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Infrastructure monitoring made easy
From ingest to insight
Dimitri Mazmanov
Product Manager | Elastic Observability
Evolving Architectures ~↑ Monitoring Complexity
Hardware & software trends
are evolving in tandem
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
3
Requirements for a
monitoring solution
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
Core features and functionality
Needs from a monitoring solution
• Support the full stack
• Easily ingest from new sources
• Monitor dynamic ecosystems
• Ability to interact with your data
– Aggregations and visualizations
– Different views based on who is
looking
• Rich and flexible alerting
• Long term, reliable storage
• Bonus points for full Observability
6
Adding logs and metrics
to Elastic Observability
Multiple ingest paths
for observability streams
Instructions
right in Kibana
Several integrations
and the list is growing
• Download and install Metricbeat
and/or Filebeat
• Edit the configuration for destination
• Enable and configure the module
• Start the beats
• Explore!
Elastic Ingest Manager
Centralized ingest and configuration
• Deploy Elastic Agent
• Choose the integration type
• Register and configure the data source
• Specify the data you want to collect
• Explore!
Use your existing shippers
Core features and functionality
Your App
Prometheus
Exporter
Your App
Prometheus
Exporter
Metricbeat +
Elasticsearch
Prometheus
Server
Metricbeat +
Elasticsearch Azure Monitor
Autodiscover
Automatically monitor
new containers
• Perfect for dynamic ecosystems
• Automatically picks up new instances
• Works with K8s, Docker, AWS, etc.
• Hints based auto-discovery for K8s
• Full context backed by
Elastic Common Schema
Elastic Common Schema
Established, predictable fields
Text & Time Series Combined
• Inverted index + columnar store
• Powerful aggregations framework
• Optimized numeric field types (BKD
• Fast response even for
high-cardinality queries
• ILM & Data Rollups
• With all of the benefits of
the Elastic Stack
Powerful data store
14
The power of Elastic in your
observability initiative
Using your data to make
observability actionable
Out-of-the-box visibility
• Ship with most integrations
• Mix and match for your needs
• Leverage Kibana drilldowns for
custom navigation paths
• Of course, dedicated Metrics
and Logs apps
Dashboards & Visualizations
Metrics App
Birds-eye view or drill down
tail -f across your infrastructure ++
Logs App
Automatically detect and alert
• Many types of alerts
• Prefiltering based on context
• Multiple facets per alert
– CPU and Memory
– Network TX and RX
• Automatically split alerts on chosen
field (per container/pod/host)
• Deviations in logging rates
Integrated Alerting
Anomaly Detection
Automatically detect and alert
• Automate anomaly detection at
scale
and across disparate data sources
• Find patterns in your logs
• Automatically call out anomalies
and outliers
The power of the Stack
Use the Stack, Luke
• Flexible, composite visualizations
with Lens and TSVB
• Pixel-perfect infographics with
Canvas
• Multiple query options including
PromQL
• Data analytics based on ML
• Powerful Security
21
Tying it all together
Elastic Observability provides everything
that you need for infrastructure monitoring
Full Stack Support
Modules & Integrations
• Hosts, VMs, Containers
• Applications and Services
• Databases
• Message Queues
• Network / Audit
• And more
Easily add new sources
Out-of-the-box visibility
• Multiple out-of-the-box integrations
• Stackdriver (GCOS
• Azure Monitor
• CloudWatch
• Statsd
• Prometheus & OpenMetrics
• Just another index
– Business KPIs
– Sales vs error rates
Interact and interrogate your data
• Multiple perspectives, geared for
different users
• Flexible metrics exploration
• Integration with other observability data
streams
• Quickly create visualizations
• Flexible alerting...
