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9 Free Azure Training Resources

ParkMyCloud

If you’re looking to tune up your Microsoft Azure knowledge, contemplating a cloud computing career, or want to show value to a potential employer, there’s never been a better time than now to seize the opportunity to learn with a few free Azure training resources. Microsoft Azure’s Own Training Resources. Azure DevOps ( 21.8K

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Continuous deployment for Azure functions

CircleCI

Firebase Cloud Functions by Google, Azure Functions. In this tutorial, you will learn and demonstrate how to continuously deploy an Azure function. An Azure account. Azure CLI installed. Azure functions core tools installed. Creating an Azure Service Principal account. Prerequisites. A CircleCI account.

Azure 52
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How to prepare for the AZ- 204 Exam: An Articulated Case Study

Cloud That

An Azure account with an active? Azure Subscription? or Azure Pass. Getting Started with Azure Virtual Machines. Creating HTML Website using Azure App Service. Management of APIs through Azure Portal. Monitoring and Logging with Azure Monitor and Application Insights. Pre-requisites:? . ? ? ??

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Open and Extensible: The Core of FlexDeploy’s Philosophy

Flexagon

First and foremost, that means creating a first class DevOps platform. If you are using less popular tools, or even homegrown solutions, this architecture enables you to plug and play just about any tech or tool into the DevOps solution. These systems are large, complex, and have generally been left behind in the DevOps revolution.

DevOps 78
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Red Hat Ansible Accelerator

Perficient

Our Ansible Accelerator provides an overview of what Ansible can do to help modernize and streamline your DevOps and IT operations. With Ansible you can configure systems, deploy software, and coordinate more advanced IT tasks such as continuous integration/continuous deployment (CI/CD) or zero downtime rolling updates. Contact Us

DevOps 52
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Pivotal Partner Days – From an OverOps Solution Engineer POV

OverOps

As a member of the OverOps field team, I spend a lot of time interacting with customers, and it seems they are all thinking about how DevOps and SREs teams can help mediate the battle between reliability and innovation. How can they achieve a happy balance between speed, innovation, and quality? Which brings me to another point.

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Introducing the MLOps Management Agent

DataRobot

In several earlier blog posts, we have focused on what we at DataRobot call the AI production gap , which refers to the gap that makes it difficult to transition models from the data science teams who develop them to the IT and DevOps teams who are responsible for deploying and monitoring them in production. Request a Demo.

Azure 52