents has arrived. Enterprise companies look for AI automation agents. The AI agent market is projected to rise from $11.7 billion in 2026 to $236 billion by 2034. AI agents for automation are tools that can help companies automate their workflows. They can automate repetitive actions within the company's structure, so the team can focus more on strategic planning.

Why Custom Route Optimization Software Outperforms Generic TMS Logic

Most logistics companies running fleet routing and scheduling software already know, at some level, that the routing output is not quite right. Not wrong in ways that cause obvious failures - just consistently suboptimal in ways that dispatchers compensate for manually, shift after shift. A fleet with mixed vehicle classes that the engine treats as equivalent. Delivery windows that get re-optimised at dispatch and then fall apart when a customer calls at 10 a.m. to reschedule. Hazmat constraints encoded as exclusion zones rather than permit-specific corridor logic. These are not edge cases.

From Alerts to Action: How Agentic AI Will Transform ITOps

What if your IT systems could go beyond detecting issues to resolving them autonomously? This white paper explains how Agentic AI enables IT operations to shift from reactive monitoring to intelligent, self-driven execution. Explore use cases, challenges, and how observability data powers AI-driven actions.

Resilience for an AI-Powered Future: PagerDuty's FY26 Impact Report

The impact vision for PagerDuty.org is to enable mission-driven teams to build a resilient world and a sustainable future for all. As a leader in modern, AI-first operations, we know that operational excellence supercharges social impact. As artificial intelligence rapidly reshapes the social sector, this commitment to resilience and efficiency has never been more vital.

Scout MCP Server: Example Prompts, Use Cases, and What's New

The Scout MCP server connects your AI assistant directly to your Scout Monitoring data. Instead of switching between your editor, Scout, and a chat window, your assistant can pull traces, errors, N+1 insights, and endpoint metrics on its own and use that context to suggest or make fixes right in your codebase. This covers how to connect it, what to ask it, how other teams are using it, and what we shipped recently.

Why AI observability is a critical ITOps priority

AI Observability is a Critical Priority for ITOps Teams See how LogicMonitor helps ITOps teams monitor AI workloads, reduce blind spots, and move toward Autonomous IT. Schedule a meeting AI has shifted from experimental pilots to everyday business operations. Customers are interacting with AI-powered applications. Engineering teams are building with LLMs, GPUs, APIs, and automation at a much faster pace. That adds to the visibility strain on already overburdened ITOps teams.

How one PM scaled customer discovery with AI

Customer interviews are one of the most powerful ways to build better products — but they’re also time-consuming. In this video, Avinoam “Avi” Zelenko, Principal Product Manager at Atlassian, shares how he transformed the way he runs customer interviews using AI automation and Rovo agents. What used to take hours of coordination, note-taking, and manual summaries now happens automatically. By stitching together the Teamwork Collection and Slack, Avi built a workflow that captures conversations, summarizes insights, and shares them across teams in real time.