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!1
Tanya Bragin
Sept 2018
Logging, Metrics, and APM: The Operations Trifecta
Logs
Metrics
APM
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Benefits of Logs + Metrics + APM in one stack
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Unified Dashboards
Same UI for KPI summaries and root cause analysis
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Unified Alerting
Trigger off any operational data to provide unified SLA monitoring
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Unified Machine Learning
Correlate multiple data sources for more intelligent anomaly detection
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Operational gains
Single technology for operational data saves on administrative costs
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Elastic Stack for logs
Metrics vs Logs
64.242.88.10 - - [07/Mar/2017:16:10:02 -0800] "GET /mailman/listinfo/hsdivision HTTP/1.1" 200 6291
64.242.88.10 - - [07/Mar/2017:16:11:58 -0800] "POST /twiki/bin/view/TWiki/WikiSyntax HTTP/1.1" 404 7352
64.242.88.10 - - [07/Mar/2017:16:20:55 -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
Making logging more turnkey with ‘modules’
• Turnkey experience for specific data types
• Data to dashboard in just one step
• Automated parsing and enrichment
• Default dashboards, alerts, ML jobs
Logging modules
System
• Linux / MacOS
• Windows Events
Containers
• Docker
• Kubernetes
Databases
• MySQL
• PostgreSQL
Queues
• Kafka
• Redis
Web servers
• Apache
• Nginx
Audit data
• Filesystem
• System calls
WINLOGBEATFILEBEATAUDITBEAT
Infrastructure Applications
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Ad-hoc log search and visualization
Kibana Discover, Visualize, Dashboard
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Hot/Warm architectures in EC / ECE
• One click hot-warm deployments
• Shipped in EC in Aug 2018
• ECE support coming!
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Elastic Stack for metrics
Metrics vs Logs
64.242.88.10 - - [07/Mar/2017:16:10:02 -0800] "GET /mailman/listinfo/hsdivision HTTP/1.1" 200 6291
64.242.88.10 - - [07/Mar/2017:16:11:58 -0800] "POST /twiki/bin/view/TWiki/WikiSyntax HTTP/1.1" 404 7352
64.242.88.10 - - [07/Mar/2017:16:20:55 -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
07/Mar/2017 16:10:00 all 2.58 0.00 0.70 1.12 0.05 95.55 server1 containerX regionA

07/Mar/2017 16:20:00 all 2.56 0.00 0.69 1.05 0.04 95.66 server2 containerY regionB

07/Mar/2017 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 and print it out, and annotate with meta-data.

Metrics are periodic measurements of numeric KPIs
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Evolution of Elasticsearch into Metrics Store
Elasticsearch for search and numerical analytics
Inverted Index for full-text search Columnar store for structured data
BKD Trees for numerical operations Rollups
• Elasticsearch primarily used for application search
• Lucene data structure: Inverted index
Elasticsearch beginnings
Circa 2010
• Elasticsearch 1.0 evolves to support a columnar store (built on top of Lucene “doc values”)
• Structured string and numerical data can be stored there for fast retrieval and summarization / analytics
Elasticsearch evolving to support analytics
~ 2010 to 2014
https://www.elastic.co/blog/elasticsearch-as-a-column-store
• Elasticsearch 5.0 adds more data structures for efficient storing and querying numbers (BKD Trees)
• These structures become the default storage for numerical and geospatial data in Elasticsearch
Elasticsearch storage efficiencies
2016
https://www.elastic.co/blog/searching-numb3rs-in-5.0
1-Dimension 2-Dimensions
• Elasticsearch 6.0 improves Lucene sparse values storage efficiency (41.5% in Metricbeat index size)
Elasticsearch storage efficiencies
2017
https://www.elastic.co/blog/minimize-index-storage-size-elasticsearch-6-0
Rollup support for long-term retentions
https://www.elastic.co/blog/data-rollups-in-elasticsearch-you-know-for-saving-space
Added in Elasticsearch 6.3
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DEMO
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Elastic Stack as a Metrics Solution
Metrics modules
System
• Linux
• MacOS
• Windows
• Perfmon
Infrastructure
Cloud
• AWS
• GCP
• Azure
• DigitalOcean
• Alibaba
Containers
• Docker
• Kubernetes
Virtualization
• vSphere
PACKETBEATMETRICBEAT
Network
• Netflow
• Packets
• TLS Envelope
Storage
• Ceph
LOGSTASHHEARTBEAT
Applications
Datastores
• MySQL
• PostgreSQL
• MongoDB
• Couchbase
• Aerospike
• Graphite
Web servers
• Apache
• Nginx
Other
• HAProxy
• Zookeeper
Queues
• Kafka
• Redis
• RabbitMQ
Caches
• Memcached
Uptime
• Heartbeat
Custom apps
• JMX/Jolokia
• PHP-FPM
• Golang
Metrics modules PACKETBEATMETRICBEAT LOGSTASHHEARTBEAT
Roadmap: New operational data sources
New Beats,
Logstash inputs
and modules
Default actions
for existing
modules
Agentless
Shippers
• Cloud Monitoring (Azure,
Amazon, GCP, …)
• Security Analytics (Bro,
Suricata, Sysmon,…)
• Machine Learning jobs for
Docker/Kubernetes
• Default alerts for top 5
modules
• Deploy as functions
• Ship data without needing to
tent to infrastructure
• Correlate data from different sources
• Ability to re-use analysis content
• Ability to re-use Elastic-provided content
Correlation between logs, metrics, and APM
Benefits
• Version 0.1 published: github.com/elastic/ecs
• Working with internal groups to validate
• Community feedback welcome!
Status
Elastic Common Schema
Visualizing time series data
Time Series Visual Builder
Visualizing time series data
Annotations
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Elastic Stack for APM
What is APM?
Example
08:32:10 Request "/api/checkout"
08.32:11 Response "/api/checkout 500 ERROR"
What is APM?
Example
08:32:10 Request "/api/products/top"
08.32:17 Response "/api/products/top 200 OK"
7 seconds - zZzzZZz
How does APM work?
Data
processor
apm-server
Data storage
elasticsearch
Browser
Agent
Web server
Agent
Web server
Agent
Web server
Agent
UI
kibana
Browser
Agent
Browser
Agent
• Focuses on search experience on top of APM data
• ‘Just another index’ in Elastic Stack
Elastic APM
APM adds end-user experience and application-level monitoring to the stack
Language support
● Python

