Operations | Monitoring | ITSM | DevOps | Cloud

Shipped: Allocate AWS cost by account name, not account ID

Until now, allocating by account name meant doing the work yourself: hand-building a custom dimension that mapped every twelve-digit AWS ID to a readable name, then maintaining it by hand in CostFormation. That mapping is fragile. Rename a definition or edit the wrong line and dashboards that depended on it quietly break. Now the account name is built in for accounts connected through AWS CUR 2.0.

Bitbucket Tests now supports tracking tests from multiple branches

Tracking tests on non-default branches was one of the most requested capabilities during the Bitbucket Tests (beta). We heard you, and today, we’re shipping it. Most teams don’t ship from main. Integration happens on develop, stabilisation on staging, releases cut from release. Until now, Bitbucket Tests only tracked the tests from default(main) branch, leaving the branches that actually matter invisible. Multiple branch tracking in Tests changes that.

Build a Docker Monitoring Dashboard in Minutes with Claude MCP + Uptrace

In this video, we use Claude MCP to create and merge Docker container dashboards in Uptrace — directly from the terminal, no manual clicking required. What you'll see: CPU, memory, network, and disk I/O dashboards created with plain text prompts Two dashboards merged into one unified view Dashboard exported as YAML for version control.

3 Things Leaders Must Know About Scaling AI

AI is moving faster than ever, but is your governance keeping up? In this video, Brooke Johnson, Ivanti’s Chief Legal Counsel and SVP of People and Security, breaks down the critical gap between AI adoption and responsible scaling. While speed is rarely the issue, trust and accountability are becoming major roadblocks for IT teams. We explore why nearly 70% of IT pros have witnessed AI hallucinations and how unclear ownership can stall even the most advanced AI initiatives.

Chaos Testing Just Got Easier | New ChaosHub & AI Prompt Library | Resilience Testing | Harness

In this video, we explore two major improvements to the Harness Resilience Testing documentation designed to help you build and manage chaos experiments more efficiently. What's new: ChaosHub Integration AI Prompt Library for Harness MCP These updates make it significantly easier to discover chaos experiments and leverage AI throughout your chaos engineering workflow. If you're using Harness Resilience Testing, this walkthrough will help you get started quickly and make the most of the new documentation experience.

Building a Control Framework for the AI SDLC

Since November, Kosli’s own engineering team has been running a live experiment: what happens to code review when the thing generating the code - and increasingly, the thing reviewing it - is an AI, not a person. Alex Kantor, Kosli’s Director of Technology, walked through that experiment in this webinar: what broke, what it cost to fix, and what four “obvious” assumptions in a standard code review control turned out not to hold once you took the human out of the loop.

Why Internal Agents Must Be Rebuilt with Runtime Context

As we entered 2026, enterprises raced to build internal AI engineering agents, automating incident response, code review, and support. The investment was real, but 88% of these pilots never reached production, and teams are now in rebuild mode, trying to understand why. Live runtime validation was the key architectural decision skipped in these v1 agents and it’s still missing from many v2 designs. Agents need to verify their reasoning against production before they act.