LINE TECHPULSE 2022 - Implementing Observability Practices on Kubernetes

Implementing Observability Practices on Kubernetes by Che-Wei Lin / Wan Jun-Wei / SRE @ LINE TECHPULSE 2022 https://techpulse.line.me/

Transcript

1. Che-Wei Lin / Wan Jun-Wei / SRE Implementing Observability Practices on Kubernetes 
2. Speakers Che Wei Lin a.k.a johnlin › Site Reliability Engineer @ LINE Taiwan › SRE Team › Loves Linux Networking, Distributed Systems & Open Source Wei › Site Reliability Engineer @ LINE Taiwan › SRE Team › A Gopher, interested in Kubernetes and Serverless › Sometimes contribute Open Source project.
3. Agenda › Traditional Monitoring Practices & Background › Overview of Observability Platform › Adoption Status & Current Practices › Challenges of Adoption › Sharing Use Cases
4. Traditional Monitoring Practices
5. Previous (K8s) Adoption Status October 2020 Projects 20+ App Configs 130+ K8s Clusters 50+
6. Current (K8s) Adoption Status October 2021 Projects +100% 20 40 K8s Clusters +40% 50 70 App Configs +500% 130 650+
7. Background Verda Infrastructure › VKS : Verda Kubernetes Service › VES : Verda Elasticsearch Service › VOS : Verda Object Storage › Most application teams use in-house service VKS for hosting applications › Verda is a private cloud service for LINE
8. Traditional Monitoring Practice Traditional Approaches › Prometheus long-term storage problem (ex: 6 months metrics) › Each team may have their own Grafana dashboards cause redundant works For Self-hosting Prometheus, Grafana For Self-hosting ELK stack › Need an expert in ELK stack to manage the performance and indices Build-in LogSender & Prometheus is Not Enough › Logs: Collect container logs with Fluentd and send to Verda Elasticsearch Service (VES) › Metrics: Prometheus monitor cluster level › Traces: Few teams adopt Zipkins for distributed request tracing
9. Overview of Observability Platform
10. Observability Platform Goal of Observability Platform › Use the same data sources and dashboards to discuss the behavior of events › The process of importing indicators into the application is the same and experience can be shared › Reduce communication costs caused by differences in tools Pooling of system knowledge for organization Everyone Uses Same Tools & Dashboards › Provides integrated logs, metrics, and tracing data sources › Built-in common used dashboards Reduce time for repeated deployment of monitoring facilities › Managed single Grafana instance › Multi-tenant for organizations and projects
11. Architecture Overview
12. Managed Ingress Controller
13. Grafana Tempo & OpenTelemetry Collector
14. Prometheus & Thanos
15. Grafana Loki
16. Adoption Status & 
 Current Practices
17. Adoption Status Observability Platform Project Adopted LINE HUB LINE TRAVEL LINE SPOT STICKER LINE TODAY LINE SHOPPING LINE MUSIC OA PLUS
18. Adoption Status Statistics of Grafana Users Organizations 34 Active users (30d) 120+ Users 200+
19. Adoption Status Statistics of Grafana Across all Organizations Dashboards 750+ Alerts 300 Data Sources 200
20. Prometheus Grafana Loki Grafana Tempo InfluxDB Elasticsearch MySQL 0 10 20 30 40 Adoption Status Statistics of Data Sources
21. Adoption Status Statistics of Telemetry Data 40B+ / week Log Lines 300M / h hourly, weekly Metric Series 16M 20B+ / week Trace Spans 200M / h
22. Adoption Status Storage Usage 20M Objects Logs 30TB 360K Objects Metrics 60 TB 1M Objects Traces 20TB
23. How to manage agents for more than 70 clusters
24. Current Practices: Argo CD ApplicationSet Manage Multiple Argo CD App Cluster B Cluster C Cluster A Argo CD Git
25. Current Practices: Telemetry Data Logs, Metrics & Traces › Logs: A record of an event that happened within an application › Metrics: Numerical representation of data. Determine a service or component’s overall behavior over time › Traces: The entire path of a request as it moves through all the nodes of a distributed system Exemplars Split view with labels Metric queries Span metrics processor Trace to logs Followed Trace ID Metrics Traces Logs
26. Challenges of Adoption
27. Challenges of Adoption Challenges of Adopting from Application Team Introducing new languages (LogQL, PromQL) Instrumenting for metrics & tracing may require retrofitting existing infrastructure
28. How to deal with these challenges Internal Hands-on Workshops for Teams
29. How to deal with these challenges Built-in Default Dashboards on Grafana › Blackbox/Uptime Dashboards › Kubernetes Events/Deployment/ Jobs › Traefik Latency/QPS Dashboards
30. How to deal with these challenges Provide managed ingress controller which already export metrics & traces Out of the box feature Built-in TLS certificates & Traefik common middlewares Integrated structure log, tracing agent and exposed metrics
31. Sharing Use Cases
32. Use Case Interactive Observation with Different Indicators Find out 500 error from metrics Link to corresponding access logs Open trace viewer for a request Jump to application logs in span of trace Logs Traces Logs Metrics
33. Increased error rate of HTTP requests Error in metrics
34. Metrics to Logs Sync All Views to This Time Range
35. Filter logs by LogQL Locate Log
36. Logs to Traces Find the Trace from Logs
37. Traces to Logs Checking the stack trace of error
38. Roadmap Next Steps Error Tracking Sentry Web Vitals Metrics to Traces Prometheus 
 with 
 Exemplars Logs Grafana Loki 
 with 
 Promtail Traces to Metrics OpenTelemetry Collector with 
 Span Metrics Processor Traces Grafana Tempo 
 with 
 OpenTelemetry Collector Metrics Prometheus 
 with 
 Thaons
39. Summary Key Takeaways › Observability platform brings a consolidated dashboard and pooling of system knowledge across organization › Current observability practices speed up for teams to achieve actionable insights from data › Traditional monitoring practices are not enough for teams debugging in a distributed system › Adoption challenges, experience sharing and use cases sharing
40. Thank you