With the huge growth of “online” and “digital”, the importance of scalability and maintainability has become more crucial than ever. Users expect their online platforms and apps to be always available, and always improving with new features. And of course all of this without ever failing or having issues like bugs.
This puts huge pressure on the business side of organizations to continuously improve and innovate, without failing. In turn, this pressure is also funneled to the IT departments like software development and operations.
Because of this mutually exclusive pressure-cooker, where on the one hand we need to innovate and improve as quickly as possible, but on the other hand, there is (still) no acceptance for failure, a lot of friction, and trust-issues are happening between development, operations, and business.
Even with new developments like DevOps culture, agile methodologies, and microservice-based architectures, there is still a lot that can be improved in the working relationship between development, ops, and business.
With the focus on introducing all kinds of promising new technologies, the importance of first defining a good process is often forgotten.
One of the most overlooked and valuable processes is what a product-manager would call “controlled Go Live”: in what way an update or new feature is being released to end-users to avoid any downtime and maximize quality. This can be user-segment based, percentage-based, geo-based, device-based, or any other combination of Layer7-related information to filter, segment or redirect upon. Combine this with observing and responding to all relevant metrics, both technical and business-related, like analytics and other quality indicators.
When implementing this automated process of “controlled GoLive” to achieve a higher quality of software releasing, a logical new functionality appears on the radar: if we can automate it, can we also make it “self-service” for either internal stakeholders like product managers, but also for end-users? Where they can decide when to upgrade, and the software implements all the automated steps and validations, using cloud-native technologies like OpenTelemetry, MachineLearning, service-meshes, ingresses and Kubernetes events.
In this talk, we are going to describe how this kind of “controlled GoLive” features, combined with self-service patterns, can bring together the worlds of developers, operations, and business by increasing trust, information-sharing and cloud-native automation.
https://gateway.on24.com/wcc/eh/2010041/lp/2714291/vamp-how-cloud-native-traffic-shaping-technologies-can-bring-devops-and-business-together
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