{"id":37658,"date":"2024-09-19T10:30:00","date_gmt":"2024-09-19T08:30:00","guid":{"rendered":"https:\/\/www.cloudmagazin.com\/2026\/04\/26\/cloud-native-observability-from-metrics-to-logs-to-traces\/"},"modified":"2026-06-10T12:59:29","modified_gmt":"2026-06-10T10:59:29","slug":"cloud-native-observability-from-metrics-to-logs-to-traces","status":"publish","type":"post","link":"https:\/\/www.cloudmagazin.com\/en\/2024\/09\/19\/cloud-native-observability-from-metrics-to-logs-to-traces\/","title":{"rendered":"Cloud-native Observability: From Metrics to Logs to Traces"},"content":{"rendered":"<p style=\"color:#6190a9;font-size:0.9em;margin:0 0 16px;padding:0;\">3 Min read<\/p>\n<h2>Key Takeaways<\/h2>\n<ul>\n<li>Observability goes beyond monitoring: not just detecting known issues, but understanding unknown ones.<\/li>\n<li>The three signal types\u2014metrics, logs, and traces\u2014together form the observability triad.<\/li>\n<li>OpenTelemetry is the vendor-neutral standard for telemetry data collection.<\/li>\n<li>Distributed tracing visualizes request paths across microservices.<\/li>\n<li>Observability platform costs can reach 5\u201315% of cloud infrastructure spending.<\/li>\n<\/ul>\n<hr style=\"border: none; border-top: 1px solid #ddd; margin: 2em 0;\">\n<p><strong>Monitoring answers the question: Is my system working? Observability answers: Why isn&#8217;t it working? In distributed cloud systems with hundreds of microservices, traditional monitoring is no longer enough. Observability\u2014the combination of metrics, logs, and traces\u2014makes complex systems debuggable.<\/strong><\/p>\n<h2>From Monitoring to Observability<\/h2>\n<p>Traditional monitoring checks known states: CPU usage, memory consumption, HTTP status codes. Dashboards show red or green. This works for monolithic applications with predictable failure modes.<\/p>\n<p>In microservice architectures, this approach fails: a slow API call might stem from an overloaded service three hops away. CPU dashboards show green across all services\u2014the issue lies in interactions. Observability enables asking arbitrary questions about the system without having to define them in advance.<\/p>\n<div style=\"margin:32px 0;border-radius:12px;overflow:hidden;\">\n<div style=\"background:linear-gradient(135deg,#004a59 0%,#002535 100%);color:#fff;padding:36px 24px;text-align:center;\">\n<div style=\"font-size:clamp(2.2em,8vw,3.5em);font-weight:800;line-height:1;color:#0bb7fd;\">15%<\/div>\n<div style=\"font-size:1.05em;margin-top:8px;opacity:0.9;\">of cloud infrastructure costs.<\/div>\n<\/div>\n<div style=\"display:flex;flex-wrap:wrap;gap:0;\">\n<div style=\"flex:1;min-width:160px;background:#00364a;color:#fff;padding:20px 16px;text-align:center;border-right:1px solid rgba(255,255,255,0.1);\">\n<div style=\"font-size:clamp(1.3em,4vw,1.8em);font-weight:800;color:#0bb7fd;\">80%<\/div>\n<div style=\"font-size:0.8em;margin-top:6px;opacity:0.8;line-height:1.3;\">of alerts are noisy (often harmless). Instead, define: \u201c99% of requests<\/div>\n<\/div>\n<div style=\"flex:1;min-width:160px;background:#00364a;color:#fff;padding:20px 16px;text-align:center;\">\n<div style=\"font-size:clamp(1.3em,4vw,1.8em);font-weight:800;color:#0bb7fd;\">99%<\/div>\n<div style=\"font-size:0.8em;margin-top:6px;opacity:0.8;line-height:1.3;\">should be served under 200ms.\u201d When that\u2019s breached,<\/div>\n<\/div>\n<\/div>\n<\/div>\n<h2>The Observability Triad: Metrics, Logs, Traces<\/h2>\n<p><strong>Metrics<\/strong> are numerical time series: request rate, latency (p50, p95, p99), error rate, queue depth. Prometheus has become the de facto standard, often paired with Grafana for visualization. Metrics answer: What is happening right now?