controller
3 stories filed under controller on Beyond Market Intelligence. The newest of them: “Scale Your Self-Hosted Runners with ARC's Latest Reliability Upgrades”, “How Uber Gives Multiple Orchestrators Control Over Scaling Without Conflict”, and “When the Loop Has No Brain, the Architecture Speaks for Itself”. For teams managing their own CI infrastructure, ARC 0.15.0 brings meaningful improvements to how self-hosted runners operate on Kubernetes. Uber has solved a tricky Kubernetes problem by separating scaling intent from execution. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every controller story on Beyond Market Intelligence, newest first.
Scale Your Self-Hosted Runners with ARC's Latest Reliability Upgrades
For teams managing their own CI infrastructure, ARC 0.15.0 brings meaningful improvements to how self-hosted runners operate on Kubernetes. The focus on reliability and observability means less time troubleshooting infrastructure and more time shipping code. This release respects that scaling compute shouldn't introduce complexity. For those exploring how AI infrastructure scales independently, our coverage of Tenstorrent's recent funding offers a complementary look at building trust in open-source foundations.
How Uber Gives Multiple Orchestrators Control Over Scaling Without Conflict
Uber has solved a tricky Kubernetes problem by separating scaling intent from execution. Its new ServiceScale controller lets multiple orchestrators manage the same workloads without stepping on each other, critical for regional failover without idle capacity. Engineers Egor Grishechko and Srikar Paruchuru explain how. It's a practical, human-centered approach to infrastructure that prioritizes outcomes over complexity. For more on how major platforms rethink their tech stacks, see Cloudflare's blog on migrating to EmDash.
When the Loop Has No Brain, the Architecture Speaks for Itself
Most discussions of loop engineering assume an LLM sits at the center of the loop. This experiment challenges that by removing the model entirely, using a deterministic, zero-dependency Python benchmark to isolate the architecture itself. The author tested whether a goal-directed controller could isolate failures better than a linear pipeline, validating it across 300 random seeds. The results are narrow but compelling: failure isolation is a measurable property of control flow, independent of reasoning.