In summary, the webinar provided insights into measuring the impact of architectural changes on engineering metrics. It emphasized the importance of contextualized dashboards, success metrics, and guardrail metrics in tracking and evaluating changes. The examples illustrated how these metrics can help detect issues early and facilitate safe and efficient architectural transitions.
- Measuring the Impact of Architectural Changes: The webinar focused on the impact of architectural changes on engineering metrics and how to measure these impacts. It highlighted the importance of tracking the right metrics and using innovative approaches to gain valuable insights during architectural changes.
- Types of Architectural Changes: The presenter discussed various types of architectural changes, including feature development, code refactors, and platform migrations. These changes can range from small code modifications to large-scale transitions and require careful evaluation and monitoring.
- Engineering Metrics and Dashboards: The webinar emphasized the need for contextualized engineering metrics. Traditional dashboards provide an overall view of system health but lack the depth and visibility to make informed decisions. Contextualized dashboards that incorporate feature flagging can offer comparative insights, attribute changes to root causes, and provide actionable tools for analysis and problem-solving.
- Success Metrics and Guardrail Metrics: The webinar differentiated between success metrics and guardrail metrics. Success metrics track the usage and performance of specific code paths or features, while guardrail metrics ensure stability and detect any unexpected issues during architectural changes. Latency, error rates, and performance indicators were highlighted as crucial guardrail metrics.
- Examples of Applying Metrics: Two examples were presented to demonstrate the practical application of metrics in identifying issues and managing architectural changes effectively. The first example discussed how monitoring metrics helped identify a bug during a code refactor. The second example showcased a phased approach to platform migration, using dual writes and dark reads to minimize downtime and ensure data integrity.
Visit split.io to learn more about leveraging feature flagging for measuring engineering metrics and optimizing architectural changes.