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Kubernetes and Artificial Intelligence/Machine Learning (AI/ML) — Four Things to Understand Today

Blue Sentry

Even if they do, many projects get stuck in the ever-so-fragile SDLC. When we look at ML deployments, there are a ton of different platform and resource considerations to manage, and CI/CD (Continuous Integration & Continuous Delivery) teams are often managing all of these resources across a variety of different microservices (i.e.,

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Cloud native architecture – the modern way to develop Software

Apiumhub

This new idea is based on JenkinsX that enables developers to deploy Kubernete’s microservices. Every cloud application has four important elements: “Continuous delivery, Containers, Dynamic Orchestration, and Microservices ”. Microservices. Microservices are cloud-oriented services that deal with different cloud operations.

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Software Engineering Daily: Feature Flags with Edith Harbaugh

LaunchDarkly

We have customers like IBM who use us to manage microservices. JM: They’re doing load balancing via feature flags? EH: Quality balancing too. It was from this idea that we would help people with a dark launch. What we found overtime is that feature flags are just so powerful. They do that via feature flags.