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Kubernetes #2 monitoring
This document discusses Kubernetes monitoring concepts and architectures. It describes how cAdvisor collects metrics from nodes and pods and sends them to Heapster for storage and visualization. It also covers the Kubernetes dashboard for visualizing cluster resources and creating/modifying resources, as well as logging with ELK or Stackdriver. Finally, it briefly mentions Datadog as a monitoring solution for Kubernetes.
In this document
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Introduction to Kubernetes monitoring concepts, architecture, and an outline of topics including Dashboard and tools like Stackdriver and Datadog.
Detailed explanation of monitoring metrics at host, container, application, and Kubernetes levels with architecture involving cAdvisor, Kubelet, and Heapster.
Insight into monitoring components such as cAdvisor for resource usage, InfluxDB for time-series data, and Grafana for data visualization.
Logging in Kubernetes using ELK or Google Stackdriver, detailing how logs are gathered and visualized.
Overview of the Kubernetes dashboard providing a web-based interface for resource monitoring and management.
Information on integrating Datadog with Kubernetes for enhanced monitoring capabilities and references for further information.
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Kubernetes #2 monitoring
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- 2. Agenda ● Kubernetes MonitoringConcept ● Kubernetes Monitoring Architecture ● Kubernetes Dashboard ● Google Stackdriver ● Datadog
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- 4. Kubernetes monitoring stack 1.Host-level metrics and event (CPU,Memory,Disk etc) 2. Container(Docker/Pod) level metrics (CPU,Memory,Disk) 3. Application metric (APM etc) 4. Kubernetes level - events, by label Image source : https://www.datadoghq.com/blog/how-to-collect-and-graph- kubernetes-metrics/
- 5. K8u monitoring solutionsmarket (2017) Source : https://thenewstack.io/5-tools-monitoring-kubernetes-scale-production/
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- 7. Kubernetes resource monitoring ●cAdvisor collect metrics from nodes and pods and send it into Kubelet ● Kublet sends all of pods in nodes information to Heapster. ● Heapster runs as a Pod in cluster ● Heapster stores all of info into storage backend (Google Stack driver, influx DB) ● It can be visualized by using Grafana Source : https://www.datadoghq.com/blog/how-to-collect-and-graph- kubernetes-metrics/
- 8. Components cAdvisor ● Open sourcecontainer resource usage and performance analysis agent ● Auto discovers all containers in the machine ● Collect CPU,memory,file system and network usage statics for containers ● Overall machine usage (node) by analyzing the ‘root’ container on the machine InfluxDB ● Open source time series DB Grafana ● Dashboard visualization tools
- 9. Components cAdvisor application metric(Alpha) ● https://github.com/google/cadvisor/blob/mast er/docs/application_metrics.md ● cAdvisor can also be configured to collect application metrics. A container can expose application metrics through multiple ways ○ on a status page, ○ through structured info like prometheus, ○ or have a separate API for fetching stats. ● Endpoint (Location to collect metrics from) ● Name of metric ● Type (Counter, Gauge, ...) ● Data Type (int, float) ● Units (kbps, seconds, count) ● Polling Frequency ● Regexps (Regular expressions to specify which metrics to collect and how to parse them) Step 2. Passing configuration to cAdvisor Step 1. Create configuration
- 10. Kubernetes Logging ● Itsupports logging with ELK or Google stack driver ● ELK ○ The fluentd-elasticsearch pods gather logs from each node and send them to the elasticsearch- logging pods ○ These Elasticsearch pods store the logs and expose them via a REST API. ○ The kibana-logging pod provides a web UI for reading the logs stored in Elasticsearch, and is part of a service named kibana-logging Image source : https://kubernetes.io/docs/tasks/debug-application-cluster/logging-elasticsearch-kibana/
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- 12. Dashboard Dashboard is Web-UIbased kubernetes interface ● Overview of application running on cluster ● Monitoring resources ● Create or modifying Kubernetes resources (such as deployments, jobs, daemonset etc) For example, you can scale a Deployment, initiate a rolling update, restart a pod or deploy new applications using a deploy wizard. Dashboard is not deployed in default. To deploy dashboard run script % kubectl create -f https://raw.githubusercontent.com/kubernetes/dashboard/master/src/deploy/recommended/kubernetes-dashboard.yaml
- 13. Connect to dashboard https://github.com/kubernetes/dashboard/wiki/Accessing-Dashboard---1.7.X-and-above ●For dev ○ kubectl proxy ○ http://localhost:8001/api/v1/namespaces/kube-system/services/https:kubernetes- dashboard:/proxy/ ● In production
- 14. Create sample user ●Guide : https://github.com/kubernetes/dashboard/wiki/Creating- sample-user
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- 16. Shell It can alsorun bash shell thru dashboard
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- 18. Reference ● GKE monitoringwith datadog https://www.datadoghq.com/blog/monitor-google-kubernetes-engine/