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.
DNS round-robin stops working under load when clients start caching responses. Agoda faced this issue at the object storage level and moved the balancing to a separate layer. The problem manifested during the increase in data workloads. S3-compatible endpoints used DNS round-robin to distribute traffic. In practice, clients cached DNS responses and continued to hit … Read more
Request timeouts do not always indicate a problem in the database. Often, degradation is hidden in the path between the application and the DB. The problem manifests when database metrics appear stable, but clients experience timeouts. At the observation level, this looks like a contradiction: latency increases while database time remains the same. The reason … Read more
The profiler in kernel space only sees addresses. Useful insights emerge only after symbolization—and in Go, this stage is structured differently than in other languages. The problem arises when the profile has already been collected, but it cannot be interpreted. The eBPF profiler captures stack traces at the kernel level and obtains a set of … Read more
When LLM becomes part of production infrastructure, traditional monitoring is no longer sufficient. The bottleneck is no longer the application code, but the routing and model selection layer — and that’s exactly where observability is needed. In LLM systems, degradation doesn’t start with HTTP endpoint failures, but with the accumulation of subtle effects: increased latency … Read more
The coregrid Radar is a weekly column where we curate key architectural insights and major releases. No need to search across multiple sources — everything in one place.
AI agents complicate observability: the same request can lead to different chains of actions. Without tracing, the system becomes opaque. The problem manifests when generative systems transition from simple LLM calls to agents. An agent plans steps, invokes tools, and makes decisions dynamically. Behavior becomes non-deterministic: the same prompt can result in different call sequences … Read more
Controls: ← → to move, ↑ to rotate, ↓ to drop.
Mobile: use buttons below.