The Giant Swarm Blog
We publish when we have something to say - insights we believe in, lessons we've learned, and ideas that might just help you build better.
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Team6 lessons learned from 6 years of building relationships with events
I've been managing relationships and organizing events at Giant Swarm for six years now. The two are more connected than the job title might suggest. The events…
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ProductOverwhelmed by scale: how product thinking fixes platform teams
Most platform engineering stories start with success. A small team builds something useful, leadership notices, and suddenly that team is everyone's platform te…
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TeamWhy we stopped gatekeeping our personal development budget
This year I'm spending my personal development budget on Thai lessons, therapy, and a scooter safety course. I'm not sure all three of those would have passed t…
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InsideThe best AI agent is the one that disappears
Here's something most AI vendors won't tell you: the goal shouldn't be to run more AI. It should be to run less — eventually. I know that sounds strange coming …
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InsideAI agents that run where your data lives
There's a pattern I keep seeing in enterprise AI conversations. Someone shows an impressive demo — an agent that analyzes logs, responds to incidents, or automa…
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TechYour platform team can't build great templates while running around fixing clusters
Most platform teams know exactly what they should be building: the templates and self-service workflows that let developers go from idea to running service with…
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InsideSee everything, own your data: the Giant Swarm Observability Platform
Most platform teams have an observability stack. Few would call it finished. You start with metrics, bolt on logging, realize you need traces, wire up alerting …
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InsideInfrastructure for AI is finally getting a standard
Over the past year, AI has exploded into production, from experimental models to customer-facing apps and internal copilots. But while the models evolved fast, …
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InsideWhy Giant Swarm isn’t “Just Ops”
There’s a quiet shift happening in how companies think about infrastructure. For a long time, running Kubernetes clusters — patching, monitoring, scaling — was …