This research investigates the integration and effectiveness of two monitoring frameworks, the Four Golden Signals and the RED Method, with Argo Rollouts for automated deployments. The study aims to identify which framework integrates better with Argo Rollouts, compare their effectiveness in automating deployment procedures, and assess the impact of automated deployments on application performance. Experiments involve fault injections, such as HTTP 500 errors and delays, to evaluate the frameworks ability to detect unhealthy deployments and trigger rollbacks. Both frameworks were successfully integrated using Prometheus for metric collection and custom analysis templates for health assessment. The Four Golden Signals provided more comprehensive insights due to its additional metrics (saturation and latency), whereas the RED Method was simpler to configure and interpret. The findings highlight the importance of carefully calibrating metric thresholds to accurately identify unhealthy deployments. Future work suggests exploring Blue-Green deployments, investigating the robustness of systems under security breaches, and assessing cost savings from using Argo Rollouts over time.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-227103 |
| Date | January 2024 |
| Creators | Gustaf, Söderlund |
| Publisher | Umeå universitet, Institutionen för datavetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | UMNAD ; 1492 |
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