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Cloud Computing Trends and Innovations

Apiumhub

Implementation: Using edge computing frameworks like AWS IoT Greengrass or Azure IoT Edge to deploy machine learning models directly on edge devices for real-time data analysis. Implementation: Utilizing tools like Google Anthos or Azure Arc to manage Kubernetes clusters across different cloud environments, providing a unified control plane.

Trends 52
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Free Cloud Courses at Linux Academy — July 2019

Linux Academy

Serverless Concepts. Serverless has been gaining momentum as cloud technology continues to become more widespread. This course provides a high-level overview of the concept of Serverless computing without getting into deep technical details. Azure CLI Essentials. Azure Concepts. Google Cloud Concepts.

Linux 60
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How companies adopt and apply cloud native infrastructure

O'Reilly Media - Ideas

Netflix is a good media company case study , with its early adoption of microservices, its contributions to chaos engineering , and its open source, multi-cloud continuous delivery platform Spinnaker (which Netflix and Google recently donated to the newly launched Continuous Delivery Foundation (CDF)). in July 2018.

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The 5 Components of Azure DevOps

ParkMyCloud

In the search to accelerate and simplify the DevOps process, we take a look at Microsoft’s Azure DevOps, a hosted service providing development and collaboration tool that was formerly known as Visual Studio Team Services (VSTS). Azure Pipelines – A CI/CD, testing, and deployment system that can connect to any Git repository.

Azure 8
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Deploy a serverless workload on Kubernetes using Knative and ArgoCD

CircleCI

Creating a pipeline to continuously deploy your serverless workload on a Kubernetes cluster. The serverless approach to computing can be an effective way to solve this problem. Serverless allows running event-driven functions by abstracting the underlying infrastructure. Microsoft Azure account. Prerequisites.

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Azure Kubernetes Service (AKS) – Simplifying Deployment with Stateful Applications

RapidValue

Instead of creating resources in cloud, you are now able to create resources and infrastructure inside Azure Kubernetes cluster through deployments and services manifest files. Azure Kubernetes Service or AKS enables you to do that. Azure handles all the critical tasks which include health monitoring and maintenance.

Azure 12
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Demystifying MLOps: From Notebook to ML Application

Xebia

Several common open source tools such as MLflow are discussed, but the same principles apply to other tooling you can find in the market. The most common open source tool that allows you to do this is MLflow. Most enterprise ML platforms (Vertex AI, Azure ML, Sagemaker) integrate with MLflow. Still with us?