Combining Logs, Metrics, and Traces for Unified Observability
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Learn how Elasticsearch efficiently combines data in a single store and how Kibana is used to analyze it. Plus, see how recent developments help identify, troubleshoot, and resolve operational issues faster.
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Combining Logs, Metrics, and Traces for Unified Observability
- 1. Jamie Smith Product Marketing, Observability April 23, 2020 Logs, Metrics, and APM for Unified Observability
- 2. Elastic Enterprise Search Elastic SecurityElastic Observability
- 3. Logs Metrics APM Uptime Elastic Observability
- 5. Higher resource utilization increases monitoring complexity • Orchestration/Hypervisor • Dynamic/ephemeral jobs • You can no longer "point" to where that job lives Monitoring Complexity Hardware & software trends are evolving in tandem Evolving Architectures ~↑ Monitoring Complexity Shift to cloud-native yields maintainable code, with costs • Traditional licensing models don't scale as well as your applications • Hurdles with autoscaling
- 6. Applications VMs/Containers Other DBs, Services & Middleware Orchestration InfrastructureAPM Metrics Logs Uptime Uptime APM Metrics APM Logs APM APM Metrics Logs Uptime Metrics Logs Uptime APM
- 7. How many tools does your org currently use for monitoring your systems?
- 8. Development Team Ops: Log Monitoring Uptime Response Time Uptime Tool Ops: Infra Monitoring Web Logs App Logs Database Logs Container Logs Log Tool Ops: Service Monitoring Real User Monitoring Txn Perf Monitoring Distributed Tracing APM Tool Container Metrics Host Metrics Database Metics Network Metrics Storage Metrics Metrics Tool Status Quo: Siloed Collection of Tools
- 9. Observability is a search use case
- 10. APM Data Uptime DataMetrics DataLog Data Elastic Approach to Observability Uptime Response Time Web Logs App Logs Database Logs Container Logs Real User Monitoring Txn Perf Monitoring Distributed Tracing Container Metrics Host Metrics Database Metics Network Metrics Storage Metrics Dev & Ops Teams
- 11. • Correlate data from different sources • Ability to re-use analysis content • Ability to re-use Elastic-provided content Benefits • Published at: github.com/elastic/ecs • Supported in Beats and APM since 7.0 • Community feedback welcome! Status Elastic Common Schema (ECS) Supports ad hoc analysis in Kibana Dashboards
- 12. Unified User Interface Same UI for KPI summaries and root-cause analysis
- 13. Correlate multiple data sources for more intelligent anomaly detection Unified Machine Learning
- 14. Trigger off any operational data to provide unified SLA monitoring Unified Alerting
- 15. Pricing aligned with business value Unified Licensing Model PER AGENT $$$$ PER HOST $$$$ PER INGEST $$$$ PER MONITOR $$$$ PER ADD-ON $$$$ • Intuitive Single, unified pricing model. No add-ons. • Cloud native No problem using with container workloads and serverless. • Future proof You pay for capacity and are not locked into a specific use case.
