Observability
20 articles from official documentation
Kubernetes v1.37: Metrics API Stabilization and Its Impact
Kubernetes v1.37 has promoted the metrics.k8s.io API to stable, a crucial step for monitoring resource usage in your clusters. This API provides real-time CPU and memory metrics for nodes and Pods, enabling effective autoscaling and performance tuning.
- →Utilize the metrics.k8s.io API for real-time CPU and memory metrics.
- →Implement metrics-server or a compatible solution to access the v1 metrics API.
The Lazy Developer’s Guide to Observing Your Code with OpenTelemetry
Observability is crucial for maintaining healthy applications, yet many developers shy away from it. With zero-code instrumentation, you can add observability without touching your source code. This guide will show you how to leverage OpenTelemetry effectively.
- →Utilize zero-code instrumentation to avoid modifying your source code.
- →Implement observability-driven development (ODD) to integrate observability into your coding practices.
Automating RCA at Scale: Mastering Multi-Signal Correlation in Kubernetes
Root Cause Analysis (RCA) can be a nightmare in cloud-native environments. Multi-signal correlation offers a structured approach to pinpoint issues by analyzing anomalies across various signals. This article dives into how this method works and what you need to implement it effectively.
- →Utilize multi-signal correlation to treat RCA as a correlation problem across various signal types.
- →Configure the sliding window to group anomalies effectively, typically set to plus or minus 5 minutes.
Solving Zero+Zero=Two in Mesh Observability
In the world of mesh observability, ensuring accurate trace propagation is crucial. When Envoy creates a new root span instead of continuing an existing trace, you end up with misleading telemetry. This article dives into how to configure OpenTelemetry and Istio to avoid this pitfall.
- →Enable tracing in Envoy to ensure spans are generated correctly.
- →Configure applications to emit B3 headers alongside W3C Trace Context headers.
Mastering Cloud-Native Engineering: The LFX Mentorship Advantage
Tired of tutorials that don’t translate to real-world scenarios? The LFX Mentorship offers a structured approach to learning cloud-native engineering, emphasizing observability as a critical pipeline. Dive into production-style environments and learn to tackle real system failures.
- →Understand observability as a resilient pipeline designed to survive failures.
- →Engage in a structured mentorship that emphasizes autonomy and independent problem-solving.
LitmusChaos in 2026: Community Growth and Project Milestones
Chaos engineering is crucial for resilient systems, and LitmusChaos is at the forefront of this movement. As a CNCF Incubating project, it empowers teams to identify weaknesses in their infrastructure through controlled chaos experiments. Discover how this platform is evolving and what it means for your Kubernetes deployments.
- →Leverage LitmusChaos to identify infrastructure weaknesses through controlled chaos experiments.
- →Engage with the growing community to share insights and best practices in chaos engineering.
Unlocking AI Agent Debugging: The Power of Observability
Debugging AI agents is impossible without clear visibility into their operations. By implementing detailed traces that capture every decision and cost, you can gain insights that drive performance. Discover how to leverage observability for effective AI agent management.
- →Implement detailed traces to capture every decision history of your AI agents.
- →Utilize Langfuse as your trace backend for structured and nested traces.
Stop Your Kubernetes Health Checks from Waking Services: Here’s How
Kubernetes health checks can inadvertently trigger your services to scale up when they should remain idle. Learn how to leverage the ProbeResponse feature to manage health checks effectively and keep your services scaled to zero when not in use.
- →Leverage the ProbeResponse feature to prevent unnecessary scaling of services.
- →Define probe rules that match your health check paths accurately.
Unlocking Observability: Insights from the Debut Observability Summit Europe
The Observability Summit Europe is set to kick off on October 5, 2026, in Prague, Czechia, and it’s a must-attend for anyone serious about Kubernetes. Dive into core topics like Observability as Code (OaC) and the Model Context Protocol (MCP) that are shaping the future of observability.
- →Explore Observability as Code (OaC) to automate observability practices.
- →Understand the Model Context Protocol (MCP) for better correlation of metrics and logs.
OpenTelemetry Graduation: A Game Changer for Kubernetes Observability
OpenTelemetry has officially graduated, marking a significant milestone in observability. This unified framework allows you to collect traces, logs, and metrics without vendor lock-in. Dive in to understand how this impacts your Kubernetes deployments.
- →Understand that OpenTelemetry merges OpenCensus and OpenTracing for unified observability.
- →Leverage standardized APIs to collect telemetry signals without vendor lock-in.
