Standing Up Progressive Delivery with Governance
Master the art of progressive delivery while minimizing risks and failures with this actionable guide.
Progressive delivery isn’t just a strategy; it’s a necessity for reducing risk in software deployment.Back to all posts
Your AI model just hallucinated in production, costing $50K in customer refunds. Or imagine a single line of legacy code bringing down your entire payment system during Black Friday. These scenarios aren't just hypothetical; they are the harsh realities that many engineering teams face today. As software complexity and
infrastructure grow, the risks associated with deploying new features escalate. Progressive delivery strategies like feature flags, canary releases, and blue/green deployments have emerged as essential tools to mitigate these risks. However, without proper governance, these techniques can lead to chaos rather than the
safety they promise. Engineering leaders must prioritize not just the technical implementation but also the governance frameworks that ensure these strategies work effectively.
Why is this critical? The change failure rate (CFR) is a metric that can make or break your team. According to industry benchmarks, teams that implement progressive delivery see CFR reduced by up to 30%. This directly impacts lead time and recovery time—two key metrics that reflect your team's operational maturity. A 5
% improvement in lead time can translate to significant revenue gains, especially in competitive markets. Governance ensures that your teams are not just deploying faster but also smarter, leading to a more resilient product.
### How to Implement It To effectively stand up progressive delivery with governance, follow these actionable steps: 1. **Establish Metrics**: Start by defining your key metrics—CFR, lead time, and recovery time. Use tools like Google Analytics and Grafana to monitor these metrics in real-time. 2. **Implement a Grad
ual Rollout Strategy**: Utilize feature flags for all new features. This allows you to control visibility on a per-user basis. Tools like LaunchDarkly or FeatureFlow can help manage these flags effectively. 3. **Set Up Canary Releases**: Deploy new features to a small subset of users first. Monitor their performance,
Key takeaways
- Implementing progressive delivery reduces change failure rates significantly.
- Governance mechanisms ensure safer rollouts and faster recovery times.
- Monitoring and metrics are crucial for maintaining operational stability.
Implementation checklist
- Establish clear metrics for change failure rate (CFR) and lead time.
- Implement feature flags for all new features.
- Set up canary releases with automated monitoring for early detection.
- Conduct regular reviews of governance policies and update as necessary.
Questions we hear from teams
- What is progressive delivery?
- Progressive delivery refers to techniques like feature flags, canary releases, and blue/green deployments that allow teams to roll out features gradually and manage risk.
- How do I measure change failure rate?
- Change failure rate can be measured by tracking the percentage of deployments that result in failures, such as incidents or rollbacks.
- What tools should I use for feature flags?
- Consider using tools like LaunchDarkly, FeatureFlow, or Unleash for effective feature flag management.
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