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Deployment Strategy Trade-offs

5 questions · Progressive Delivery Language

1. A team historically does "big bang deployments." An architect proposes switching to progressive delivery. What is the core risk of a big bang deployment?

Big bang deployments are slower to execute than progressive delivery strategies If a bug is introduced, 100% of users are affected immediately — there is no partial exposure phase to detect problems before they reach the full user base Big bang deployments require more engineers to coordinate and are more expensive to operate

2. An engineer uses the term "blast radius" during a deployment planning meeting. In this context, what does blast radius mean?

The geographic area affected by a cloud region outage during a deployment The scope and scale of impact if the deployment fails — how many users are affected, which features are broken, and for how long The number of microservices that need to be redeployed as part of a single release

3. A DORA report mentions "change failure rate" as a key DevOps metric. What does change failure rate measure?

The percentage of deployments that fail to complete successfully due to pipeline errors The percentage of changes to production that result in a degraded service requiring remediation (hotfix, rollback, or patch) The rate at which change requests are rejected during code review

4. An engineering manager is asked by a non-technical director: "Why does it take so long to deploy? Can't we just push the code?" How should the manager frame the value of progressive delivery?

"We need additional time because our deployment pipeline has too many manual approval steps that we have not been able to automate yet." "Progressive delivery allows us to deploy safely and frequently — by validating each change against real traffic before full exposure, we reduce the risk of outages that would cost far more in lost revenue and customer trust than the extra deployment time." "Regulatory compliance requires us to follow a staged rollout process with sign-offs at each stage."

5. A team evaluates whether to use blue-green deployment or a canary release for their next major API update. Which statement best describes when canary is preferable to blue-green?

Canary is always preferable because it provides both gradual rollout and instant rollback, making blue-green obsolete Canary is preferable when you want to validate the new version under real production load gradually; blue-green is preferable when you need instant, all-or-nothing cutover with zero-downtime and a ready rollback target Blue-green is always preferable for API changes because APIs cannot handle partial traffic splits

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