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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

speedscale

Diagnose Serial N+1 API Calls With Tempo + proxymock

Aug 11, 2026 By Matt LeRay In Speedscale
One API request took 302 milliseconds. Nothing failed. CPU was mostly idle. The response was correct. The trace made the problem obvious: eight inventory calls, each waiting for the previous one. But the trace could not tell me why the application made eight calls, or whether changing their execution would preserve the response. It showed the shape of the wait, not the input that created it.
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manageengine

Platform engineering is not just a developer trend, but a practice ITOps should be paying attention to

Aug 11, 2026 By Monideepa Mrinal Roy In ManageEngine
Riya has managed IT operations at a mid-sized FinTech company for six years. She knows the infrastructure inside out: Every server, monitoring alert, and compliance requirement is owned by her team. So when Riya heard the engineering lead mention their new internal developer platform in a quarterly review, she assumed her team would be looped in eventually. This did not happen. Three months later, Riya's team was called in to investigate an outage.
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speedscale

The Pod Was Cheaper. The Service Wasn't.

Aug 11, 2026 By Matt LeRay In Speedscale
A smaller Kubernetes pod can lower allocation cost while completing less work. Green status codes and matching schemas can hide it. This walkthrough combines OpenCost allocation data with proxymock behavior and performance evidence. A candidate passes only when behavior and throughput hold while unit cost falls.
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speedscale

Flamegraphs Find It. Replay Proves It.

Aug 11, 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. This walkthrough gives the agent two independent witnesses: Together, they turn AI code verification into an experiment with two independent checks.
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Incident.io

We turned off Pub/Sub and nobody noticed

Aug 11, 2026 By Engineering In Incident.io
Like many modern software stacks, the incident.io platform is predominantly event-driven. For example, whenever you send us an alert, post a message to our agent on Slack, or update an entry in your Catalog - these are all events that then get enqueued on a message topic, meaning any of our downstream components that are interested in that event can subscribe and react asynchronously, such as sending a push notification or posting a reply to you in Slack.
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cortex

DRIVE vs SPACE: What each framework measures and when to use them

Aug 11, 2026 By Ganesh Datta In Cortex
When Nicole Forsgren, Margaret-Anne Storey, and their coauthors published "The SPACE of Developer Productivity" in 2021, they settled an argument the industry had been losing for years. Productivity is not one number, and it is not a proxy like commits or story points. It is multidimensional, and any attempt to flatten it into a single metric will mislead you. Most of what came after in developer productivity measurement builds on SPACE. SPACE and DRIVE were built for different jobs.
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gitkraken

An 80% AI Adoption Rate Is Like an 80% Gym Membership Rate. It Doesn't Prove Anyone Got Stronger.

Aug 11, 2026 By Jade Nangah In GitKraken
Leadership has stopped asking whether your team is using AI. They’re asking what you’re delivering with it. That’s a harder question, because most of the numbers teams have been reporting, adoption rate, seats activated, prompts run, don’t actually answer it.
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upsun

Don't build the autonomous AI factory first

Aug 11, 2026 By Upsun In Upsun
Here's a scene playing out in engineering teams right now. An engineer spends the weekend running four or five coding agents in parallel. Monday morning, a teammate opens their laptop to 53 changed files with 2000+ diffs and a message that says, more or less, "should be good to merge." Nobody asked for this much output. Nobody has time to review it properly. The team doesn't feel faster. It feels ambushed.
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