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GitHub Spark is shutting down August 31 — export code now and replace broken `llm()` calls

GitHub Spark stops being available to existing users on August 31, 2026. Deployed apps are meant to keep running, but owners should export code to a repository now; Spark apps using `llm()` need a separate inference provider because the underlying GitHub Models service retired July 30.

GitHub Actions is starting runtime brownouts for outdated self-hosted runners

Teams with pinned, custom-image or auto-update-disabled GitHub Actions runners can now see registration or job execution fail before the September 25 cutoff. The migration is not just a one-time jump to v2.329.0: already-registered runners must also stay within 30 days of the latest runner release.

Google Cloud is making every Application Integration run execute under an explicit identity

The migration turns integration identity from an implicit platform detail into an operational dependency. Teams may need new run-as accounts and `Service Account User` grants not only for runtimes but also for editors, publishers, approvers and deployment automation.

Railway has stopped new services adopting Config as Code ahead of the December 1 hard cutoff

The August 28 transition is now active, and Railway’s current documentation removes an earlier ambiguity about new services in existing projects. Config as Code is legacy-only from here; production users should migrate and validate `.railway/railway.ts` before the December hard cutoff.

Cerebras CS-4 turns Nexus into a multi-generation rack-scale inference platform

CS-4 combines three WSE-3 Turbo wafers with Cerebras’ Nexus rack design. The practical shift is architectural: compute, power and I/O become modular, while Cerebras now says the same platform is intended to support CS-5 in 2027 and a 3D-memory CS-6 generation after that.

AWS Security Agent can now hard-cap autonomous pentest spend and revalidate individual fixes

AWS’s agentic pentesting service can run multiple security tasks in parallel, so billable task-hours may exceed wall-clock test duration. New per-run task-hour limits stop a test gracefully at the ceiling and preserve findings, while targeted revalidation checks specific fixes without rerunning the entire pentest.

Google is adding hard spend caps and commitment pricing for AI agent workloads

Google’s new agent FinOps model combines hard monthly spend caps that pause agent API calls, Flexible Savings Plans with one- or three-year commitments, pay-as-you-go Gemini Enterprise usage and planned deferred execution at up to half normal inference cost. The controls are useful, but commitment economics and task eligibility need to be modeled carefully.