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Gabriel Moskovicz
Solution Architect
April 15th
Logs, Metrics, and APM for
Unified Observability
Elastic Enterprise Search Elastic SecurityElastic
Observability
Logs Metrics APM Uptime
Elastic Observability
4
#ObservaBLT
Observability
=
+
+
Higher resource utilization
increases monitoring complexity
• Orchestration/Hypervisor
• Dynamic/ephemeral jobs
• You can no longer "point" to where
that job lives

Shift to cloud-native yields
maintainable code, with costs
• Traditional licensing models don't
scale as well as your applications
• Hurdles with autoscaling
Monitoring Complexity
Hardware & software trends are evolving in tandem
Evolving Architectures ~↑ Monitoring Complexity
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
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
Observability is a search use case
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
Unified User Interface
Same UI for KPI summaries and root-cause analysis
Correlate multiple data sources for more intelligent anomaly detection
Unified Machine Learning
Trigger off any operational data to provide unified SLA monitoring
Unified Alerting
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.
Elastic Stack for logs
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
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 UI: 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
Elastic Stack for metrics
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
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
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
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
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
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
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
Infrastructure Metrics UI
Containers, hosts, services, cloud monitoring,
ad-hoc metrics exploration
Elastic Stack for APM
28
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 open tracing enabled with
Distributed tracing, added Go Agent,
integrated UI with Logs & Metrics
6.6
Elastic APM GA
Agents for Python, Node.js, Ruby, Javascript;
Real User Monitoring
Beyond
APM Agents
• Easy to add to your applications
• Multiple Language Support
• Designed to be lightweight
• Open source
• Support distributed tracing
• OpenTracing compatible
Auto-instrumentation of common programming frameworks
31
Elastic Stack for uptime
Heartbeat: Uptime Monitoring
• 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
35
Demo
What now?
Try it yourself!
While you monitor, why not protect?
Elastic SIEM
Come to the AMA booth!
Questions?

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Combinação de logs, métricas e rastreamentos para observabilidade unificada

  • 1. Gabriel Moskovicz Solution Architect April 15th Logs, Metrics, and APM for Unified Observability
  • 2. Elastic Enterprise Search Elastic SecurityElastic Observability
  • 3. Logs Metrics APM Uptime Elastic Observability
  • 5.
  • 6. Higher resource utilization increases monitoring complexity • Orchestration/Hypervisor • Dynamic/ephemeral jobs • You can no longer "point" to where that job lives
 Shift to cloud-native yields maintainable code, with costs • Traditional licensing models don't scale as well as your applications • Hurdles with autoscaling Monitoring Complexity Hardware & software trends are evolving in tandem Evolving Architectures ~↑ Monitoring Complexity
  • 7.
  • 8. 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
  • 9. 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
  • 10. Observability is a search use case
  • 11. 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
  • 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.
  • 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 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 UI: 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
  • 19. Elastic Stack for metrics
  • 20. 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
  • 21. 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
  • 22. 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
  • 23. 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
  • 24. 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
  • 25. 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
  • 26. 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 Infrastructure Metrics UI Containers, hosts, services, cloud monitoring, ad-hoc metrics exploration
  • 28. 28 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 open tracing enabled with Distributed tracing, added Go Agent, integrated UI with Logs & Metrics 6.6 Elastic APM GA Agents for Python, Node.js, Ruby, Javascript; Real User Monitoring Beyond
  • 29. APM Agents • Easy to add to your applications • Multiple Language Support • Designed to be lightweight • Open source • Support distributed tracing • OpenTracing compatible Auto-instrumentation of common programming frameworks
  • 30.
  • 33.
  • 34. • 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
  • 36. What now? Try it yourself!
  • 37. While you monitor, why not protect? Elastic SIEM
  • 38. Come to the AMA booth! Questions?