MetaRoCE and Ethernet for AI Infrastructure
MetaRoCE for AI Infrastructure: How Offloading Intelligence to the NIC Helps Ethernet Maintain Throughput, Low Tail Latency, and Graceful Recovery.
Observability
Observability on ThecoreGrid focuses on understanding, monitoring, and debugging complex distributed systems in production.
We cover logging, metrics, tracing, and profiling as core pillars for gaining visibility into system behavior under real workloads. Topics include instrumentation strategies, telemetry pipelines, alerting design, SLI/SLO definition, and incident detection in highload environments. We analyze trade-offs between signal quality, cost, and system overhead, along with challenges of cardinality, sampling, and data retention. Content is grounded in BigTech practices, including incident post-mortems and lessons from operating large-scale systems. You’ll find deep dives into modern observability stacks, correlation techniques, and debugging methodologies for microservices and cloud-native platforms. Instead of tool-focused tutorials, the Observability tag delivers engineering insights for SREs, platform teams, backend engineers, and architects responsible for system reliability, performance, and operational transparency.
POWERSLIDER: dynamic power cap for LLM serving
Dynamic power caps for LLM serving: how POWERSLIDER distributes power across stages, maintains goodput, and withstands grid demand response.
MetaRoCE for AI Infrastructure on Ethernet
MetaRoCE for Ethernet-based AI infrastructure: how Meta moves intelligence into the NIC, eliminates PFC, and creates a loss-resilient transport for million-GPU scale.
Alloy central gateway: how to avoid dropping the telemetry stream
A central gateway for full telemetry: sizing, load testing, HPA, WAL, and GOMEMLIMIT in a production scenario—with no blind spots.
Automated RCA in microservices at Atlassian
Automated RCA in microservices turns metrics, logs, and traces into ranked root cause hypotheses for faster incident validation and cleaner diagnosis
AWS Aurora and DynamoDB for AI Context
Data replication for AI agents: how Aurora, DynamoDB, and Keyspaces help avoid stale reads, race conditions, and context errors.
Git fetch in CI: how Datadog alleviated CPU from a bottleneck
Git fetch in CI became a bottleneck. An analysis of the gitretriever architecture at Datadog, CPU reductions, relay models, and APIs for code queries.
Container security Swift: zero-touch on hundreds of clusters
Container security at Swift: how zero-touch automation, central scanning, and regression testing reduced noise and simplified protection for hundreds of clusters.
eBPF for AI API: control without code changes
eBPF for AI API in Kubernetes: how to intercept traffic, limit AI agents, and control behavior without code changes and container restarts.
Swift container security without manual noise
Container security at Swift: how centralized architecture, automated scans, and regression testing reduced manual noise in hybrid cloud.