Flipkart's Chaos Engineering Revolution: Insights from KubeCon + CloudNativeCon India 2026
Chaos engineering is not just a buzzword; it's a necessity for resilient systems. Flipkart's Central Reliability Engineering team showcased their innovative use of LitmusChaos, including a DaemonSet-based model for chaos injection. Dive into how they tackled real-world challenges with this approach.
- →Implement a hybrid multi-tenancy architecture for chaos engineering to support diverse workloads.
- →Utilize a DaemonSet-based model for high-availability chaos injection across your Kubernetes cluster.
Building a Custom Metrics Exporter for Kubernetes: A Practical Guide
Custom metrics exporters are essential for monitoring application states in Kubernetes. By exposing metrics through a simple HTTP server, you can gain insights into your application's performance. Learn how to implement this with concrete examples and avoid common pitfalls.
- →Expose application metrics through a /metrics endpoint for Prometheus scraping.
- →Use counters for totals, gauges for current values, and histograms for distributions.
Diagnosing Kubernetes Control Plane Performance with AWS DevOps Agent
Kubernetes control plane performance can make or break your cluster's stability. The AWS DevOps Agent autonomously identifies issues, correlating CloudWatch logs with throttling patterns to deliver actionable insights. This article dives into how to leverage this tool effectively in production environments.
- →Utilize the AWS DevOps Agent to autonomously investigate performance issues in your Kubernetes control plane.
- →Configure the agent with the correct EKS Access Entry Type and Access Policy for optimal performance.
Speed Up Your Volcano Workload Insights with Headlamp
Tired of slow inspections of your Volcano workloads? Headlamp integrates seamlessly with Volcano, allowing you to visualize workload states and queue behaviors in one place. Dive into the specifics of how this integration enhances your Kubernetes experience.
- →Utilize Headlamp to visualize Volcano workload states and queue behaviors.
- →Access dedicated views for Jobs, Queues, and PodGroups directly in Headlamp.
Building High-Impact Observability Pipelines in Kubernetes
In a world where every metric consumes resources, designing sustainable observability pipelines is crucial. Implementing an observability mesh can connect your metrics, traces, and logs seamlessly, enhancing your monitoring strategy.
- →Implement green observability to optimize resource usage in your telemetry.
- →Utilize an observability mesh to connect metrics, traces, and logs effectively.
Flipkart's Chaos Engineering Triumph: Scaling Kubernetes with Confidence
Chaos engineering is essential for building resilient systems, and Flipkart's recent success showcases its power. By executing 90% of chaos experiments in staging, they ensure stability during high-traffic events. Discover how they customized LitmusChaos for their unique needs.
- →Execute chaos experiments in staging environments to identify weaknesses before production.
- →Leverage LitmusChaos extensions for tailored chaos engineering solutions.
Dynamic Configuration for Cloud Native Swift Services in Kubernetes
Dynamic configuration is crucial for cloud-native applications, especially in a Kubernetes environment. By leveraging the ConfigReader and ReloadingFileProvider, you can achieve hot reloading of configuration values without restarting your services. This article dives into how to set it up effectively.
- →Utilize ConfigReader to manage configuration from multiple providers effectively.
- →Implement ReloadingFileProvider for hot reloading of configuration without service restarts.
Understanding the Kubernetes Integration Tax: Navigating Prometheus and Cilium in Production
Running multiple CNCF projects together in Kubernetes can lead to hidden costs, known as the integration tax. This article dives into how Cluster API manages your infrastructure and the importance of generating your monitoring effectively.
- →Understand the integration tax when running multiple CNCF projects together.
- →Utilize Cluster API for managing Kubernetes-native resources effectively.
Tracing AI Agents: Jaeger's Evolution with OpenTelemetry
Jaeger is evolving to trace AI agents, addressing the complexities of monitoring AI interactions. With the integration of OpenTelemetry, it streamlines data collection through protocols like MCP and ACP, enhancing performance and collaboration.
- →Understand the Model Context Protocol (MCP) for secure data access by AI models.
- →Utilize the Agent Client Protocol (ACP) for uniform communication with AI agents.
OpenTelemetry Graduation: The New Standard for Observability in Kubernetes
OpenTelemetry's graduation marks a pivotal moment in the observability landscape. This open-source framework standardizes telemetry data collection, allowing seamless transitions between analysis tools without code rewrites.
- →Standardize telemetry data collection with OpenTelemetry to reduce tool fragmentation.
- →Utilize a single set of APIs and SDKs to simplify observability across your systems.
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