Azure Functions in . NET Core for Large Data Processing Functions can process multiple data streams or batches simultaneously, leveraging concurrency and parallelism to handle large workloads efficiently 1 Choose the Right Trigger Azure Functions
Building Scalable Applications with Azure Functions: Best . . . In this blog post, we’ll delve into the best practices and tips for building scalable applications with Azure Functions Azure Functions is a serverless compute service that enables you to run event-driven code without having to explicitly provision or manage infrastructure
Mastering Storage in Azure Functions: Options and Best Practices From durable and highly available Blob storage to a fully managed NoSQL database with Cosmos DB, and seamless integration with Azure Data Lake Storage for big data processing, Azure Functions provides a comprehensive set of tools to take your applications to the next level
Big Data Architectures - Azure Architecture Center . . . Batch processing: The datasets are large, so a big data solution often processes data files by using long-running batch jobs to filter, aggregate, and otherwise prepare data for analysis Usually these jobs involve reading source files, processing them, and writing the output to new files You can use the following options:
Best practices for using Azure Data Lake Storage - Azure . . . This article provides best practice guidelines that help you optimize performance, reduce costs, and secure your Data Lake Storage enabled Azure Storage account For general suggestions around structuring a data lake, see these articles: