Kubernetes Logs Monitoring & Observability
Explore the nuances of Kubernetes Logging, offering a comprehensive approach to efficiently troubleshoot Kubernetes, trace issues, and optimize cluster performance.
Monitor Kubernetes logs across clusters, nodes, and workloads
Collect container stdout and stderr
Capture logs emitted to stdout and stderr by containers running in Kubernetes pods, including application output and runtime errors.
Aggregate pod and namespace logs
Organize logs by pod, namespace, workload, and label selectors to simplify troubleshooting in multi-tenant Kubernetes clusters.
Track pod lifecycle events
Ingest logs related to pod creation, restarts, crashes, and termination to analyze deployment and stability issues.
Monitor node-level system logs
Collect kubelet and container runtime logs from worker nodes to diagnose scheduling failures, image pull errors, and resource pressure.
Debug CrashLoopBackOff scenarios
Analyze container startup logs and failure messages to identify configuration errors and repeated pod restarts.
Correlate logs with Kubernetes metadata
Enrich log entries with Kubernetes context such as pod name, node, namespace, and deployment to speed up root cause analysis.
Observe control plane log signals
Capture logs from Kubernetes control plane components to investigate cluster-level issues and API server errors.
Handle high-volume cluster logging
Centralize Kubernetes logs from large clusters while maintaining query performance during traffic spikes and rolling deployments.
Centralize and Explore Kubernetes Logs With Atatus
Collect logs from Kubernetes containers and system components into Atatus so you can search, filter, and correlate them with contextual signals for faster insight.
Logs Fragmented Across Pods and Nodes
Logs spread across short-lived pods and multiple nodes make centralized visibility difficult, and collecting them in one place reveals cluster-wide patterns.
Application and System Logs Do Not Connect
Without centralized ingestion, Kubernetes system logs and application logs remain isolated, and bringing them together provides clearer operational context.
High Volume Makes Searching Hard
Kubernetes environments generate massive log volume, and structured fields with filters help narrow down to the entries that matter most.
Surface Log Patterns With Context
Logs alone lack context, and correlating log activity with traces or related signals ties events back to pods, services, and request paths.
Real-Time Log Visibility for Active Clusters
Streaming logs from containers in real time helps spot shifts in behavior or emerging issues while they are happening.
Why choose Atatus for Kubernetes logs monitoring?
Production-ready visibility into Kubernetes workloads, pod lifecycle events, and cluster operations
Kubernetes-native log collection
Designed to collect logs directly from Kubernetes pods and nodes without requiring changes to application containers.
Deep workload context
Automatically associates logs with Kubernetes metadata such as namespaces, deployments, nodes, and labels.
Faster incident investigation
Correlates pod restarts, container crashes, and deployment events across logs to reduce mean time to resolution.
Scales with growing clusters
Handles high log volumes generated by large Kubernetes clusters and dynamic workloads without performance degradation.
Supports modern Kubernetes environments
Works across managed Kubernetes services, self-hosted clusters, and hybrid infrastructure setups.
Built for SRE and platform teams
Provides the log visibility required by platform engineers to operate and maintain reliable Kubernetes infrastructure.
Unified Observability for Every Engineering Team
Atatus adapts to how engineering teams work across development, operations, and reliability.
Developers
Trace requests, debug errors, and identify performance issues at the code level with clear context.
DevOps
Track deployments, monitor infrastructure impact, and understand how releases affect application stability.
Release Engineer
Measure service health, latency, and error rates to maintain reliability and reduce production risk.
Frequently Asked Questions
Find answers to common questions about our platform