- 16. Elastic Stack for logs
- 17. Logs 64.242.88.10 - - [07/Jan/2019:16:10:02 -0800] "GET /mailman/listinfo/hsdivision HTTP/1.1" 200 6291 64.242.88.10 - - [07/Jan/2019:16:10:02 -0800] "POST /twiki/bin/view/TWiki/WikiSyntax HTTP/1.1" 404 7352 64.242.88.10 - - [07/Jan/2019:16:10:02 -0800] "GET /twiki/bin/view/Main/DCCAndPostFix HTTP/1.1" 200 5253 For each event, print out what happened. Logs are chronological records of events
- 18. Ongoing investment in log ingest & long-term retention 2015 2016 2018 2017 2019 ELK Stack is born Logstash and Kibana released, forming an OSS logging alternative 2011-12
- 19. Ongoing investment in log ingest & long-term retention 2015 2016 2018 Elastic welcomes Beats to the family, introducing light-weight data shippers 2017 2019 ELK Stack is born Logstash and Kibana released, forming an OSS logging alternative 2011-12 Filebeat: Lightweight log shipper
- 20. Ongoing investment in log ingest & long-term retention 2015 2016 2018 Filebeat: Lightweight log shipper Elastic welcomes Beats to the family, introducing light-weight data shippers 2017 2019 Simplified ingest architecture with Filebeat modules & ingest node ELK Stack is born Logstash and Kibana released, forming an OSS logging alternative 2011-12 Modules: Out-of-the-box log parsers
- 21. Elastic welcomes Beats to the family, introducing light-weight data shippers Ongoing investment in log ingest & long-term retention 2015 2016 Hosted Logging in Elastic Cloud & ECE Introduction of ECE enabling log clusters with index curation, hot/warm templates 2018 Filebeat: Lightweight log shipper 2017 2019 Modules: Out-of-the-box log parsers Simplified ingest architecture with Filebeat modules & ingest node ELK Stack is born Logstash and Kibana released, forming an OSS logging alternative 2011-12
- 22. Ongoing investment in log ingest & long-term retention 2015 2016 Hosted Logging in Elastic Cloud & ECE Introduction of ECE enabling log clusters with index curation, hot/warm templates 2018 2017 Cold storage for logging: Frozen Indices & ILM Curated log-based troubleshooting, improved cold storage efficiency and index lifecycle management 2019 Modules: Out-of-the-box log parsers Simplified ingest architecture with Filebeat modules & ingest node Hot. Warm. Cold. Delete. ELK Stack is born Logstash and Kibana released, forming an OSS logging alternative 2011-12 Elastic welcomes Beats to the family, introducing light-weight data shippers Filebeat: Lightweight log shipper
- 23. Ongoing investment in log ingest & long-term retention 2015 2016 Hosted Logging in Elastic Cloud & ECE Introduction of ECE enabling log clusters with index curation, hot/warm templates 2018 2017 Cold storage for logging: Frozen Indices & ILM Curated log-based troubleshooting, improved cold storage efficiency and index lifecycle management 2019 Modules: Out-of-the-box log parsers Simplified ingest architecture with Filebeat modules & ingest node ELK Stack is born Logstash and Kibana released, forming an OSS logging alternative 2011-12 Logs App: Integrating Logs with Metrics and APM Logging libraries support Elastic Common Schema, trace-id in logs, workflow from Logs to APM Elastic welcomes Beats to the family, introducing light-weight data shippers Filebeat: Lightweight log shipper
- 24. Elastic Stack for metrics
- 25. Metrics vs Logs Metrics are periodic measurement of numeric KPIs 07/Jan/2019 16:10:00 all 2.58 0.00 0.70 1.12 0.05 95.55 server1 containerX regionA 07/Jan/2019 16:20:00 all 2.56 0.00 0.69 1.05 0.04 95.66 server2 containerY regionB 07/Jan/2019 16:30:00 all 2.64 0.00 0.65 1.15 0.05 95.50 server2 containerZ regionC Every x minutes, measure the CPU load, print it out, and annotate with meta-data. 64.242.88.10 - - [07/Jan/2019:16:10:02 -0800] "GET /mailman/listinfo/hsdivision HTTP/1.1" 200 6291 64.242.88.10 - - [07/Jan/2019:16:10:02 -0800] "POST /twiki/bin/view/TWiki/WikiSyntax HTTP/1.1" 404 7352 64.242.88.10 - - [07/Jan/2019:16:10:02 -0800] "GET /twiki/bin/view/Main/DCCAndPostFix HTTP/1.1" 200 5253 For each event, print out what happened. Logs are chronological records of events