<\/p>\n<p><strong>Logs<\/strong> are textual entries with context: error messages, audit trails, debug information. Structured logging (JSON instead of plain text) makes logs machine-readable. The ELK Stack (Elasticsearch, Logstash, Kibana), Loki, and Datadog Logs are common platforms. Logs answer: What happened?<\/p>\n<p><strong>Traces<\/strong> follow a request across all involved services. Each hop is recorded as a span\u2014with timing, service name, and metadata. Jaeger, Zipkin, and Datadog APM visualize trace waterfalls. Traces answer: Where is the problem?<\/p>\n<h2>OpenTelemetry: The Universal Standard<\/h2>\n<p>Before OpenTelemetry, every observability tool created vendor lock-in: Datadog Agent, New Relic Agent, Dynatrace OneAgent\u2014all required proprietary instrumentation. Switching tools meant re-instrumenting the entire codebase.<\/p>\n<p>OpenTelemetry (OTel) solves this as a vendor-neutral standard. Applications are instrumented once using OTel SDKs and can send telemetry data to any compatible backend\u2014Grafana Cloud, Datadog, Honeycomb, Jaeger. The OTel Collector receives, processes, and exports data flexibly.<\/p>\n<p>OTel is a CNCF project backed by all major observability vendors. The recommendation is clear: Always use OpenTelemetry for new instrumentation\u2014never proprietary agents.<\/p>\n<h2>Keeping Costs Under Control<\/h2>\n<p>Observability costs can spiral out of control. Datadog bills exceeding 50,000+ Euro per month are not uncommon among mid-sized companies. The main drivers: every log entry, metric, and trace incurs ingestion and storage costs.<\/p>\n<p>Cost optimization strategies: <strong>Sampling<\/strong> \u2013 don\u2019t trace every request, but do it intelligently (Tail-Based Sampling traces only unusual requests). <strong>Log-Level Management<\/strong> \u2013 use Debug logs only in development, Info level in production. <strong>Retention Policies<\/strong> \u2013 move logs and traces to cold storage or delete them after 30 days.<\/p>\n<p>Open-source stacks (Prometheus + Grafana + Loki + Tempo) eliminate licensing fees but require operational overhead. The trade-off: SaaS (more expensive, less effort) vs. self-hosted (cheaper, more ops).<\/p>\n<h2>Alerting: The Right Signal at the Right Time<\/h2>\n<p>Too many alerts are worse than none \u2013 alert fatigue causes critical alerts to be overlooked. Best practice: base alerts on SLOs (Service Level Objectives), not individual metrics.<\/p>\n<p>Instead of alerting on &#8220;CPU > 80%&#8221; (often harmless), define: &#8220;99% of requests should be answered within 200ms.&#8221; When the error budget is exhausted, the system triggers an alert \u2013 regardless of whether CPU, memory, or an external service is the root cause. Tools like Sloth and Pyrra automate SLO-based alerting using Prometheus data.<\/p>\n<h2>Frequently Asked Questions<\/h2>\n<details style=\"border-bottom: 1px solid #e0e0e0; padding: 10px 0;\">\n<summary style=\"cursor: pointer; font-size: 15px;\"><strong>How much does an observability platform cost?<\/strong><\/summary>\n<p style=\"margin: 8px 0 4px 8px; color: #555;\">SaaS solutions (Datadog, New Relic, Dynatrace) typically cost 5\u201315% of your cloud infrastructure spend. For a monthly cloud bill of 100,000 \u20ac, that\u2019s 5,000\u201315,000 \u20ac\/month. Open-source stacks (Prometheus + Grafana + Loki) eliminate licensing costs but require 0.5\u20131 FTE for operations.<\/p>\n<\/details>\n<details style=\"border-bottom: 1px solid #e0e0e0; padding: 10px 0;\">\n<summary style=\"cursor: pointer; font-size: 15px;\"><strong>Is OpenTelemetry production-ready?<\/strong><\/summary>\n<p style=\"margin: 8px 0 4px 8px; color: #555;\">Yes. Traces and metrics have been stable (GA) since 2023. Logs reached GA in 2024. All major observability vendors support OTel. Recommendation: Always start new projects with OTel. Migrate existing instrumentation gradually.