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cloudzero

Shipped: Put every AI task on the cheapest model that can actually do it

Aug 3, 2026 By Djo Lopez In CloudZero
If your team builds with AI, someone is defaulting to the biggest model available (say, Fable) because it feels like the safe pick, and the safe pick is almost always the most expensive one. One over-powered choice looks harmless on its own, but multiplied across every prompt, agent, and workflow, and you get a big number on the P&L. All that, yet nobody chose which model on purpose. As we like to say, using a default is not a decision.
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Your AI agents don't need better models. They need the same context.

Aug 3, 2026 By Upsun In Upsun
Everyone on the team has good coding agents. That is not what made the team fast. The shared repo, the shared docs, and a glossary nobody is allowed to drift from did more than any model choice. In this Product Highlights conversation, Patrick Dawkins, a principal engineer at Upsun who is building Upsun Dispatch under a hard deadline, explains what his team changed to sustain that pace. His take: "As well as the team all having access to the same things and the same vocabulary, all the agents also have access to those docs.".
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upsun

Migration playbook: escaping lock-in without disruption

Aug 3, 2026 By Upsun In Upsun
Migration projects fail in a predictable sequence. The technical work gets scoped. The timeline gets set. The engineering team starts moving workloads. Somewhere in the middle, dependencies surface that weren't in the original assessment, the double-run period extends beyond the budget allocated for it, and the project either stalls or completes at significantly higher cost than planned.
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pagerly

Cloud Outage Response: Lessons From July 2026

Aug 2, 2026 By Falit Jain In Pagerly
Cloud outage response got a brutal stress test in July 2026. In the span of nine days, three separate cloud infrastructure failures took large chunks of the internet offline: AWS CloudFront on July 16, Microsoft Azure West US on July 23, and AWS us-west-2 on July 24. None of them were caused by a dramatic data center fire or a nation state attack. They were routing faults, configuration translation bugs, and a piece of networking hardware on the path between a region and a metro area.
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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.
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pagerly

Cloud Outage Preparedness: On-Call Lessons for 2026

Jul 31, 2026 By Falit Jain In Pagerly
Cloud outage preparedness stopped being a nice-to-have this month. In a span of roughly 48 hours, Microsoft Azure lost a big chunk of its West US footprint and Amazon Web Services dropped connectivity between its us-west-2 region in Oregon and the Seattle metro. The AWS event alone rippled outward and knocked DoorDash, Reddit, Hulu, Apple Pay, Snapchat, Fortnite, and the PlayStation Network offline for millions of users, according to incident trackers. Neither outage was caused by anything exotic.
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pagerly

Cloud Outage Incident Response: Lessons From 2026

Jul 31, 2026 By Falit Jain In Pagerly
Cloud outage incident response stopped being a hypothetical exercise this summer. In a single stretch of July 2026, three of the biggest cloud providers stumbled in quick succession, and the ripple effects reached apps that millions of people use every day. If your team runs anything on a hyperscaler, the events of the last few weeks are a direct message: the question is no longer whether your provider will have a bad day, but whether your on-call rotation is ready when it does.
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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.
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cloudzero

What is FP&A? Financial planning and analysis in the AI spend era

Jul 31, 2026 By Lyne Carolyne In CloudZero
FP&A stands for financial planning and analysis. It is the corporate finance function responsible for budgeting, forecasting, variance analysis, and decision support. If you're asking what is FP&A in practice: FP&A teams build the annual operating plan, project revenue and expenses, explain gaps between plan and actuals, and give leadership the numbers behind strategic decisions. Accounting reports what happened. FP&A models what happens next.
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