- 26. Evolution of Elastic Stack to a Metrics Store BKD trees Data structures optimized for numerical time series analysis. Columnar storage Structured data storage, resulting in compact storage and faster analytics Rollups Aggregate older data into bigger time buckets Aggregations framework Analytics features to slice and dice data along various dimensions 2012 2016 2014 2018
- 27. Elastic as an Infrastructure Metrics Solution 201? 2017 Users start putting metrics in Elastic Need for high-cardinality aggregations, and correlating metrics and logs 2016 2018 2019
- 28. Elastic as an Infrastructure Metrics Solution 201? 2017 Users start putting metrics in Elastic Need for high-cardinality aggregations, and correlating metrics and logs 2016 2018 2019 Metricbeat: Turnkey metric collection Metricbeat is introduced for turnkey metrics collection
- 29. Elastic as an Infrastructure Metrics Solution 201? 2017 Users start putting metrics in Elastic Need for high-cardinality aggregations, and correlating metrics and logs 2016 2018 2019 Metricbeat: Turnkey metric collection Metricbeat is introduced for turnkey metrics collection Time Series Visual Builder UI for advanced metrics visualization, working with pipeline aggregations
- 30. Elastic as an Infrastructure Metrics Solution 201? 2017 Users start putting metrics in Elastic Need for high-cardinality aggregations, and correlating metrics and logs 2016 2018 2019 Metricbeat: Turnkey metric collection Metricbeat is introduced for turnkey metrics collection Time Series Visual Builder UI for advanced metrics visualization, working with pipeline aggregations Prometheus / OpenMetrics integration Enables turnkey collection in Kubernetes ecosystem and beyond Your App Prometheus Exporter Your App Prometheus Exporter Metricbeat + Elasticsearch Prometheus Server Metricbeat + Elasticsearch
- 31. Elastic as an Infrastructure Metrics Solution 201? 2017 Users start putting metrics in Elastic Need for high-cardinality aggregations, and correlating metrics and logs 2016 2018 2019 Metricbeat: Turnkey metric collection Metricbeat is introduced for turnkey metrics collection Time Series Visual Builder UI for advanced metrics visualization, working with pipeline aggregations Prometheus / OpenMetrics integration Enables turnkey collection in Kubernetes ecosystem and beyond Metrics App Containers, hosts, services, cloud monitoring, ad-hoc metrics exploration
- 32. Elastic Stack for APM
- 33. 33 Why APM? 03:43:45 Request "GET cyclops.ESProductDetailView" 03:43:57 Response "cyclops.ESProductDetailView 200 OK" 12 seconds - zZzzZZz Example: Slow response or load times
- 34. Why APM? 03:43:59 Request "POST /api/checkout" 03:43:59 Response "/api/checkout 500 ERROR" Example: Errors & Exceptions
- 35. 35 Evolution of Elastic Stack to Open Source APM Elastic joins forces with Opbeat A next-generation APM solution designed for developers 2017 6.1 Search for APM + more agents Enabled search & Machine Learning for APM, Java agents GA, RUM GA 6.4 Elastic APM beta release Including APM Server and curated APM UI native to Kibana 6.2 Support for OpenTracing, Distributed tracing, and an app completely integrated with Logs & Metrics 6.6 Elastic APM GA Agents for Python, Node.js, Ruby, Javascript; Real User Monitoring Beyond Embracing open standards
- 36. APM Agents ● Java ● Go ● .NET ● Javascript (React / Angular) ● RUM (Real User Monitoring) Language Support ● Python ● Ruby ● Node.js • Easy to add to your applications • Designed to be lightweight • Open source • Support distributed tracing • OpenTracing compatible Auto-instrumentation of common programming frameworks
- 37. Distributed Tracing & OpenTracing + Jaeger intake End-to-end transaction tracking with auto-instrumentation or OpenTracing IDs
- 39. 39 Elastic Stack for uptime
- 42. 42 Demo
- 43. 43 Demo
- 44. What now? Try it yourself!
- 45. While you monitor, why not protect? Elastic SIEM
- 46. Thank you
- 47. 47 Matt Riley Senior Director of Product Management, Enterprise Search Search for All with Elastic Workplace Search