TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #14691 · May 10
#csharp#architecture#aspnetcore#clean_architecture#cqrs#ddd#dotnet#dotnetcore#event_driven_architecture#event_sourcing#kubernetes#masstransit#messaging#microservice#microservices#oauth2#opentelemetry#software_architecture#software_design#software_engineering#vertical_slice_architecture Migrating from a monolithic architecture to a cloud-native microservices architecture offers several benefits. It improves scalability, allowing different parts of the application to grow independently. This approach also enhances reliability by isolating faults, so if one service fails, others continue to work. Additionally, microservices enable faster deployment and updates, as each service can be developed and deployed separately. This flexibility allows teams to use the best technology for each service, making development more efficient and agile[2][3][5]. https://github.com/meysamhadeli/monolith-to-cloud-architecture
Search: #classification
@djangoproject · Post #240 · 01/25/2017, 10:03 AM
http://www.aparat.com/v/4nbc9 This talk gives a quick overview of Python's capabilities as a #data_processing and #machine_learning tool through practical examples: gathering data from the web or a local file, validating/modifying it and finally analyzing it to build models for #classification and #prediction#tasks.