Mateusz Suski
fcf305bd70
- fix runner configuration issues - correct workflow labels and execution environment - resolve dependency issues in pipeline (python deps) - improve reliability of automation runs
31 lines
1.0 KiB
Markdown
31 lines
1.0 KiB
Markdown
# Observability Stack Architecture
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## Components
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- Filebeat: tails sample and container logs.
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- Logstash: receives and processes log events.
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- Elasticsearch: stores searchable observability data.
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- Kibana: supports log exploration and dashboards.
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- Grafana: provides operational dashboards.
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- Alert rules: document symptoms, thresholds, and severity.
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- Incident simulation: generates controlled failure signals.
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## Data Flow
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```
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Log source -> Filebeat -> Logstash -> Elasticsearch -> Kibana
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v
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Grafana
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```
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Incident exercises follow this flow:
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```
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Operator -> incident_simulation.sh -> logs/incident_simulation.log -> Filebeat -> Logstash -> alerts/dashboards
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```
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## Notes
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This is a local demonstration stack, not a production Elasticsearch deployment. A production version would add dedicated nodes, TLS, secret management, retention policies, index lifecycle management, and external alert delivery.
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