LLM evaluation at scale on Apache Spark
LLM evaluation at scale on Apache Spark: how the distributed architecture, caching, and statistical validation of models are structured.
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.
Golden path platform without implementation traps
Why the golden path platform fails during implementation: an analysis of errors, templates, and metrics that truly show results.
LLM Agents for B2G Co-Simulation of Energy Systems
How LLM agents automate building-grid co-simulation through DAG and multi-agent orchestration, reducing errors and complexity in pipelines.
Platform health through the lens of developer experience
How to measure platform health through developer experience, adoption, and toil, not just observability and uptime.
Knowledge Graph for TAM through LLM and LangExtract
How Knowledge Graph and LangExtract enhance data extraction accuracy and traceability in Total Airport Management systems –>
Observability: When Security Intercepts Traffic Before the Application
Sometimes the system “breaks” even before entering the application. This case is about how the security layer completely obscures the behavior of the backend. Observability
Platform engineering metrics without telemetry
Platform engineering metrics without a baseline deprive teams of control. An analysis of the approach using the Kubernetes Secrets Manager and scorecard model.
Edge AI on Kubernetes without Loss of Consistency
Edge AI Kubernetes as a unified platform: how to scale the edge without fragmentation and maintain control over distributed infrastructure.
Mid-path Network Analysis through A/B Route Comparison
Mid-path network analysis through A/B comparison reveals bottlenecks in interconnection, hidden behind traditional metrics of latency and throughput.
Edge error handling without failure data
Edge error handling: why CDN failures without logs block diagnostics and how to build observability for analyzing such incidents