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- Analyzed AWS RDS utilisation graphs to derive possible patterns of high utilization, which helped us narrow down the key hour wherein we had the highest utilization.
- Based on the metrics above we digged dug deep to analyze API response times and detailed trace of services using our distributed tracing setup, Jaeger.
- Several APIs were taking ~20-40s with majority of the time being spent querying the database; on analyzing the queries it was clear that they were not running optimally.
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- Nithin DV (Unlicensed) Partitioning strategy for tables (Time & Tenant Based and on kafka topics)
- Ghanshyam Rawat Nithin DV (Unlicensed) Tarun Lalwani Strategy plan to Index data based on columns of the tables, Query Optimisation
- Ghanshyam Rawat Nithin DV (Unlicensed) Tarun Lalwani DB Script review process plan
- Abhishek Jain, Nithin DV (Unlicensed) To review what kind of data being captures and logged by Jaeger tracing, logs should be masked (Important)
- Gajendran C (Unlicensed) Nithin DV (Unlicensed) Production infra alerting and dashboards (ES, Kafka, Zuul, Jaeger, DB) to the roadmap.
- Tarun Lalwani Come up with strategy to do basic performance testing on services
- Nithin DV (Unlicensed), Tarun Lalwani To come up with the proof point on the need for synchronous calls to solve the specific use case.
