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Features

🛠️ Kubesense Features

Kubesense is an all-in-one observability platform for Kubernetes environments, offering advanced monitoring, logging, tracing, and metrics collection with minimal setup and high performance. With eBPF at its core, Kubesense provides real-time insights into infrastructure and application behavior, empowering teams to optimize performance, troubleshoot issues, and maintain system health.

Key Features​

⚙️ Infrastructure Monitoring​

Kubesense provides deep visibility into the health and performance of your Kubernetes infrastructure. With real-time insights into nodes, pods, and cluster resources, Kubesense helps you understand resource consumption patterns and identify potential bottlenecks.

  • Node and Pod Monitoring: Track CPU, memory, and disk utilization across nodes and pods.
  • Network Monitoring: Visualize traffic between Kubernetes resources and identify unusual network behaviors.
  • Resource Allocation: Monitor resource usage to ensure optimal allocation and prevent over-provisioning or resource exhaustion.

📜 Logs Management​

Efficient log management is crucial for troubleshooting and compliance. Kubesense captures and organizes logs from across your Kubernetes cluster, enabling quick access and real-time search.

  • Centralized Logging: Collect logs from all cluster components in a unified view.
  • Log Filtering and Search: Use advanced search capabilities to locate specific log entries quickly.
  • Alerting and Notifications: Set up alerts based on log patterns to stay informed about important events and issues.

🚀 Application Performance Monitoring (APM)​

Kubesense provides Application Performance Monitoring to help you measure and optimize application performance at the service level.

  • Service-Level Metrics: Gain insights into latency, throughput, and error rates for each service.
  • Transaction Monitoring: Monitor key transactions to ensure smooth user experiences and pinpoint performance bottlenecks.
  • Root Cause Analysis: Leverage AI-driven RCA to diagnose underlying causes of performance issues without needing extensive manual investigation.

🔍 Trace Explorer​

The Trace Explorer in Kubesense enables a granular view of distributed traces across services, making it easy to track the flow of requests and identify latency issues.

  • Trace Visualization: View detailed trace maps to analyze request flows across services.
  • Error Tracing: Identify failed requests and understand where errors originate within a trace.
  • Request Latency Analysis: Drill down into each service interaction to measure latency and optimize performance.

🌐 Supported Protocols​

Kubesense supports various protocols for seamless monitoring and tracing of network and service interactions.

  • HTTP/HTTPS: Monitor and trace HTTP traffic across your services.
  • gRPC: Track gRPC communication patterns for microservices-based applications.
  • TCP/UDP: Capture low-level TCP/UDP communication for network analysis.
  • Database Protocols: Compatible with popular database protocols for SQL query monitoring.

💻 Supported Programming Languages​

Kubesense is compatible with multiple programming languages commonly used in cloud-native applications.

  • Languages Supported:
    • Java
    • Node.js
    • Python
    • Go
    • .NET
    These languages are auto-instrumented for tracing, logging, and monitoring, making it easy to achieve comprehensive observability without extensive manual setup.

🔄 Distributed Tracing​

Kubesense’s Distributed Tracing feature provides end-to-end visibility into service requests across complex applications. Distributed tracing allows you to understand the full path of a request, including every microservice it interacts with, making it an essential tool for debugging and performance optimization.

  • End-to-End Request Tracing: Follow requests across multiple services to analyze their path and detect latency issues.
  • Trace Aggregation: Aggregate trace data for better analysis of request flows and performance patterns.
  • Error Identification: Identify and troubleshoot errors in specific parts of the trace to minimize system downtime.

📈 Service Map​

The Service Map in Kubesense provides a visual overview of service dependencies and relationships within your Kubernetes environment.

  • Service Interactions: See how services interact with each other in real-time.
  • Health Monitoring: Monitor the health status of each service, including error rates and latency.
  • Dependency Mapping: Automatically map service dependencies, helping to identify critical services and potential failure points.

📊 Metrics​

Kubesense collects and visualizes metrics at various levels, enabling precise monitoring and proactive management of resources.

  • Resource Metrics: Collect metrics on CPU, memory, and disk usage for nodes, pods, and containers.
  • Custom Metrics: Set up custom metrics to monitor specific aspects of your applications.
  • Real-Time Dashboards: View metrics in real-time dashboards for quick insights into system health and performance.
  • Alerting on Thresholds: Set threshold-based alerts on critical metrics to catch issues before they escalate.

With these comprehensive features, Kubesense equips DevOps and SRE teams with the insights they need to maintain reliable, high-performing applications in Kubernetes environments. Each feature is designed to provide maximum visibility and minimize the manual effort required to monitor and troubleshoot complex systems.