AWS EKS Anywhere orchestration at scale
At-scale orchestration with AWS EKS Anywhere: how to centralize the management of on-premises clusters and servers using AWS Step Functions, Lambda, and DynamoDB.
SRE
SRE on ThecoreGrid focuses on engineering practices for running reliable, scalable, and observable systems in production.
We cover core Site Reliability Engineering principles, including SLI/SLO design, error budgets, incident management, and operational excellence in highload environments. Topics include monitoring, alerting, automation, capacity planning, and failure handling across distributed systems. We analyze trade-offs between reliability and feature velocity, as well as strategies for reducing toil and improving system resilience. Content is grounded in BigTech practices, including real incident post-mortems and lessons from operating systems at scale. You’ll find deep dives into observability, release engineering, chaos testing, and reliability patterns for cloud-native platforms. Instead of high-level overviews, the SRE tag delivers practical, production-focused insights for SREs, DevOps engineers, platform teams, and architects responsible for maintaining system stability and performance under real-world conditions.
CLASP: scaling serverless stream processing
CLASP for serverless stream processing: why chained requests change worker capacity, how operator placement affects latency, and how state migration keeps state local.
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.
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.
MCPTT under Load: Where Voice Breaks
MCPTT interoperability under high load: how jitter, QoS and carrier boundaries trigger voice failure in dense stadium networks.
LL SC and QHI without loss of efficiency
Randomized LL/SC using FADD: preserving the QHI property, reducing capacity complexity, and ensuring wait-free operation without asymptotic overhead
QoS-aware autoscaling for distributed AI inference
QoS-aware autoscaling for AI inference: distributed scheduling with user devices, lower dedicated capacity, and better tail latency under growth
Graph-based remediation reduces pager alerts in MongoDB
How graph-based remediation automates MongoDB recovery and reduces pager alerts through state machine and pathfinding in a graph
DTMC Planning for URLLC Considering HARQ RTT
DTMC analysis of URLLC with proactive HARQ, accounting for HARQ RTT: How to properly schedule resources and avoid reliability and latency degradation
DNS routing for gRPC eliminates thundering herd
DNS routing for gRPC: how changing the Route 53 policy eliminated the thundering herd and distributed the load across 121 million connections without errors