Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing business operations. Microsoft's Azure offers a robust AI and ML portfolio, including Azure Applied AI Services, Cognitive Services, Machine Learning, and AI Infrastructure, enabling the creation of intelligent applications. Azure's integration with OpenAI distinguishes it from competitors like AWS and GCP, by providing advanced AI algorithms for businesses to enhance automation, decision-making, and customer experiences, reinforcing its edge as a cloud provider.
Ephemeral OS disks in Azure, suited for stateless VMs, boost boot speed and performance by utilizing local storage, reducing costs. These temporary, low-latency disks are managed by Azure and lost upon VM restart or deletion; hence they're unsuitable for stateful VMs. Creating a VM and reimaging discards all changes, reverting to a pristine state.
Azure Kubernetes Service (AKS) offers scalable, reliable cloud computing with simplified management and integration with Azure services. It stands out as cost-effective compared to AWS's EKS and GCP's GKE, providing the latest Kubernetes updates and a pay-as-you-go model. To further reduce costs, services like Spot by NetApp and Ocean optimize cloud expenses, making AKS a robust choice for containerized applications.
Serverless computing, like Azure Functions, enables developers to build and run applications without managing infrastructure, cutting time and resources for deployment. Azure Functions offers on-demand, scalable, event-driven computing, supporting multiple programming languages, with cost-effective, consumption-based billing. While Azure Functions competes with Google Cloud Functions and AWS Lambda, the best choice depends on specific business needs and existing ecosystems.
Comparison of cloud computing free trials by the major providers GCP/AWS/Azure.
In this blog post, I've included a number of free training resources, some well-known, others not so much...
