Progressive Delivery 🛠️

Learn how feature flags, canary releases, A/B testing, and observability contribute to safer and faster software deployment. Your regular intake of dev randomness! [Codeanywhere](%2F%2Fwww.codeanywhere.com%2F%3Futm_medium=email%26utm_source=newsletter%26utm_campaign=HT/1/0101018a93b52937-726208a0-04d7-47b2-9622-4192822b1459-000000/u1rnmkKOE4hmpioZuxaz-X-GGmQ=340) ISSUE #69 Hi there, I trust this message finds you well and coding happily this magnificent Thursday. I want to dig into a fascinating topic in the software delivery landscape that has been making waves in recent years: Progressive Delivery. Although it's not the newest kid on the block, its relevance and impact are undeniably significant. A Journey Through Time: Software Delivery Evolution How we deliver software has always been intrinsically linked to how software is distributed and consumed. In the early days, software and hardware releases were intertwined, suiting the long cycles of the waterfall methodology. As software became independent of hardware, agile methodologies emerged, offering the advantage of incorporating customer feedback via beta testing. Yet, with this approach, significant adjustments remained challenging as the development cycle advanced. The advent of Software-as-a-Service (SaaS) and cloud-native architectures paved the way for Continuous Delivery. This allowed for frequent automatic updates, but with a catch - potential bugs could immediately reach the entire user base. This dilemma brought forth an innovative concept: Progressive Delivery. Progressive Delivery Unveiled Progressive Delivery is essentially a controlled, phased approach to software delivery. It's designed to minimize the risks of releasing new features and updates by giving teams control over who sees what and when. Various mechanisms help achieve this, including: - Feature Flags: These are invaluable tools that enable developers to turn features on or off for specific user groups, offering a safety net for new releases. - Canary Releases: This approach involves initially rolling out updates to a small subset of users. The team can then monitor and address any issues before a full-scale release. - A/B Testing: This technique lets teams experiment with different feature versions and compare their performance. - Observability: Monitoring feature performance provides insights into user behavior and overall system health. - Rollbacks and Roll Forwards: In case of issues, quick reversions or advancements can be made without affecting the overall user experience. Why Progressive Delivery Makes Sense For developers, Progressive Delivery brings together the best of two worlds: speed and safety. New features can be rapidly pushed to production behind feature flags and then gradually rolled out based on readiness. This fosters a resilience mindset and empowers developers to focus on building features, free from the worry of immediate exposure. On the business front, Progressive Delivery offers control over feature exposure and rollout cadence. It enables product teams to utilize user feedback to drive iterations rather than merely react to issues. The result? Faster innovation, reduced risk, and better user engagement. Progressive Delivery in Action Many leading tech and non-tech companies have successfully integrated Progressive Delivery principles into their processes: - [IBM leverages feature flags](%2F%2Flaunchdarkly.com%2Fcase-studies%2Fibm%2F%3Futm_medium=email%26utm_source=newsletter%26utm_campaign=HT/1/0101018a93b52937-726208a0-04d7-47b2-9622-4192822b1459-000000/SVXyzQK4CBi0n-F2ABGu7UaIJfU=340) to manage updates across thousands of Kubernetes clusters. - [Amazon practices continuous deployment](%2F%2Faws.amazon.com%2Fbuilders-library%2Fautomating-safe-hands-off-deployments%2F%3Futm_medium=email%26utm_source=newsletter%26utm_campaign=HT/1/0101018a93b52937-726208a0-04d7-47b2-9622-4192822b1459-000000/s6udGweKSutUia-g0ptL2gxleH0=340), automatically deploying changes to production multiple times a day using pipelines. - [Comcast uses feature flags](%2F%2Fwww.split.io%2Fblog%2Fseries-c-announcement%2F%3Futm_medium=email%26utm_source=newsletter%26utm_campaign=HT/1/0101018a93b52937-726208a0-04d7-47b2-9622-4192822b1459-000000/QGWOULMUfFnNEtuBYMpleAb2ov8=340) and targeted rollouts to test changes in different regions. - [Capital One uses canary releases](%2F%2Fwww.capitalone.com%2Ftech%2Fcloud%2Fcanary-deployments-on-aws%2F%3Futm_medium=email%26utm_source=newsletter%26utm_campaign=HT/1/0101018a93b52937-726208a0-04d7-47b2-9622-4192822b1459-000000/HdN0ikbUHX5nRX_Pctow9QL6H84=340) to reduce the risk associated with frequent releases. These examples highlight how organizations across industries leverage Progressive Delivery to balance agility and control. What's Next for Progressive Delivery? Progressive Delivery has carved out a distinct space in the software development landscape, but it's not without its challenges. Success demands seamless collaboration among developers, ops, and business teams and solid workflow alignment. Despite these challenges, as we navigate an era of increasing digital transformation and software complexity, Progressive Delivery presents a promising path to balance agility with control. It serves as a cornerstone for the future of efficient, effective, and user-centric software delivery. Conclusion In conclusion, Progressive Delivery may not be a new trend. Still, it's a strategic approach in the software delivery ecosystem that helps teams deliver high-quality software with reduced risks and improved control. Here's to delivering quality software, progressively and effectively! %2F%2Ftwitter.com%2Fnibalic%3Futm_medium=email%26utm_source=newsletter%26utm_campaign=HT/1/0101018a93b52937-726208a0-04d7-47b2-9622-4192822b1459-000000/poXzia5BKVwuD4LMl9JxffZwQ8M=340 Niko - Codeanywhere team Your cheerful email mate Around the Web [ExLlamaV2: GPU Inference Library](%2F%2Fgithub.com%2Fturboderp%2Fexllamav2%3Futm_medium=email%26utm_source=newsletter%26utm_campaign=HT/1/0101018a93b52937-726208a0-04d7-47b2-9622-4192822b1459-000000/NxSR4nvVhZzHJwmrcP80v2TilhE=340) ExLlamaV2 is an initial release of an inference library for running local deep learning language models on consumer GPUs. Although it still requires extensive testing and tuning, it offers an exciting opportunity for developers. Visit the GitHub repository for more information. [The RedMonk Programming Language Rankings: January 2023](%2F%2Fredmonk.com%2Fsogrady%2F2023%2F05%2F16%2Flanguage-rankings-1-23%2F%3Futm_medium=email%26utm_source=newsletter%26utm_campaign=HT/1/0101018a93b52937-726208a0-04d7-47b2-9622-4192822b1459-000000/C_7fPxWUnfBk_fADBpEq0mq7XH0=340) Discover the latest language rankings report from RedMonk, covering the first quarter of 2023. This in-depth analysis provides insights into the popularity and usage of programming languages. Be sure to check out the comprehensive article for more details. [Beyond Metrics: Unlocking True Developer Potential](%2F%2Fwww.daytona.io%2Fdotfiles%2Fbeyond-metrics-unlocking-true-developer-potential%3Futm_medium=email%26utm_source=newsletter%26utm_campaign=HT/1/0101018a93b52937-726208a0-04d7-47b2-9622-4192822b1459-000000/l8r_2kXMdO2Fta3BEGmlHZssyTI=340) Create a culture of innovation and creativity. Metrics don't define excellence, people do. 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