Resilience Coverage

Resilience Coverage is a metric that quantifies the protection level of a pull request against bugs that can impact a significant portion of your user base and/or expose gaps in observability. 
Resiliance Coverage screenshot

Today’s Challenge

Shepherdly takes a fresh approach on creating high quality and resilient code by measuring risk and resilience and providing an adaptive set of mitigations for the author to follow directly into the PR, based on the risk of a code change.

One Size Fits All Compliance

Developers want nuanced guidance.

It’s common for teams to use heuristics for PR checks or static checklists. Using the same quality gate for all changes creates fatigue and notable efficiency loss.

Prioritizing PR Reviews

Review workload for senior engineers is already considerable. Developer co-pilots are accelerating that. 

An advanced mechanism to quickly assess risk and resiliency is needed in order to differentiate routine from high-risk changes.

Speed vS Resiliency tradeoffs

How much velocity does it cost to achieve your quality goals?

Is cutting some corners getting you the speed you want?

Teams are conscious of the balance, but lack metrics to monitor outcomes empirically. Cycle Time, Bug Rate, and Resilience Coverage are exportable to non-engineering stakeholders and empower teams to guide their organizations in customer first terms.

Our Philosophy

Risk-based decision making doesn’t mean going slow. It empowers you to move at your own pace with the added dimension to clarify the likely outcomes, objectively.
Instantaneous, objective, and automated risk analysis in the dev flow, encourages a more disciplined and data-driven approach to coding.

Since the Risk Score is trained exclusively on your team's PR history, the score is a reflection of what patterns and behaviors have and have not led to buggy code.
Resilience Coverage and Risk Scores enable teams and other stakeholders to codify the right amount of risk management per team. Some teams should go fast, others need deeper risk decisions.

Using cycle time, that mix can then be measured for its effect on delivery velocity. Demystifying this trade-off is incredibly useful for framing the realities of software development to stakeholders outside of engineering.