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

Blue Sentry

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., Kubernetes & ML. Contact us to learn more.

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AIOps and our Robot Kubernetes Kops

Linux Academy

While Machine Learning is just a subset of true Artificial Intelligence vendors of infrastructure automation have coined a new buzz acronym, AIOps. The popularity of agile development, continuous integration, and continuous delivery has brought levels of automation that rival anything preciously known.

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4 Rs for Scaling your testing? The first steps towards a rewarding engagement

Trigent

Many of these like deployment frequency, error rates at increased load, performance & load balancing, automation coverage of delivery process and recoverability helps to ascertain the efficiency of QA scale up.

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Software Engineering Daily: Feature Flags with Edith Harbaugh

LaunchDarkly

Edith joins the show to discuss how to implement feature flagging, why an intelligent release process can lead to a more scientific predictable environment for software development and many other topics. Isn’t that just config files and isn’t that just a feature itself in like a continuous delivery platform or a cloud provider?