Operations | Monitoring | ITSM | DevOps | Cloud

User Feedback to Pull Request in Minutes with Cursor + Sentry

Apr 14, 2026 By Sentry In Sentry
Cursor Automations + Sentry Triggers: go from user feedback to a pull request automatically. See how to set up an end-to-end workflow that turns feedback into code changes, posts the PR to Slack, and keeps your team in the loop. In this video, we walk through a real-world example using Sentry Docs. A user submits feedback through a widget on the docs site, it lands in Sentry as an issue, and when assigned, a Cursor Automation kicks off. The automation reads the feedback, validates it, generates a PR against the repo, and posts the link in the relevant Slack thread. No manual work required.
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datadog

Offline evaluation for AI agents: Best practices

Apr 14, 2026 By Tom Sobolik In Datadog
If you’re building LLM-powered applications and agents, you’ve probably asked yourself: “How do I know if my changes actually made things better?” You can tweak prompts, adjust temperature settings, or try different models, but it’s not always easy to validate whether version B’s response is better than version A’s. Most teams fly blind in preproduction and rely on user feedback to see how well their application works in the real world.
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qovery

Stopping Kubernetes cloud waste: agentic automation for enterprise fleets

Apr 14, 2026 By Mélanie Dallé In Qovery
Agentic Kubernetes resource reclamation is the practice of using an autonomous control plane to continuously identify, suspend, and delete idle infrastructure across a multi-cloud Kubernetes fleet. It replaces manual cleanup and reactive autoscaling with intent-based policies that act on business state, eliminating the configuration drift and cloud waste typical of unmanaged fleets.
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circleci

Building an agentic content production system with Claude Code

Apr 14, 2026 By Ron Powell In CircleCI
This post by an engineer explains how his team uses the.claude folder in Claude Code. The folder is the hidden directory where you store context files, behavioral rules, and automated workflows so Claude understands how to operate in a specific project. He’d set up coding conventions, tool configs, CI integrations. Very engineering-brained. The tool is called Claude Code, so fair enough. I run a web and content team. We write blog posts, tutorials, and technical guides for a living.
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Densify

AI Factories Will Be Won on Efficiency: Why the Kubex + Rafay Partnership Matters

Apr 13, 2026 By Kubex In Densify
The early era for AI was defined by experimentation, standing up isolated environments, and finding the first practical use cases. Today, the conversation is different. Enterprises are no longer asking whether AI matters. They are asking how to scale it sustainably, securely, and economically. That shift is giving rise to the AI factory: a repeatable, governed, production-ready environment where data scientists, platform teams, and application teams can build, train, deploy, and operate AI at scale.
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honeycomb

Optimizing the OpenTelemetry Python SDK for LLM Workloads

Apr 13, 2026 By Alex Boten In Honeycomb
Agentic workloads thrive with precision tooling. Just like developers, they need the rich context, high cardinality, and fast feedback loops that allow them to ask exploratory open-ended questions of their code. But instrumentation is costly, and from the dawn of software, developers have tried to do the most possible with the least amount of resources.
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harness

Your AI Agents Are Only As Good As Your Data | Harness Blog

Apr 13, 2026 By Sunil Gattupalle In Harness
Every agent demo follows the same arc. The agent calls an API. A deployment triggers. A ticket gets created. The audience is impressed. Then someone asks a real question: "Which regions had the highest order failure rate this quarter, and are any of them linked to vendor SLA breaches?" That question crosses four entity types — orders, fulfillment records, vendors, SLA contracts.
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lightrun

Top 6 AI SRE Tools and Why Runtime-Grounded Reliability Is the New Standard

Apr 13, 2026 By Lightrun Team In Lightrun
AI SRE tools accelerate incident detection, root cause analysis, and remediation across distributed production systems. They ingest telemetry signals, including logs, metrics, traces, alerts, and deployment history, to correlate anomalies, narrow fault domains, and reduce manual triage. This guide breaks down the top AI SRE tools in 2026 and helps you choose the right one based on your team’s biggest bottleneck, whether that is faster triage, deeper root cause analysis, or runtime-level validation.
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