LaunchDarkly announced the private preview of Warehouse Native Experimentation, its Snowflake Native App, to offer Data Warehouse Native Experimentation.
Software deployment velocity directly impacts a business's bottom line — companies with higher release rates achieve 20% higher operating returns(link is external) than those pushing updates less often. The development field is becoming increasingly more competitive, with elite and high performing teams making up two-thirds of DevOps teams(link is external) for the first time in 2021. And the delta between higher performing teams and lower performing teams is growing. To keep up, companies need to innovate and improve their delivery cycle.
But speed alone is not enough to give companies a competitive advantage. Software functionality needs to satisfy customers' needs while also being stable and reliable because all it takes is one bad experience to turn users away from a brand. Once they are gone, they don't come back — PwC reports 32% of U.S. consumers(link is external) say they won't give brands a second chance.
Checking all the necessary boxes for a successful software update requires a continual and fast feedback loop. Continuous deployment and progressive deployment power the feedback cycle, providing DevOps teams with the knowledge they need to improve quality and speed up delivery.
Continuous Deployment as the Engine of Faster Feedback
Continuous deployment (CD) automatically deploys code from testing into a production environment. The process makes releasing updates reliable, predictable and repeatable, and frees developers from spending time troubleshooting deployment issues. Eliminating mundane and easily-automated tasks creates more time for coding quality software and bug fixes and lightens developers' workload, improving work quality, creating a greater sense of job satisfaction, and preventing burnout.
By automating deployments, CD accelerates software development and delivery. The faster and more frequently software is released, the quicker teams can receive feedback to identify and fix issues and push out a new update.
Progressive Deployment Fuels the Feedback Loop
Progressive deployment works similarly to continuous deployment, with the added benefit of progressive rollouts. Using strategies like canary and blue/green, the automated process pushes new production code to a small number of users and gradually increases the audience size while continually gathering real usage data on the update's health.
The progressive deployment cycle includes five steps.
1. Code development and testing with continuous integration (CI).
2. Automated integration testing in a staging environment.
3. Progressive deployment to production.
4. Data gathering to determine the health of the software.
5. Wider delivery of the application, if everything is working correctly.
Steps four and five repeat until all users receive the update. The process can roll back the release to a previously designated version if feedback reveals a problem at any point during deployment. This strategy limits the blast radius of the update, minimizing the number of people who receive substandard software and preventing outages that cost companies between $500,000 to $5 million per hour(link is external).
The continuously incoming information during progressive deployment identifies issues quickly, allowing for remediation while maintaining customers' quality of service. Because developers don't need to troubleshoot deployment problems, they can focus on writing code.
Progressive deployment ensures properly functioning software at each stage of development and delivery with limited developer involvement. The enhanced feedback cycle provides the agility to pivot when unexpected problems arise and the foresight to identify evolving user needs. By automating deployment and data gathering, development teams have the knowledge and time to create and quickly deliver higher quality software with the performance, features and stability necessary to satisfy customers.
Industry News
SingleStore announced the launch of SingleStore Flow, a no-code solution designed to greatly simplify data migration and Change Data Capture (CDC).
ActiveState launched its Vulnerability Management as a Service (VMaas) offering to help organizations manage open source and accelerate secure software delivery.
Genkit for Node.js is now at version 1.0 and ready for production use.
JFrog signed a strategic collaboration agreement (SCA) with Amazon Web Services (AWS).
mabl launched of two new innovations, mabl Tools for Playwright and mabl GenAI Test Creation, expanding testing capabilities beyond the bounds of traditional QA teams.
Check Point® Software Technologies Ltd.(link is external) announced a strategic partnership with leading cloud security provider Wiz to address the growing challenges enterprises face securing hybrid cloud environments.
Jitterbit announced its latest AI-infused capabilities within the Harmony platform, advancing AI from low-code development to natural language processing (NLP).
Rancher Government Solutions (RGS) and Sequoia Holdings announced a strategic partnership to enhance software supply chain security, classified workload deployments, and Kubernetes management for the Department of Defense (DOD), Intelligence Community (IC), and federal civilian agencies.
Harness and Traceable have entered into a definitive merger agreement, creating an advanced AI-native DevSecOps platform.
Endor Labs announced a partnership with GitHub that makes it easier than ever for application security teams and developers to accurately identify and remediate the most serious security vulnerabilities—all without leaving GitHub.
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GitHub announced a wave of new features and enhancements to GitHub Copilot to streamline coding tasks based on an organization’s specific ways of working.
Mirantis launched k0rdent, an open-source Distributed Container Management Environment (DCME) that provides a single control point for cloud native applications – on-premises, on public clouds, at the edge – on any infrastructure, anywhere.
Hitachi Vantara announced a new co-engineered solution with Cisco designed for Red Hat OpenShift, a hybrid cloud application platform powered by Kubernetes.