What is progressive delivery?
Progressive delivery is a modern approach to software delivery that emphasizes the controlled and gradual release of software features to specific user segments. This strategy allows development teams to validate new changes with a subset of users before rolling them out to the entire user base. By using progressive delivery, organizations can limit the blast radius of a change, which reduces risk, helps identify issues early, and creates continuous feedback loops, which are crucial for making data-driven decisions about feature acceptance and potential adjustments.
In contrast to traditional deployment methods, progressive delivery minimizes disruption and enhances user experience. It uses techniques like feature flags, canary releases, and A/B testing. These techniques allow developers to test features in a real-world environment with actual user interactions, providing valuable insights into user behavior and feature performance. As software becomes more complex and user expectations rise, adopting progressive delivery helps organizations remain competitive and responsive to market needs.
This is part of a series of articles about software deployment.
Evolution of progressive delivery
Progressive delivery has roots in traditional deployment methodologies but evolved as a response to the growing complexity of modern software development and the demand for faster, more reliable releases. Earlier practices, such as manual deployment and big-bang releases, often led to extended downtime, higher failure rates, and limited scope for experimentation. These challenges drove the adoption of agile methods and DevOps practices, setting the stage for more incremental and iterative approaches to delivery.
The concept of progressive delivery emerged as an extension of Continuous Delivery, emphasizing the automation of release processes and the ability to manage risk through phased rollouts. Tools like feature flags and canary deployments became crucial, allowing teams to control the exposure of new features to users while maintaining system stability. Over time, organizations began integrating monitoring and feedback mechanisms, further enhancing their ability to adapt releases based on user behavior and real-world performance.
Today, progressive delivery represents a convergence of technical innovations and strategic methodologies. It aligns with lean and agile development principles, focusing on delivering value incrementally while fostering collaboration between development, operations, and business teams.
Key components of progressive delivery
Feature flags
Feature flags let developers toggle specific features on or off without deploying new code. This control over feature exposure allows teams to conduct experiments, perform A/B testing, and release updates gradually, improving the development process’s flexibility. Using feature flags, teams can isolate new features and validate them under real-world conditions, reducing the impact of potential failures and ensuring a smoother user experience.
Feature flags also improve collaboration between development and operations teams, aligning technical efforts with business objectives. They empower non-technical stakeholders by giving them control over which features are live, fostering a more agile and responsive approach to development.
Blue/green deployments
Blue/green deployments reduce downtime during software releases by maintaining two identical production environments—blue and green. The existing production environment runs on one, while new updates are deployed to the other. Once the new version is tested and verified, traffic is switched from the old version to the new one, ensuring a seamless transition with minimal risk of disruption. This process ensures user experience remains largely unaffected during updates.
This deployment strategy provides a reliable rollback mechanism, as reverting to the previous version is instant and straightforward should any issues arise with the new release. By enabling an easy switch between environments, blue-green deployments enhance reliability and operational continuity.
Canary releases
Canary releases are a method wherein a new software version is deployed to a small group of users before a full rollout. This approach allows teams to monitor the new version’s performance and behavior, ensuring it meets the desired criteria before broad deployment. By releasing to a subset of users, organizations can identify and resolve issues early, minimizing risks and ensuring a more stable release process. Canary releases thus play a critical role in validating features and maintaining system reliability.
Canary releases provide a practical way to gather insights and feedback from real-world usage, offering a richer context for decision-making processes. The data gathered from canary releases can guide further improvements and help teams prioritize issues based on their impact.
A/B testing
A/B testing in progressive delivery involves comparing two versions of software to determine which performs better according to defined metrics. By exposing different user groups to different feature sets, this technique helps organizations measure user response and engagement, leading to data-informed decisions about feature implementations. As part of a progressive delivery approach, A/B testing can significantly improve feature adoption and overall product success.
This method provides actionable insights into user preferences and behavior, guiding developers to optimize features for improved satisfaction and performance. By iterating based on user feedback, teams can enhance product offerings in alignment with user needs and expectations.
Observability and monitoring
Observability and monitoring are crucial for implementing progressive delivery. They offer visibility into system performance and user interactions with new features. These practices involve collecting, analyzing, and acting on metrics that inform decision-making throughout the delivery process. Enhanced observability ensures teams detect anomalies and issues quickly, allowing them to respond swiftly and maintain system integrity.
With monitoring tools, organizations can track key performance indicators and user reactions to changes in real-time. This fast feedback loop is critical for continuous improvement, helping teams to refine operations and enhance feature effectiveness based on actual user data.
Tony Kelly is a DevOps marketing leader who drives innovation and awareness of the latest trends in Continuous Delivery.
Benefits of progressive delivery
Progressive delivery offers significant advantages by letting teams deploy software updates in a controlled and iterative manner. Below are the key benefits of adopting progressive delivery:
- Risk mitigation: Gradual rollouts, supported by techniques like canary releases and feature flags, help detect and resolve issues early, preventing widespread disruptions and enhancing system stability.
- Faster feedback loops: Incremental releases allow organizations to collect real-time user feedback, enabling rapid iterations and data-driven improvements to features.
- Improved user experience: Thorough testing in smaller user segments reduces the likelihood of bugs and ensures new features are optimized, providing a seamless experience for all users.
- Enhanced flexibility: Features can be toggled on or off as needed, allowing teams to respond quickly to changing priorities or unforeseen challenges without redeploying code.
- Cross-team collaboration: Shared visibility into feature rollouts fosters alignment between technical and business teams, allowing for more informed and collaborative decision-making.
- Cost efficiency: Identifying and addressing issues early reduces the expense of fixing bugs or failures in production, optimizing the overall development budget.
Progressive delivery versus Continuous Delivery and Deployment
While progressive delivery builds on principles established by Continuous Delivery and Continuous Deployment, it introduces a more nuanced approach to managing feature rollouts and risk.
