Kubernetes 1.37 Native Histograms: Prometheus Migration Guide
Enable Kubernetes 1.37 native histograms safely, configure Prometheus 3, migrate queries and dashboards, and validate observability cost and accuracy.
84 articles
Enable Kubernetes 1.37 native histograms safely, configure Prometheus 3, migrate queries and dashboards, and validate observability cost and accuracy.
SigNoz, Uptrace, and Highlight compared for self-hosted, open-source observability in 2026 — OpenTelemetry-native design, self-hosting complexity, and which fits teams wanting full data control without Grafana's stack sprawl.
Alert fatigue is a data problem before it's a culture problem — most teams have never actually measured which alerts fire often and get dismissed. Build a tool that analyzes historical alert-to-resolution patterns with Claude API and recommends specific tuning, not generic advice.
A single LLM call struggles to reason over a trace spanning 40 microservices. Multi-agent systems — one agent per service domain, coordinated by an orchestrator — are emerging as the pattern for root-causing failures in genuinely large distributed traces.
Sentry, Bugsnag, and Rollbar compared for application error tracking in 2026 — issue grouping accuracy, release health tracking, source map handling, and which fits your team's debugging workflow and budget.
Honeycomb, Grafana Cloud, and Chronosphere compared for 2026 — high-cardinality trace analysis, cost predictability at scale, and which observability platform fits your team's actual debugging workflow.
OpenTelemetry Collector, Vector, and Fluent Bit compared for log and telemetry pipelines in 2026 — performance, protocol support, transform capability, resource footprint, and which to pick for your observability stack.
Datadog, New Relic, and Dynatrace compared on pricing, Kubernetes monitoring, distributed tracing, AI features, and total cost of ownership. Honest verdict for DevOps and SRE teams choosing an APM in 2026.
Prometheus vs VictoriaMetrics compared on what actually matters: resource usage, query performance, long-term storage, cardinality limits, Grafana compatibility, and total cost of ownership for teams running at scale.
Build a production-ready log pattern classifier using Claude API that automatically categorizes log lines into errors, warnings, anomalies, and noise — saving on-call engineers hours of manual log triage.
How to add OpenTelemetry tracing to LLM applications in production — instrumenting Anthropic SDK calls, tracking token usage and latency, connecting LLM traces to your existing observability stack.
A practical comparison of Prometheus and VictoriaMetrics for production monitoring in 2026 — covering resource usage, query performance, cardinality handling, and when to migrate.
eBPF explained simply — what it is, how it works, why it is changing networking and observability in Kubernetes, and the tools built on top of it that you are probably already using.
An honest, hands-on comparison of Datadog vs Grafana Cloud for DevOps teams in 2026 — covering cost, features, ease of setup, alerting, and when each platform makes sense. No marketing fluff.
Comparing Grafana Loki, AWS CloudWatch Logs, and Datadog Logs on cost, query language, integrations, and alerting. Which log management platform fits your team in 2026?
Honest hands-on review of groundcover — the eBPF-based Kubernetes observability platform. What you get out of the box, how it compares to Datadog and Dynatrace, real limitations, and a final verdict.
Detailed comparison of Prometheus Operator and VictoriaMetrics Operator for Kubernetes monitoring — resource usage, CRDs, HA setup, Grafana compatibility, and when to switch.
Fix Grafana panels stuck on 'No data' or spinning forever. Covers datasource issues, time range mismatches, variable resolution failures, Prometheus scrape interval mismatches, and broken panel JSON.
An honest hands-on review of Netdata in 2026 — real-time 1-second metrics, auto-discovery, Netdata Cloud vs self-hosted, resource usage, alerting, and how it compares to Prometheus + Grafana for DevOps teams.
Prometheus pulls metrics by default. The Pushgateway lets short-lived jobs push metrics. Here's exactly when each model fits and when you should NOT use Pushgateway.
Serving vision-enabled LLMs (Claude Vision, GPT-4V) in production requires different patterns from text-only models. Here's how to handle images, latency, and cost at scale.
Prometheus doesn't scale to multi-cluster, long-term storage on its own. Compare Victoria Metrics, Thanos, and Cortex to pick the right solution for your scale.
How to safely test new LLM models and prompts in production using A/B testing, shadow mode, and traffic splitting — without risking user experience.
SRE teams talk about SLOs, SLIs, and error budgets constantly, but the terms get used loosely. Here's what each one actually means, with real numbers, and how they connect to decide when to ship vs slow down.
Consumer lag climbing and you don't know why? Here's a step-by-step way to find whether it's slow processing, rebalancing storms, or partition skew — and how to actually fix each cause.
Your logs have the answers — but there are too many to read. Build an AI anomaly detector that queries Loki for unusual patterns and uses Claude API to explain what's wrong and what to do.
