SRE Implementation

The Objective
It is currently usual to have a diverse technical landscape. Similarly, Singlife’s technological stack differed between platforms. Different teams oversaw their systems, but there were obstacles as well.
The following are a few of them:
The following are a few of them:
- Because there was no "single view" of all the systems, reducing the mean time to recovery (MTTR) was difficult.
- The objectives for the service level were not established.
- Lack of visibility into issues and outages affecting third-party services.
- The extent to which performance might be improved was unknown.
The Challenge
It was not an easy task to narrow down impacted services during unplanned outage.
The Solution
Taking “If you can’t measure it, you can’t improve it” as the first principal of SRE, we introduced a scalable system wherein:
- All internal and external systems will be closely monitored at all times.
- Metrics were recorded, and service level goals were established.
- An overview of the entire ecology.
- Introduced latency monitoring and set up notifications in the event of a violation.
- Uptime monitoring was implemented to detect and mitigate any unplanned outages.
- For enhanced alerting and escalation capabilities, we integrated our SRE system with the sophisticated incident response orchestration platform.
- To give a coherent perspective, we employed a variety of tools and technologies.
The Results
- Every system, both internal and external, will be constantly monitored.
- Metrics were kept track of, and service level goals were set.
- View of the entire biosphere from a single vantage point.
- Latency monitoring was implemented, with alarms set up in the event of a breach.
- Uptime monitoring was implemented to detect and mitigate any unplanned outages.
- For enhanced alerting and escalation capabilities, we integrated our SRE system with a sophisticated incident response orchestration platform.
- AWS Lambda functions for modifying alarm behaviour. Grafana for visualization. Cloudwatch for monitoring cloud-native metrics.
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Performance Metrics
- Singlife increased its stability and over three months, we were able to reduce errors to less than 1%.
- Over three months, we also attempted to achieve an API latency of less than one second.
About Client & Client Feedback
Singlife is a well-reputed finance firm in the region known for its credibility and authenticity. Scalable System implementation proved to be quite a success for them as they witnessed less errors in the operations and workflow.

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