Agile Stacks Blog

Replay: Top3 Challenges of Scaling Kubernetes

Posted by John Morada on Jun 3, 2020 3:00:00 AM

Ever wanted to just see what others are doing to scale their Kubernetes clusters? Sometimes it's as simple as seeing what they've done that makes us better at what we do.

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Topics: Container, Infrastructure Automation, Kubernetes

Controlling your costs on AWS using the power of Agile Stacks

Posted by Sean O'Shaughnessey on May 28, 2020 3:08:00 AM

Agile Stacks is motivated to help our customers save money as they deploy the compelling Kubernetes container orchestration platform. We have had several customers save a significant amount of money using our ever-expanding capabilities of using AWS Spot Instances. For example, Zeeto reduced cloud costs by 75% by adopting the Agile Stacks DevOps automation platform SuperHub on AWS. The company completely automated the software delivery process using an infrastructure-as-code approach and maximized their savings by deploying on Spot Instances.

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Topics: Cloud, CTO, DevOps Automation, Infrastructure Automation

"Deep Survival": Thinking through it with your software infrastructure

Posted by John Morada on May 5, 2020 10:35:18 PM

“Training is an attempt to make predictions more accurate in a given environment. But as the environment changes (and it always does), what you need is versatility, the ability to perceive what’s really happening and adapt to it.” --Laurence Gonzalez, Deep Survival: Who Lives, Who Dies, and Why

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

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