As an educator and data scientist, Kubeflow gets your labs started fairly quickly

Posted by John Morada on Apr 12, 2020 6:18:00 PM

A recent search on Indeed.com shows an open request for data scientists at approximately 3,600 job postings. But being a data scientist doesn't mean needing to be an Ops engineer. There is a difference:

  • Data Scientist - as widely defined, is an individual with the primary role of sourcing data to be used in algorithmic and statistical analysis to identify trends, insights and other relevant information
  • Ops Engineer - aka Application Operations Engineer, is pragmatically the technical staff charged with the optimization, maintenance, monitoring and governance of in-production business systems.
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Topics: AI, DevOps Automation, Machine Generated Code, Machine Learning, Higher Education, Data Science

When to go big with a Kubernetes cluster(?) | Part 1

Posted by Rick Richardson on Jan 30, 2020 4:30:00 AM

In this three-blog series, let's figure out the strategic preparation and tactical automation that you need. We understand Kubernetes is powerful yet it takes some effort to get there.

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Topics: Business Agility, Business/IT alignment, CIO, Cloud, Cloud Computing, CTO, Infrastructure Automation, Kubernetes

A Case Study: With Kubernetes, the sum is greater than the parts for Zeeto.io

Posted by John Morada on Dec 13, 2019 12:01:20 AM

When it comes to automating a deployment pipeline, Agile Stacks delivers. Just ask Matt Ferguson, the CTO of Zeeto.io. The powerful combination of AWS services and native Kubernetes gave Matt and his team the assurances of running enterprise AI workloads to meet Zeeto’s growing customer needs.

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Topics: composable, composition, IT configuration management, open source software, OpenSource, Infrastructure Automation, Kubernetes

Buzzword bingo for software automation

Posted by John Morada on Nov 10, 2019 9:00:00 AM

Infrastructure as code (IaC) delivers the promise of agility and speed to IT Ops teams as well as developers. Yet new terms seem to be blended or, worse, misused in the context of what value can be achieved.

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Topics: Application Composition, Application Templating, Component, Component as a Service, Component based software engineering, Component Software, Componentization, composable, composition, DevOps, Ecosystem, Enterprise Applications, Enterprise Architecture, innovation, IT configuration management, open source software, OpenSource, Service Oriented Architecture, software development, Software Engineering, source code management, Full Stack Deployment, DevOps Automation, Infrastructure Automation, Kubernetes

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