<\/p>\n<\/details>\n<details style=\"border-bottom: 1px solid #e0e0e0; padding: 10px 0;\">\n<summary style=\"cursor: pointer; font-size: 15px;\"><strong>How much should you trace?<\/strong><\/summary>\n<p style=\"margin: 8px 0 4px 8px; color: #555;\">Not everything. Tail-Based Sampling traces only requests that are unusual \u2013 high latency, errors, rare paths. This reduces data volume by 90\u201399% with minimal information loss. Head-Based Sampling (e.g., 10% of all requests) is simpler but less intelligent.<\/p>\n<\/details>\n<details style=\"border-bottom: 1px solid #e0e0e0; padding: 10px 0;\">\n<summary style=\"cursor: pointer; font-size: 15px;\"><strong>Which observability platform is the best?<\/strong><\/summary>\n<p style=\"margin: 8px 0 4px 8px; color: #555;\">It depends on context. Datadog offers the best all-in-one experience but is expensive. Grafana Cloud is more cost-effective and open-source-friendly. Honeycomb excels at query-based exploration. For small teams: Grafana Cloud Free Tier or self-hosted Prometheus + Grafana.<\/p>\n<\/details>\n<details style=\"border-bottom: 1px solid #e0e0e0; padding: 10px 0;\">\n<summary style=\"cursor: pointer; font-size: 15px;\"><strong>Do you need observability for monoliths?<\/strong><\/summary>\n<p style=\"margin: 8px 0 4px 8px; color: #555;\">Yes, but less urgently than for microservices. Metrics and logs are often sufficient for monoliths. Tracing becomes relevant once the monolith calls external services (databases, APIs, message queues). Starting with Prometheus + Grafana makes sense for any tech stack.<\/p>\n<\/details>\n<p style=\"text-align: right;\"><em>Header image source: Pexels \/ AS Photography<\/em><\/p>\n<h2>Editor\u2019s Reading Picks<\/h2>\n<ul>\n<li><a href=\"https:\/\/www.cloudmagazin.com\/en\/2026\/04\/05\/lenovo-thinkcentre-m75q-tiny-gen-5\/\">Lenovo ThinkCentre M75q Tiny Gen 5: Enterprise Mini-PC with AMD PRO and 5 Watt Idle for Edge and Kiosk<\/a><\/li>\n<li><a href=\"https:\/\/www.cloudmagazin.com\/en\/2026\/04\/04\/serverless-ai-overrated-cold-start-gpu-inference\/\">Serverless AI is overrated \u2013 here\u2019s what matters instead<\/a><\/li>\n<li><a href=\"https:\/\/www.cloudmagazin.com\/en\/2026\/04\/04\/qnap-ts-464\/\">QNAP TS-464: 4-Bay NAS with Docker, HDMI, and PCIe Slot \u2013 features Synology doesn\u2019t offer in this class<\/a><\/li>\n<\/ul>\n<h2>More from the MBF Media Network<\/h2>\n<p><a href=\"https:\/\/www.securitytoday.de\" target=\"_blank\">SecurityToday<\/a> | <a href=\"https:\/\/mybusinessfuture.com\" target=\"_blank\">MyBusinessFuture<\/a> | <a href=\"https:\/\/www.digital-chiefs.de\" target=\"_blank\">Digital Chiefs<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"Discover how cloud-native observability with metrics, logs, and traces provides in-depth insights into your complex systems.","protected":false},"author":31,"featured_media":27438,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_yoast_wpseo_meta-robots-noindex":"","_yoast_wpseo_meta-robots-nofollow":"","_yoast_wpseo_meta-robots-adv":"","_yoast_wpseo_canonical":"","_yoast_wpseo_opengraph-title":"","_yoast_wpseo_opengraph-description":"","_yoast_wpseo_opengraph-image":"","_yoast_wpseo_opengraph-image-id":0,"_yoast_wpseo_twitter-title":"","_yoast_wpseo_twitter-description":"","_yoast_wpseo_twitter-image":"","_yoast_wpseo_twitter-image-id":0,"pre_headline":"","bildquelle":"","teasertext":"","language":"de","_evm_slot_owner":"","_evm_translation_lang":"","featured_post":0,"featured_post_sortierung":0,"_wp_old_slug":[],"footnotes":""},"categories":[929],"tags":[192,320,237,416],"industry":[],"class_list":["post-37658","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-cm-guides","tag-cloud","tag-cloud-service","tag-cloud-trends","tag-cloud-loesung"],"evm_reading_time_minutes":5,"wpml_language":"en","wpml_translation_of":27439,"acf":[],"yoast_head":"<!-- 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