Everyone says 'observability' now but most teams are still just doing monitoring. Here's what actually separates the two — and why it matters when your system breaks in a way you didn't expect.
CI/CD tests tell you your code works in a test environment. Continuous Verification tells you your code works in production, on real traffic, right now. Here's the methodology, the tools, and why it's becoming the standard for mature engineering teams.
You created a silence in AlertManager but alerts are still firing. Here are the 6 most common reasons silences fail and exactly how to fix each one.
Three serious continuous profiling tools, one decision to make. Here's an honest comparison of Pyroscope, Parca, and Grafana Pyroscope — performance, ecosystem, storage, and which one your team should actually use.
Continuous profiling tells you exactly which function is burning your CPU or leaking memory — in production, all the time. Here's what it is, how it works, and how to set it up with Pyroscope.
LLMs degrade silently. Here's how to build a weekly eval pipeline using Claude Haiku as an LLM judge, SQLite for score tracking, and GitHub Actions to alert on quality drops.
Build a tool that takes PagerDuty incident data, Slack messages, and system metrics and generates a structured blameless postmortem — timeline, root cause, action items — in minutes instead of days.
LLMs in production face real security threats: prompt injection, jailbreaks, sensitive data leakage, and SSRF via tool calls. Learn the attacks and defenses for production AI systems.
Not every LLM problem needs fine-tuning. Understand when prompt engineering is enough, when to use RAG for knowledge, and when fine-tuning actually makes sense — with real decision criteria.
Prometheus shows your target as DOWN in the Targets page. Here's every reason a scrape target goes down and exactly how to debug and fix each one.
Build an SLO breach predictor that reads error budget burn rate from Prometheus, uses Claude to analyze patterns, and sends Slack alerts before SLOs breach — not after.
Build production-ready LLM agents with LangGraph and Claude API — tool calling, persistent memory with Redis, multi-agent orchestration, and Kubernetes deployment patterns.
Choosing a log storage backend? Elasticsearch, OpenSearch, and Grafana Loki have very different architectures, costs, and use cases. Here's the honest comparison with Kubernetes examples.
Building a RAG system that actually works in production requires the right chunking strategy, embedding model, and retrieval tuning. Here's what works, what doesn't, and real configuration examples.
Choosing a log collector for Kubernetes? Fluent Bit, Fluentd, and Vector each handle log collection differently. Here's the practical comparison with resource usage and config examples.
Implement LLM streaming with FastAPI and Anthropic SDK using Server-Sent Events and WebSockets. Real code with token buffering, error handling, and Kubernetes deployment.
Running LLMs in production without observability is flying blind. Here's how to instrument your LLM calls with OpenTelemetry to track traces, costs, latency, and quality metrics.
Chaos engineering sounds like deliberately breaking things. It is — but in a controlled way that makes your systems stronger. Here's what it is, how it works, and how to start.
Choosing a distributed tracing backend? Grafana Tempo, Jaeger, and Zipkin all solve the same problem differently. Here's which one to pick and why.
Build an AI assistant that reads PagerDuty alerts, fetches related runbooks, and generates a first-response action plan — so your on-call engineer doesn't start from zero at 3am.
OpenTelemetry (OTel) is the open standard for collecting traces, metrics, and logs. Learn what it is, why it matters, and how to start using it.
Choosing an on-call and incident management platform in 2026. PagerDuty, Opsgenie, and VictorOps (Splunk On-Call) all route alerts and manage on-call rotations. Here's what actually differentiates them.
Track your error budget automatically and get AI-generated burn rate alerts and incident summaries. Build a real SLO monitoring tool with Python, Prometheus, and Claude API.
Redis changed its license to BUSL in 2024 and Valkey forked it. Meanwhile Dragonfly and KeyDB offer multi-threaded alternatives. Here's a full comparison — performance, licensing, features, and when to choose each.
Manual runbooks go stale. Build a system that watches your Kubernetes cluster, detects incidents, and generates step-by-step runbooks automatically using LLMs. Full implementation with Python, kubectl, and Ollama.
OpenSearch forked from Elasticsearch in 2021 when AWS and Elastic had a licensing dispute. In 2026, both have evolved significantly. Here's a full comparison — features, licensing, performance, managed services, and which one to pick.
Tired of noisy Grafana alerts that wake you up for nothing? Build an AI layer that classifies incoming alerts as actionable or noise, enriches them with context, and routes them intelligently — using Claude or GPT-4 as the reasoning engine.
Prometheus is crashing with OOMKilled or running out of memory. The culprit is almost always high cardinality metrics — labels with thousands of unique values. Here's how to find which metrics are killing your Prometheus and exactly how to fix it.