● Node.js

● Ruby (Beta)

● RUM (Beta)


● Java (Beta)
● Go (Beta)
Curated UI for APM
Combine custom
workflow with
freedom of search
Roadmap: Distributed Tracing
Trace and map across multiple services

• See the end-to-end view and
navigate to individual transactions
• Based on the notion of a end-to-
end Trace ID across services
• Investigating compatibility with
OpenTracing API and aligning
with W3C trace context spec
Single transaction
Distributed tracing
Transaction
Span
Span
Span
HTTP request Response
Distributed tracing example
Distributed tracing
Trace A
Transaction 1
Span
Span
Span
Transaction 2
Span
Transaction 3
Span
Span
APM is another index in Elasticsearch
Need another visualization? Build a dashboard, no need to wait for your vendor
!41
DEMO
!42
What now?
Try it yourself!
!44
Come to Speaker AMA!
Questions?

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Logging, Metrics, and APM: The Operations Trifecta

  • 1. !1 Tanya Bragin Sept 2018 Logging, Metrics, and APM: The Operations Trifecta
  • 3. !3 Benefits of Logs + Metrics + APM in one stack
  • 4. !4 Unified Dashboards Same UI for KPI summaries and root cause analysis
  • 5. !5 Unified Alerting Trigger off any operational data to provide unified SLA monitoring
  • 6. !6 Unified Machine Learning Correlate multiple data sources for more intelligent anomaly detection
  • 7. !7 Operational gains Single technology for operational data saves on administrative costs
  • 9. Metrics vs Logs 64.242.88.10 - - [07/Mar/2017:16:10:02 -0800] "GET /mailman/listinfo/hsdivision HTTP/1.1" 200 6291 64.242.88.10 - - [07/Mar/2017:16:11:58 -0800] "POST /twiki/bin/view/TWiki/WikiSyntax HTTP/1.1" 404 7352 64.242.88.10 - - [07/Mar/2017:16:20:55 -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
  • 10. Making logging more turnkey with ‘modules’ • Turnkey experience for specific data types • Data to dashboard in just one step • Automated parsing and enrichment • Default dashboards, alerts, ML jobs
  • 11. Logging modules System • Linux / MacOS • Windows Events Containers • Docker • Kubernetes Databases • MySQL • PostgreSQL Queues • Kafka • Redis Web servers • Apache • Nginx Audit data • Filesystem • System calls WINLOGBEATFILEBEATAUDITBEAT Infrastructure Applications
  • 12. !12 Ad-hoc log search and visualization Kibana Discover, Visualize, Dashboard
  • 13. !13 Hot/Warm architectures in EC / ECE • One click hot-warm deployments • Shipped in EC in Aug 2018 • ECE support coming!
  • 15. Metrics vs Logs 64.242.88.10 - - [07/Mar/2017:16:10:02 -0800] "GET /mailman/listinfo/hsdivision HTTP/1.1" 200 6291 64.242.88.10 - - [07/Mar/2017:16:11:58 -0800] "POST /twiki/bin/view/TWiki/WikiSyntax HTTP/1.1" 404 7352 64.242.88.10 - - [07/Mar/2017:16:20:55 -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 07/Mar/2017 16:10:00 all 2.58 0.00 0.70 1.12 0.05 95.55 server1 containerX regionA
 07/Mar/2017 16:20:00 all 2.56 0.00 0.69 1.05 0.04 95.66 server2 containerY regionB
 07/Mar/2017 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 and print it out, and annotate with meta-data.
 Metrics are periodic measurements of numeric KPIs
  • 16. !16 Evolution of Elasticsearch into Metrics Store
  • 17. Elasticsearch for search and numerical analytics Inverted Index for full-text search Columnar store for structured data BKD Trees for numerical operations Rollups
  • 18. • Elasticsearch primarily used for application search • Lucene data structure: Inverted index Elasticsearch beginnings Circa 2010
  • 19. • Elasticsearch 1.0 evolves to support a columnar store (built on top of Lucene “doc values”) • Structured string and numerical data can be stored there for fast retrieval and summarization / analytics Elasticsearch evolving to support analytics ~ 2010 to 2014 https://www.elastic.co/blog/elasticsearch-as-a-column-store
  • 20. • Elasticsearch 5.0 adds more data structures for efficient storing and querying numbers (BKD Trees) • These structures become the default storage for numerical and geospatial data in Elasticsearch Elasticsearch storage efficiencies 2016 https://www.elastic.co/blog/searching-numb3rs-in-5.0 1-Dimension 2-Dimensions
  • 21. • Elasticsearch 6.0 improves Lucene sparse values storage efficiency (41.5% in Metricbeat index size) Elasticsearch storage efficiencies 2017 https://www.elastic.co/blog/minimize-index-storage-size-elasticsearch-6-0
  • 22. Rollup support for long-term retentions https://www.elastic.co/blog/data-rollups-in-elasticsearch-you-know-for-saving-space Added in Elasticsearch 6.3
  • 24. !24 Elastic Stack as a Metrics Solution
  • 25. Metrics modules System • Linux • MacOS • Windows • Perfmon Infrastructure Cloud • AWS • GCP • Azure • DigitalOcean • Alibaba Containers • Docker • Kubernetes Virtualization • vSphere PACKETBEATMETRICBEAT Network • Netflow • Packets • TLS Envelope Storage • Ceph LOGSTASHHEARTBEAT
  • 26. Applications Datastores • MySQL • PostgreSQL • MongoDB • Couchbase • Aerospike • Graphite Web servers • Apache • Nginx Other • HAProxy • Zookeeper Queues • Kafka • Redis • RabbitMQ Caches • Memcached Uptime • Heartbeat Custom apps • JMX/Jolokia • PHP-FPM • Golang Metrics modules PACKETBEATMETRICBEAT LOGSTASHHEARTBEAT
  • 27. Roadmap: New operational data sources New Beats, Logstash inputs and modules Default actions for existing modules Agentless Shippers • Cloud Monitoring (Azure, Amazon, GCP, …) • Security Analytics (Bro, Suricata, Sysmon,…) • Machine Learning jobs for Docker/Kubernetes • Default alerts for top 5 modules • Deploy as functions • Ship data without needing to tent to infrastructure
  • 28. • Correlate data from different sources • Ability to re-use analysis content • Ability to re-use Elastic-provided content Correlation between logs, metrics, and APM Benefits • Version 0.1 published: github.com/elastic/ecs • Working with internal groups to validate • Community feedback welcome! Status Elastic Common Schema
  • 29. Visualizing time series data Time Series Visual Builder
  • 30. Visualizing time series data Annotations
  • 32. What is APM? Example 08:32:10 Request "/api/checkout" 08.32:11 Response "/api/checkout 500 ERROR"
  • 33. What is APM? Example 08:32:10 Request "/api/products/top" 08.32:17 Response "/api/products/top 200 OK" 7 seconds - zZzzZZz
  • 34. How does APM work? Data processor apm-server Data storage elasticsearch Browser Agent Web server Agent Web server Agent Web server Agent UI kibana Browser Agent Browser Agent
  • 35. • Focuses on search experience on top of APM data • ‘Just another index’ in Elastic Stack Elastic APM APM adds end-user experience and application-level monitoring to the stack Language support ● Python
 ● Node.js
 ● Ruby (Beta)
 ● RUM (Beta) 
 ● Java (Beta) ● Go (Beta)
  • 36. Curated UI for APM Combine custom workflow with freedom of search
  • 37. Roadmap: Distributed Tracing Trace and map across multiple services
 • See the end-to-end view and navigate to individual transactions • Based on the notion of a end-to- end Trace ID across services • Investigating compatibility with OpenTracing API and aligning with W3C trace context spec
  • 39. Distributed tracing example Distributed tracing Trace A Transaction 1 Span Span Span Transaction 2 Span Transaction 3 Span Span
  • 40. APM is another index in Elasticsearch Need another visualization? Build a dashboard, no need to wait for your vendor
  • 42. !42
  • 43. What now? Try it yourself!
  • 44. !44 Come to Speaker AMA! Questions?