Volume 1 Issue 3 | 2024 | View PDF
Paper Id:IJMSM-V1I3P107
doi: 10.71141/30485037/V1I3P104

Foundations of Observability Engineering

Shekhar Jha

Citation:
Shekhar Jha, "Foundations of Observability Engineering" International Journal of Multidisciplinary on Science and Management, Vol. 1, No. 3, pp. 45-47, 2024.

Abstract:
Our global and dynamic life is reliant on behavior in complex systems. Observability engineering provides the means and tools to understand how these systems work, are not working and are healthy. It describes basics of metrics, logs and traces, and how to collect, work with and visualize data streams. This includes real-world design issues for observable systems like selecting appropriate metrics, logging and tracing apps, and good alerting. And segmented by metrics terms like Mean Time to Detect (MTTD), Mean Time to Resolve (MTTR), Change Failure Rate (CFR) etc.

Keywords: Observability, Metrics, Logs, Traces, MTTD, MTTR, AI/ML-Powered Observability.

References:
1. Aditya Pawar, The Three Pillars of Observability: Metrics, Logs and Traces, eginnovations, 2024. Online: https://www.eginnovations.com/blog/the-three-pillars-of-observability-metrics-logs-and-traces/
2. Sonja, API Observability Dashboard with OpenTelemetry and Grafana, Tyk 5.7, 2023. Online: https://community.tyk.io/t/api-observability-dashboard-with-opentelemetry-and-grafana/6580
3. AI-Powered Observability, logz.io. Online: https://logz.io/platform/
4. What is MTTD? Why does it matter for ITOps?, BigPanda, 2024. Online: https://www.bigpanda.io/blog/what-is-mean-time-to-detect-mttd/
5. What is Observability Engineering?, Dynatrace. Online: https://www.dynatrace.com/knowledgebase/observability-engineering