Datadog dashboards show no data, hosts appear offline, or custom metrics aren't showing up. Here's how to systematically diagnose and fix Datadog agent issues on Kubernetes and VMs.
Three popular log forwarding agents, three very different use cases. Here's the practical comparison with memory usage, performance, and a clear recommendation for each scenario.
Datadog and Splunk are both enterprise observability platforms but serve different strengths. Here's the honest comparison — pricing, use cases, and which one to choose.
Grafana Alloy and the OTel Collector both collect and forward observability data. But they have different strengths. Here's when to use each.
Deploy Langfuse on Kubernetes to get complete tracing, cost tracking, and evaluation for your LLM applications. Step-by-step guide with Helm charts, Postgres, ClickHouse, and production configuration.
Linkerd vs Istio head-to-head comparison — performance, complexity, features, and which one to pick for your Kubernetes setup in 2026.
Grafana vs Kibana vs Datadog — a practical comparison of features, cost, and when to use each. Stop guessing and pick the right observability tool for your team.
Your Prometheus /targets page shows red. Services are running but Prometheus can't scrape them. Here's every reason this happens — wrong port, NetworkPolicy blocks, ServiceMonitor label mismatch, auth — and exactly how to fix each one.
Grafana Loki and the ELK Stack (Elasticsearch, Logstash, Kibana) are the two most popular log management solutions. Here's a detailed comparison to help you choose the right one.
Observability explained in plain English — what it means, how it's different from monitoring, the three pillars (metrics, logs, traces), and why every DevOps engineer needs to understand it.
Step-by-step project walkthrough: set up Prometheus, Grafana, Loki, and AlertManager on Kubernetes using Helm. Real configs, real dashboards, production-ready.
Static alerts miss 40% of real incidents. Learn how AI and ML-based anomaly detection — using tools like Prometheus + ML, Dynatrace, and custom LLM runbooks — catches what thresholds can't.
A real comparison of the three most popular monitoring tools — what they're actually good at, where they fall short, and which one fits your team's situation.
Service mesh sounds complicated but the concept is simple. Here's what it actually does, why teams use it, and whether you need one — explained without the buzzwords.
Step-by-step guide to setting up Prometheus Alertmanager for Kubernetes monitoring. Covers installation, alert rules, routing, Slack/PagerDuty integration, silencing, and production best practices.
Everything you need to know about Kubernetes VPA. Covers installation, recommendation modes, right-sizing strategies, VPA vs HPA, and production best practices for resource optimization.
LLMs are now analyzing logs, correlating alerts, and executing runbook steps autonomously. Learn how AI-powered incident response works, the tools available, and how DevOps engineers should prepare.
How to use LLMs and AI tools for intelligent log analysis in DevOps. Covers practical workflows, open-source tools, prompt engineering for logs, and building custom log analysis agents.
Everything you need to know about Cilium, the eBPF-powered CNI for Kubernetes. Covers architecture, installation, network policies, observability with Hubble, and replacing kube-proxy.
How LLMs and AI are transforming log analysis, anomaly detection, and root cause analysis — and the tools DevOps engineers should know about in 2026.
Step-by-step guide to setting up Grafana's machine learning features for anomaly detection, predictive alerting, and intelligent noise reduction. Stop alert fatigue with AI.
60% of enterprises now use AIOps self-healing. 83% of alerts auto-resolve without humans. The era of 2 AM PagerDuty wake-ups is ending. Here's what replaces it.
The definitive comparison of AIOps tools in 2026. Datadog AI, Moogsoft, PagerDuty AIOps, BigPanda, and more — features, pricing, and which one fits your team.
AI agents are moving beyond alerting into autonomous incident detection, root cause analysis, and remediation. Here's why Agentic SRE will fundamentally change how we handle production incidents.
AWS CloudWatch is the central monitoring service for everything running on AWS. This guide covers metrics, logs, alarms, dashboards, Container Insights, and production best practices.
Chaos engineering is moving from Netflix-scale novelty to expected practice at any serious engineering team. Here's why it will be as normal as unit tests within three years.
Grafana Loki is the Prometheus-inspired log aggregation system built for Kubernetes. This guide covers architecture, installation, LogQL queries, and production best practices.
Istio and Linkerd are powerful but heavy. eBPF-based networking is changing the game. Here's why I think the sidecar proxy era is ending.
OpenTelemetry is becoming the default observability standard, replacing vendor-specific agents. This guide covers what it is, how traces/metrics/logs work, and how to instrument a Node.js app end-to-end.
Learn how to set up Prometheus and Grafana from scratch in 2026. Covers metrics collection, PromQL queries, alerting rules, Alertmanager, Grafana dashboards, and Kubernetes monitoring with kube-prometheus-stack.