This practical guide bridges the gap between general cloud computing architecture in Microsoft Azure and scientific computing for bioinformatics and genomics. You'll get a solid understanding of the architecture patterns and services that are offered in Azure and how they might be used in your bioinformatics practice. You'll get code examples that you can reuse for your specific needs. And you'll get plenty of concrete examples to illustrate how a given service is used in a bioinformatics context.You'll also get valuable advice on how to:Use enterprise platform services to easily scale your bioinformatics workloadsOrganize, query, and analyze genomic data at scaleBuild a genomics data lake and accompanying data warehouseUse Azure Machine Learning to scale your model training, track model performance, and deploy winning modelsOrchestrate and automate processing pipelines using Azure Data Factory and DatabricksCloudify your organization's existing bioinformatics pipelines by moving your workflows to Azure high-performance compute servicesAnd more