AI compute infrastructure Stargate how to scale 10GW
AI compute infrastructure as the foundation for scaling models. An analysis of Stargate, architecture, partnerships, and growth constraints.
Architecture and Infra
Architecture and Infra on ThecoreGrid covers the foundations of designing and operating scalable, reliable systems at BigTech level. This category brings together system design and infrastructure practices: distributed architectures, highload patterns, cloud-native platforms, and core layers such as compute, networking, and storage. We focus on real engineering decisions — how to balance reliability, performance, cost, and long-term system evolution. Topics include Infrastructure as Code, Kubernetes, multi-region deployments, traffic management, and platform design. Content is grounded in production experience: incident post-mortems, large-scale migrations, and lessons from operating infrastructure under heavy load. Instead of abstract theory, you get practical trade-offs, proven patterns, and insights drawn from real-world systems. Architecture & Infra is built for architects, backend and platform engineers, DevOps teams, and SREs responsible for complex distributed systems and mission-critical infrastructure.
HSM vault for E2E backup without trust in the platform
HSM backup vault enhances end-to-end encryption for backups. The architecture eliminates platform access to keys and introduces verifiable trust. The problem arises when backups leave the device and enter the cloud. Even with end-to-end encryption, the question remains: who controls the recovery keys and how can it be proven that the provider does not have … Read more
Security of AI Agents in Kubernetes through Jobs
Security of AI agents in Kubernetes: why Jobs and Vault change the model of isolation, secrets, and trust in dynamic workloads.
CDN error handling under edge failure pressure
CDN error handling: why edge errors lose context and how to architecturally prepare for failures at the CDN level.
BYOC Logs: Scalable Log Storage
BYOC Logs are transforming log management: storing data in your own infrastructure while enabling unified observability without sacrificing control or scalability
KV cache restoration acceleration through 3D parallelism
KV cache restoration in LLM serving: how 3D parallelism reduces TTFT and eliminates bottlenecks in compute and I/O. –>
Kubernetes controller staleness cache control
How Kubernetes controller staleness affects system behavior and how version 1.36 addresses the issue through AtomicFIFO and resource version control
Grafana observability dashboards: flexible customization
Grafana observability dashboards: how to configure services and perform drill-down analysis without leaving the application, while reducing observability fragmentation
Adaptive microservice management under dynamics
Adaptive microservice management in cloud-native systems: how load dynamics, network, and dependencies affect autoscaling and management architecture
SFC for split learning reduces latency
How optimizing split learning through SFC reduces latency in distributed AI by jointly managing placement and routing