Operations | Monitoring | ITSM | DevOps | Cloud

speedscale

Flamegraphs Find It. Replay Proves It.

Jul 31, 2026 By Matt LeRay In Speedscale
I made an API endpoint 13 times faster. Then I realized my first verification only checked the status, headers, and response schema. I had not checked the totals. I had made the bug faster. That is the problem with giving an AI coding agent one kind of evidence. A CPU profile can show where the application is slow, but not whether an optimization preserves behavior. A traffic replay can prove that behavior stayed stable, but not explain why the code burns CPU.
Read Post
Why More UK Firms are Turning to Colocation for their AI Workloads

Why More UK Firms are Turning to Colocation for their AI Workloads

Jul 31, 2026 By OpsMatters In Pulsant
The last few years have seen AI conversations dominated by the need for investment in hyperscale infrastructure as firms race to build ever larger training models. But as those conversations evolve, the emphasis is shifting to the next phase of AI adoption, focusing on the scaling of use cases and real-world value.
Read Post
upsun

Software is a team sport. Most AI tools forgot that.

Jul 31, 2026 By Upsun In Upsun
Every AI coding tool ships the same promise: your developers, faster. Autocomplete in the IDE, agents in the terminal, a working prototype before lunch. And it delivers, at least for the person holding the keyboard. The problem is that most of what it takes to ship software was never a solo activity, and that is the part the market keeps skipping.
Read Post
megaport

Megaport Signs Open Weights and American AI Leadership Letter

Jul 31, 2026 By Megaport In Megaport
Megaport has signed the Open Weights and American AI Leadership letter, supporting open-weight AI, customer choice, and the infrastructure that powers AI innovation. Artificial intelligence is reshaping how organizations build, deploy, and scale digital infrastructure. As AI adoption accelerates, the conversation is evolving beyond model performance alone to the broader ecosystem needed to support long-term innovation.
Read Post
elastic

Closing the AI gap: How next-generation knowledge access unlocks mission outcomes for government

Jul 31, 2026 By Oksana Abramovych In Elastic
A recent IDC Spotlight report based on a survey of 685 public sector respondents found that 72% describe scaling AI from pilot to production as "very" or "somewhat" difficult.¹ Choosing the right model is only part of the challenge. Agencies also need to get their data ready for AI.
Read Post

Agent Observability Deep Dive Demo | Grafana Cloud

Jul 31, 2026 By Grafana In Grafana
Grafana AI Observability is our new database and platform for observing AI Agents. Over the past year at Grafana Labs, we built Agents and we needed a way to understand how they are performing, what are the costs associated with them, what's the error rate or time to the first token as well as how they are behaving. Grafana Staff Engineer, Ivana Hučková provides a deep dive demo on how Grafana AI Observability connects our experience building Agents with our experience building observability systems.
View Video
gitkraken

Kepler Is in Public Preview: One Task, Every Repo, Every Agent

Jul 31, 2026 By Jade Nangah In GitKraken
A faster car doesn’t get you home faster if the freeway is still jammed. That is the problem most teams run into once they add a second, third, or fourth AI coding agent to the mix. More agents generate more code. They do not automatically generate more finished work, because someone still has to track which agent is waiting on input, which one just opened a pull request, and which one has been quietly stuck for twenty minutes. Kepler is GitKraken’s answer to that traffic jam.
Read Post
cloudzero

LLM cost optimization: 7 strategies to cut inference spend

Jul 31, 2026 By Lyne Carolyne In CloudZero
LLM cost optimization is the practice of cutting what you spend on large language models, mostly inference, without losing the quality that makes the AI worth running. The biggest levers are routing requests to cheaper models, caching repeated tokens, batching anything that can wait, trimming prompts, right-sizing models, cutting calls you do not need, and putting one gateway and cost view in front of all of it.
Read Post

Copyright © 2026 OpsMatters™. All rights reserved.