Operations | Monitoring | ITSM | DevOps | Cloud

honeycomb

Everything We Talked About at O11yCon 2026

May 27, 2026 By Ken Rimple In Honeycomb
We just wrapped O11yCon 2026, and this year's conversations hit differently. Agent-based software development is here, now. It's no longer an optional choice, and everybody is struggling to understand what their agents are doing and how to make them cost less and perform better. Over the course of fifteen talks, we saw clearly that the old assumptions on how and who (or what) writes our software has been upended. Here are some highlights. We'll have videos available in the near future.
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sentry

You don't need to pick one: how Sentry and OpenTelemetry work together

May 27, 2026 By Lazar Nikolov In Sentry
You already instrumented the backend with OpenTelemetry. Your services emit spans. Your teams know the OTel APIs. Maybe you already run a Collector. So when you start evaluating Sentry, the obvious question is: Do you need to replace your OpenTelemetry setup with the Sentry SDK? No. The practical answer is usually: keep OpenTelemetry where it already works, add the Sentry SDK where it gives you more application context, and send OpenTelemetry Protocol (OTLP) events to Sentry.
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The "Secret" Angle: The Automation Strategy Behind Morgan Sindall Group's IT Success

May 27, 2026 By Ivanti In Ivanti
Morgan Sindall Group is a leading UK construction and regeneration group with a turnover of over £4.1 billion. The group operates through several specialized divisions: They have leveraged Ivanti's solutions—specifically Ivanti Neurons—to modernize their IT service management (ITSM) and asset management. By integrating these tools, they've been able to automate manual processes, improve visibility across their complex infrastructure, and enhance the digital employee experience for their diverse workforce.
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tigera

The AI Agent Accountability Gap: Why Network Policies, API Gateways, And RBAC Are Not Enough

May 27, 2026 By Alister Baroi In Tigera
In The Five Pillars of AI Agent Accountability: A Diagnostic Framework for Engineering Leaders, we walked through each pillar of AI agent accountability (traceability, authorization provenance, identity and ownership, policy at scale, and human oversight) and argued that most enterprises today sit at Level 0 or Level 1 of the Accountability Maturity Model. The most common reaction we get when we share that framework is some version of: “We’re already covered. We have network policies.
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gitkraken

10 Privacy-First Engineering Intelligence Platforms 2026

May 27, 2026 By Jade Nangah In GitKraken
Engineering leaders need more than raw metrics, they need actionable insights they can trust with their data. When evaluating engineering intelligence platforms, privacy controls and centralized repository oversight should top your criteria list. The platforms on this list each offer distinct approaches to tracking DORA metrics, developer productivity, and code quality while keeping your data secure.
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gitkraken

How to Use Git Blame in Your Editor in 6 Steps (2026)

May 27, 2026 By Jade Nangah In GitKraken
Tracking down who made a specific change in your codebase can feel like detective work. Whether you’re debugging an issue or trying to understand why a particular piece of logic exists, knowing the history behind each line is invaluable. GitKraken makes this process simple with tools like GitLens for VS Code and GitKraken Desktop, which bring blame annotations directly into your workflow.
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gitkraken

Healthy PR Lifecycle Time: Benchmarks & Targets (2026)

May 27, 2026 By Jade Nangah In GitKraken
Your pull request has been open for three days. Your reviewer hasn’t commented. You’re starting to wonder if anyone will ever look at it—and whether the code you wrote on Monday still makes sense on Thursday. This feeling is common. PR lifecycle time—the duration from first commit to merged code—directly impacts how quickly you ship features, how fresh your code stays, and how engaged your reviewers remain.
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mezmo

Builder in the loop: Eric Lake on making AURA smarter after every incident

May 27, 2026 By Mezmo In Mezmo
Builder in the Loop is a Mezmo interview series focused on the engineers, product leaders, and operators shaping AURA, an open-source, MCP-native agent harness for production operations. The goal is to get past the polished product layer and talk through the decisions that matter when AI starts interacting with real systems. Key questions include: What should agents be allowed to do? How do they get better over time? Where should humans stay in the loop?
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harness

Bring Your Playwright Suite to Harness: No Rewrites, No Infrastructure, AI-Powered Triage Built In | Harness Blog

May 27, 2026 By Debaditya Chatterjee In Harness
Key Takeaway: Harness AI Test Automation now runs existing Playwright suites without code changes, adds AI-powered failure triage, and integrates test results directly into build and deployment pipelines. ‍
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