Operations | Monitoring | ITSM | DevOps | Cloud

How frictionless development created a trillion dollar mistake

We've all heard from an engineering leader about the exact moment they realized their architecture had gotten too complex. It usually happens when they look at a service map and realize it looks like a box of tangled Christmas lights. This cognitive overload is exactly what Steve Evans, the former SVP of engineering at Chegg, reflected on in a recent post on LinkedIn. He argued that microservices were a trillion dollar mistake because we often over-build for future problems that never actually arrive.

End-to-End Tracing with Uptrace: Follow Any Request Across Your Entire System

Stop guessing where requests slow down. With Uptrace, you can follow any request across your entire system and instantly see performance bottlenecks, errors, and latency sources. This video covers: Build real observability, not just dashboards.

Uptrace Tutorial: Dashboards, Percentiles, Heatmaps & OpenTelemetry Metrics

Learn how to use *Uptrace* to measure what truly matters in your applications using percentiles, heatmaps, and histograms—then turn that data into dashboards that answer questions before they’re even asked. In this tutorial, you’ll discover how to: Whether you’re setting up observability for the first time or replacing expensive monitoring tools, this guide shows how Uptrace helps you understand performance, reliability, and user experience — all in one place.

Uptrace Errors & Logs Tutorial: Capture Stacktraces, Context, and Traces in One Place

Every error tells a story — and Uptrace helps you see the full picture. In this tutorial, you’ll learn how to use Uptrace to capture errors, logs, stacktraces, and request context in a single observability platform. See how errors automatically link to traces, understand exactly what happened, and debug issues faster with rich attributes, user data, and performance impact. What you’ll learn: Understand not just *what broke*, but *who it affected and why* — and fix problems with confidence using Uptrace.

Heroku Moves to Sustaining Mode: What It Means and What You Can Do About It

Last week, Heroku announced it is transitioning to a "sustaining engineering model." In plain English: no new features, no new enterprise contracts for new customers, and Salesforce is redirecting its investment elsewhere. The platform will be maintained for security and stability, but that's it. If you've been in this industry long enough, you know what "sustaining mode" means.

The PaaS Graveyard: Why Platforms Keep Dying and Developers Keep Migrating

I've been in this industry since before the word "PaaS" existed. I founded Cloud 66 in 2012 — the same year Heroku was peaking, dotCloud was pivoting to become Docker, and the idea of "just git push and forget about servers" felt like the future. It was the future. Partly. The deployment experience was revolutionary. The business model wasn't. Last week, Heroku announced its transition to "sustaining mode" — no new features, no new enterprise contracts.

Sustainable AI Investment: A Systems Thinking Approach

According to our new report, FinOps in the AI Era: A Critical Recalibration, 40% of companies now spend $10M or more annually on AI. Most can’t tell you if it’s working. That’s not a budgeting problem. It’s a systems problem. And Donella Meadows wrote the playbook for understanding it.

The AI-nigma: FinOps Is Maturing - So Why Is Cloud Efficiency Falling?

Q: What do you call it when FinOps maturity surges but cloud efficiency plummets? A: An AI-nigma. I don’t claim to be a comedian. But I do claim to be Fred FinOps, so the paradoxical findings from CloudZero’s new report titled FinOps in the AI Era: A Critical Recalibration, created in partnership with B2B SaaS benchmarking firm Benchmarkit, had me scratching my head. The good news: These numbers tell a story of cloud cost maturity and control. But then there’s the bad news.

FinOps Maturity Has Never Been Higher. So Why Is Cloud Efficiency Plummeting?

Whoever thought we’d see the day when cloud cost management (CCM) seemed easy? CloudZero just released FinOps In The AI Era: A Critical Recalibration, an annual report on the state of cloud and AI costs. The report surfaced what looks like a paradox: FinOps maturity is accelerating, but organizational cloud efficiency is plummeting. 72% of organizations now have formal cloud cost management (CCM) programs. That’s nearly double what we saw in our last survey (39%).