Elastic Certified Observability Engineer Exam
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Certification for experts who can implement observability to monitor and react to events anywhere.
Course summary
The Elastic Certified Observability Engineer exam tests your knowledge and skills on using the Elastic Stack to implement observability, from ingesting metrics, logs, APM and uptime data to a single data source, to analyzing and reacting to events using Kibana, machine learning, and alerting.
To best prepare for this exam, we highly encourage participants to attend the Elastic Observability Engineer training course.
Check out our Certification FAQ for general questions or email
- Topics
- Audience
- Duration
- Pre-reqs
- Requirements
Topics
To be fully prepared for the Elastic Certified Observability Engineer exam, candidates should be able to complete all of the following exam objectives with only the assistance of Elastic documentation:
- Configure and run Heartbeat to determine the uptime of a process or service
- Use Heartbeat to determine if a service is reachable via ICMP, TCP or HTTP
- Use the Uptime app in Kibana to monitor the uptime and availability of a service
Metrics
- Install the Elastic Agent to collect metrics
- Enable and configure integrations to collect the metrics of a specific service
- Use the Metrics app in Kibana to analyze and answer questions about metrics collected in Elasticsearch
- Use the Metrics app to enable and analyze the predefined machine learning jobs
Logging
- Install the Elastic Agent to collect logs
- Enable and configure integrations to collect the logs from a specific service
- Enable and configure integrations to tail a given custom log file
- Use the Logs app in Kibana to analyze and answer questions about log events collected in Elasticsearch
- Use the Logs app to enable and analyze the predefined machine learning jobs
APM
- Use the APM app in Kibana to analyze and answer questions about APM data collected in Elasticsearch
- Use the Real Experience app in Kibana to analyze and answer questions about RUM data collected in Elasticsearch
- Edit and configure the APM integration
Structuring and Processing Data
- Use Kibana to edit or define an ingest node pipeline
- Configure the custom logs integration to use an ingest pipeline
- Define ingest node pipelines that use the various processors, including (but not limited to) append, convert, date, dissect, dot expander, geoip, grok, fail, json, remove, rename, set, and split
Working with Observability Data
- Find anomalies in Observability data using the predefined machine learning jobs in Kibana
- Define a machine learning job in Kibana on Observability data
- Define or edit an Index Lifecycle Management policy for indices
- Define an alert using Kibana Alerts
- Create dashboards that use visualizations based on Observability data
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