Manage Kubernetes with Cloud Automation Services

With Kubernetes becoming mainstream, significant challenges around governance and management are arising: Operations team lack observability and platform-specific expertise to manage different teams using multiple clouds and stacks. They need a consistent approach to implement policies and processes no matter what is under the hood. Cloud Automation Services abstract the cloud and platform complexity to let you focus on adding value to the business.
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Spotlight

OTHER ON-DEMAND WEBINARS

Integrating Infrastructure Security and Compliance into CI/CD

Application teams are increasing their deployment velocity by moving security and compliance checks earlier in the software development life cycle (SDLC), when corrective changes are easier and faster to make. In this webinar, Josh Stella (Co-founder and CTO at Fugue) and Ricardo Green (Senior Solutions Architect) will walk thro
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AWS Developer Tools Live Lab Challenge

In this on-demand lab challenge, you will be guided through the AWS Developer Tools Challenge on Cloud Academy. Several tasks must be completed to complete the challenge using a continuous deployment stack built on AWS Developer Tools (CodePipeline, CodeBuild, CodeDeploy, API Gateway, Lambda). The Lab Challenge simulates troubleshooting and performing updates in a real-world scenario.
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The State of Hybrid Cloud Database Management

Join Phil Goodwin, IDC Analyst and Chris Paap, Sr. Solutions Marketing Manager at Nutanix, as they discuss new trends revealed in the latest IDC survey. Learn how organizations leverage hybrid clouds for their database strategies and how IT leaders and their organizations can realize improved performance, cost savings, and productivity.
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Featuring IBM Watson Machine Learning and Watson OpenScale: Automate and Operationalize AI

IBM

As organizations rush to innovate and modernize business with AI, one thing is clear. Just getting more insight in your business is no longer good enough. Your business needs fine-tuned foresight on what will happen next. At the heart of any prediction are production-ready models that are trustworthy, explainable and fully traceable. Furthermore, the ability to augment your data science and business teams with AI productivity and automation features is vital to business success. And, you need a simplified way of preparing and shaping data, building and training models and deploying them into production.
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