Interactive, immersive UI
From multiple levels of detail
• Context-aware smart filtering
• Multiple detection criteria
dimensions
• Rich action options
• Built into your workflows
Flexible Alerting and ML
Leverage built-in data management
• Index lifecycle management
• Configurable redundancy
• Data rollups
• Highly available, distributed by nature
Long term, reliable storage
Needs from a monitoring solution
Core features and functionality
• Support the full stack
• Easily ingest from new sources
• Monitor dynamic ecosystems
• Ability to interact with your data
• Rich and flexible alerting
• Long term, reliable storage
• Bonus points for full Observability
Thank You

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Infrastructure monitoring made easy with Elastic Observability

  • 1. Infrastructure monitoring made easy From ingest to insight Dimitri Mazmanov Product Manager | Elastic Observability
  • 2. Evolving Architectures ~↑ Monitoring Complexity Hardware & software trends are evolving in tandem 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
  • 4. 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
  • 5. Core features and functionality Needs from a monitoring solution • Support the full stack • Easily ingest from new sources • Monitor dynamic ecosystems • Ability to interact with your data – Aggregations and visualizations – Different views based on who is looking • Rich and flexible alerting • Long term, reliable storage • Bonus points for full Observability
  • 6. 6 Adding logs and metrics to Elastic Observability Multiple ingest paths for observability streams
  • 7.
  • 8. Instructions right in Kibana Several integrations and the list is growing • Download and install Metricbeat and/or Filebeat • Edit the configuration for destination • Enable and configure the module • Start the beats • Explore!
  • 9. Elastic Ingest Manager Centralized ingest and configuration • Deploy Elastic Agent • Choose the integration type • Register and configure the data source • Specify the data you want to collect • Explore!
  • 10. Use your existing shippers Core features and functionality Your App Prometheus Exporter Your App Prometheus Exporter Metricbeat + Elasticsearch Prometheus Server Metricbeat + Elasticsearch Azure Monitor
  • 11. Autodiscover Automatically monitor new containers • Perfect for dynamic ecosystems • Automatically picks up new instances • Works with K8s, Docker, AWS, etc. • Hints based auto-discovery for K8s • Full context backed by Elastic Common Schema
  • 13. Text & Time Series Combined • Inverted index + columnar store • Powerful aggregations framework • Optimized numeric field types (BKD • Fast response even for high-cardinality queries • ILM & Data Rollups • With all of the benefits of the Elastic Stack Powerful data store
  • 14. 14 The power of Elastic in your observability initiative Using your data to make observability actionable
  • 15. Out-of-the-box visibility • Ship with most integrations • Mix and match for your needs • Leverage Kibana drilldowns for custom navigation paths • Of course, dedicated Metrics and Logs apps Dashboards & Visualizations
  • 16. Metrics App Birds-eye view or drill down
  • 17. tail -f across your infrastructure ++ Logs App
  • 18. Automatically detect and alert • Many types of alerts • Prefiltering based on context • Multiple facets per alert – CPU and Memory – Network TX and RX • Automatically split alerts on chosen field (per container/pod/host) • Deviations in logging rates Integrated Alerting
  • 19. Anomaly Detection Automatically detect and alert • Automate anomaly detection at scale and across disparate data sources • Find patterns in your logs • Automatically call out anomalies and outliers
  • 20. The power of the Stack Use the Stack, Luke • Flexible, composite visualizations with Lens and TSVB • Pixel-perfect infographics with Canvas • Multiple query options including PromQL • Data analytics based on ML • Powerful Security
  • 21. 21 Tying it all together Elastic Observability provides everything that you need for infrastructure monitoring
  • 22. Full Stack Support Modules & Integrations • Hosts, VMs, Containers • Applications and Services • Databases • Message Queues • Network / Audit • And more
  • 23. Easily add new sources Out-of-the-box visibility • Multiple out-of-the-box integrations • Stackdriver (GCOS • Azure Monitor • CloudWatch • Statsd • Prometheus & OpenMetrics • Just another index – Business KPIs – Sales vs error rates
  • 24. Interact and interrogate your data • Multiple perspectives, geared for different users • Flexible metrics exploration • Integration with other observability data streams • Quickly create visualizations • Flexible alerting... Interactive, immersive UI
  • 25. From multiple levels of detail • Context-aware smart filtering • Multiple detection criteria dimensions • Rich action options • Built into your workflows Flexible Alerting and ML
  • 26. Leverage built-in data management • Index lifecycle management • Configurable redundancy • Data rollups • Highly available, distributed by nature Long term, reliable storage
  • 27. Needs from a monitoring solution Core features and functionality • Support the full stack • Easily ingest from new sources • Monitor dynamic ecosystems • Ability to interact with your data • Rich and flexible alerting • Long term, reliable storage • Bonus points for full Observability