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2 posts tagged with "industry"

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Media and Streaming Engineering: Building for Peak Load

· 9 min read
Artur Pan
CTO & Co-Founder at PanDev

When Super Bowl LVIII streamed on CBS in 2024, peak concurrent viewers hit 123 million — a number that isn't a KPI, it's a physics problem. Disney+'s Ahsoka finale generated 14 million account logins in a 15-minute window. Netflix's Tyson-Paul fight in late 2024 failed visibly on Twitter because the streaming stack buckled at ~60 million concurrent streams. Media engineering is not optimizing for average throughput. It's optimizing for the one hour per quarter where your graphs go vertical.

The companies that do this well share a specific team shape, a specific release cadence, and a specific set of measurement habits that don't apply to most B2B SaaS. Pulling DORA metrics off a streaming platform and comparing them to a CRM is apples and typhoons. This is a field guide for the engineering leaders who run — or are about to run — a media platform through peak.

Manufacturing Software Engineering: Agile Meets Hardware

· 8 min read
Artur Pan
CTO & Co-Founder at PanDev

A mid-sized automotive supplier I consulted for in 2024 had a production bug land at 03:15 on a Tuesday. The fix took 8 minutes to code and 19 days to deploy — because it required a software update to PLCs on 14 production cells, each of which could only be updated during the 4-minute changeover window between shift batches. The engineering team's average lead time on the office-IT side: 31 hours. On the shop-floor side: 14 days. Same team, same repository, two different universes of delivery constraint.

Manufacturing software engineering is Agile meeting hardware. The practices that work at a SaaS startup — deploy-whenever, feature flags, canary releases — collide with regulated plant-floor reality: OEE targets, changeover costs, OT/IT separation, and production lines that cannot pause for a deploy. A 2023 Deloitte Smart Factory study found 73% of manufacturers cite "IT/OT integration" as the top barrier to digitization. The problem isn't technology; it's that metrics and rituals designed for pure software break when the software touches a physical process.