Operations | Monitoring | ITSM | DevOps | Cloud

AI SRE in Practice: Enabling Non-Experts to Troubleshoot Kubernetes

Kubernetes troubleshooting traditionally requires deep platform expertise. Understanding pod lifecycle, decoding error messages, correlating events across resources, and identifying root cause all demand experience that takes years to build. This expertise gap creates a bottleneck where only senior engineers can handle production issues, limiting how quickly teams can resolve incidents.

How does AI enhance search?

Explore how artificial intelligence enhances search engines through semantic understanding, vector embeddings, and contextual retrieval. Learn how AI-powered search delivers faster and more accurate results. Additional Resources: About Elastic Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale. Elastic’s solutions for search, observability, and security are built on the Elastic Search AI Platform — the development platform used by thousands of companies, including more than 50% of the Fortune 500.

Database Schema Evolution: Designing for Continuous Change | Harness Blog

Modern database design is no longer a one-time activity but an ongoing process that evolves as business needs, scale, and system behavior change. Instead of large redesigns, teams rely on incremental and backward-compatible schema changes, such as adding columns, indexes, or new tables, to safely adapt the database without disrupting production.

How to Lower Your Egress Fees in 2026

Egress fees can quietly drive cloud costs. Learn practical ways to reduce your cloud egress fees in 2026 without redesigning everything. Cloud egress fees can sneak up on you. One month your cloud bill can look reasonable, and the next it’s clear that data movement is causing your cloud spend to fluctuate. For many network teams, egress is still treated as a fixed cost or something you only revisit during a major architecture change, but that approach doesn’t hold up in 2026.

Automotive Manufacturing Speed & Accuracy with Machine Vision | Zebra

Automotive manufacturing demands speed, accuracy, and accountability. Only Zebra offers a comprehensive machine vision portfolio with hardware and software solutions for every point on your assembly line. In the fast-paced world of vehicle production, precision and complete traceability are paramount. Every component, from its initial scan upon arrival to its final placement in the vehicle, must be meticulously tracked and inspected to prevent costly errors and uphold the highest quality standards.

The Spark Avengers Unite: Dispatches on the FUTURE of IT (w/ Matt, Moe & Denis)

Tom assembles the “Spark Avengers” for a deep dive into the most talked-about innovation in IT: Nexthink Spark, the personal AI agent for every employee. Joined by Moe Haidar, Denis Schertenleib and Matt Rose, the team unpacks how Spark evolved from early LLM experiments into an enterprise-ready, autonomous IT agent already delivering 70%+ first contact resolution. From printers and frozen cameras to complex root-cause analysis, Spark is transforming support from reactive to proactive.

What's New in Calico: Winter 2026 Release

As anyone managing one or more Kubernetes clusters knows by now, scaling can introduce an exponentially growing number of problems. The sheer volume of metrics, logs and other data can become an obstacle, rather than an asset, to effective troubleshooting and overall cluster management. Fragmented tools and manual troubleshooting processes introduce operational complexity leading to the inevitable security gaps and extended downtime.

OpenTelemetry traces for Bitbucket Pipelines via webhooks

Continuous delivery is only as good as your ability to understand what’s happening inside your pipelines. When a build is slow, flaky, or burning through capacity, you need more than a green/red status and a wall of logs — you need traces. Bitbucket Pipelines now exposes pipeline execution as OpenTelemetry (OTel) traces via webhook events. This lets you stream detailed pipeline spans into your own observability stack and correlate them with the rest of your system. This post walks through.