Continuous Delivery focuses on automating and streamlining the release process so that software updates can be deployed to production at any time. The primary goal is to ensure that code is always in a deployable state, with thorough testing and quality checks integrated into the pipeline. However, Continuous Delivery doesn’t dictate how new features are exposed to users, leaving it up to you to decide the rollout strategy.
Continuous Deployment takes automation further by automatically pushing every successful change through the pipeline into production. This practice eliminates manual steps, accelerating the release cycle. While efficient, Continuous Deployment assumes a high degree of confidence in the stability and quality of every release, as it provides limited flexibility for managing risk during rollouts.
Progressive delivery emphasizes phased feature rollouts, allowing organizations to manage risk more effectively while gathering real-world feedback. Using feature flags, canary releases, and other techniques, progressive delivery enables teams to test new features with smaller user groups and expand exposure gradually based on performance and feedback. This targeted approach reduces the likelihood of widespread issues and provides greater control over the user experience.
Challenges in implementing progressive delivery
Technical complexity
Technical complexity is a significant challenge in implementing progressive delivery. The approach requires sophisticated tooling and infrastructure to manage feature flags, execute canary releases, and conduct real-time A/B testing. Teams need to implement robust systems to handle the intricacies of dynamic feature toggling and ensure consistent performance across all segments and environments.
Managing feature rollouts at different stages adds layers of complexity to the software delivery pipeline. This complexity necessitates a proficient understanding of modern deployment practices and the ability to integrate diverse technologies seamlessly.
Cultural and organizational shifts
Adopting progressive delivery often requires significant cultural and organizational shifts. Teams must embrace a mindset that prioritizes iterative development, collaboration, and continuous learning. Transitioning to this approach can be challenging, particularly in organizations with entrenched, traditional processes and workflows.
Successful implementation of progressive delivery involves fostering a collaborative culture where all stakeholders are engaged and aligned with strategic objectives. This cultural shift emphasizes openness, agility, and shared accountability, supporting continuous improvement and innovation. Organizations must invest in training and change management initiatives to facilitate this transition.
Tooling and infrastructure requirements
Progressive delivery necessitates sophisticated tooling and infrastructure, posing a challenge for many organizations. Implementing and managing tools for feature flagging, canary deployment, and real-time monitoring requires technical expertise and investment. Organizations must evaluate and integrate technologies that support these practices while maintaining system compatibility and security.
Additionally, effective progressive delivery demands an infrastructure capable of supporting simultaneous rollouts across different environments and user segments. Organizations must ensure their infrastructure is scalable and resilient enough to accommodate the dynamic nature of progressive delivery.
Best practices for implementing progressive delivery
1. Start with small, controlled audiences
Initiating new feature rollouts with a limited user base allows teams to monitor performance and user feedback closely. This approach helps mitigate risk by identifying potential issues early and providing an opportunity to make necessary adjustments before a wider release.
Engaging with a controlled audience offers valuable insights into user experiences, enabling teams to understand how new features are received and perform under real-world conditions. These insights drive data-informed decisions that improve the quality and impact of future feature rollouts, contributing to a refined and reliable progressive delivery process.
2. Automate deployment processes
With automated deployments, organizations can make sure software deployments are reliable and repeatable. Manual deployments are high risk, error-prone, and slow and internal scripted solutions often come with a heavy maintenance burden. Automation provides a stable deployment process, environment progression, and variable substitution so teams can focus on innovation and feature improvements.
Deployment automation ensures that new software versions are delivered seamlessly and predictably across environments. This predictability is crucial for maintaining user trust and satisfaction, making automation a core component of effective progressive delivery.
3. Implement robust monitoring and observability
Robust monitoring and observability are vital for achieving effective progressive delivery. Implementing these practices ensures teams have the visibility required to assess system performance and user interactions quickly. Monitoring tools provide real-time data on key metrics, facilitating prompt identification of abnormalities and issues during feature rollouts.
Observability supports proactive insights by providing in-depth analytics into how systems and users are interacting with features. These insights help teams make informed decisions about feature improvements and adjustments based on precise data.
4. Prepare for quick rollbacks
Preparing for quick rollbacks is a critical aspect of effective progressive delivery. Ensuring that teams can swiftly revert to previous stable states in the event of issues is essential for minimizing disruption and safeguarding user experience. Implementing strategies such as feature toggles and maintaining parallel production environments supports rapid rollback processes, offering fail-safes during deployment anomalies.
A well-prepared rollback plan helps organizations mitigate the impact of unforeseen challenges, reducing potential downtime and maintaining service continuity. When development teams can rollback easily, they can confidently experiment with new features, knowing that they can protect user experience if unforeseen problems occur.
5. Foster a culture of continuous learning
A key benefit of progressive delivery is using an experimental approach to build a deeper understanding of users. For this to happen, the organization needs a culture of psychological safety and continuous learning. Limiting the ability to collaborate and experiment prevents crucial discoveries and reduces the organization’s competitiveness.
Progressive delivery lets teams test ideas in the real world instead of through interviews or wireframes. It reveals how users really behave instead of how they think they will respond to a feature or redesign. What teams and organizations learn from this approach will give them a competitive edge and help them discover and adapt to market demands and technological advancements.
Progressive delivery with Octopus
At Octopus Deploy, we’re all about making Continuous Delivery (CD) easier and faster for software teams. Fast, repeatable, and reliable deployments to improve software delivery performance and provide faster turnaround times for feedback on new features or experiments.
Octopus seamlessly handles software delivery across multi-cloud, Kubernetes, data centers, and hybrid setups. We’re also big on governance, risk, and compliance (GRC), helping Platform Engineering teams enhance the Developer Experience (DevEx).
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