Cloud Storage: blog storage for static assets and media files. - Source: dev.to / 5 months ago

Preevy includes built-in support for saving profiles on AWS S3 and Google Cloud Storage. You can also store the profile on the local filesystem and copy it manually before running Preevy - we won't show this method here. - Source: dev.to / 6 months ago

Google Cloud Storage{:target="_blank"} is a globally distributed object storage service offered by Google Cloud Platform. They provide trustworthy and scalable databases for storing large amounts of blob data. They also provide a way to optimize cost and performance with different storage classes and pricing options. - Source: dev.to / 11 months ago

Google Cloud Storage - https://cloud.google.com/storage/. - Source: dev.to / 12 months ago

Also, in terms of packing a pre-trained model you will probably want to puts weights, biases etc into S3 or similar object storage (https://cloud.google.com/storage etc) and load it on application start. Source: about 1 year ago

While gRPC and Apache Thrift have served the microservice architecture well, CloudWeGo's advanced features and performance metrics set it apart as a promising open source solution for the future. - Source: dev.to / 4 months ago

Services in general communicate via Thrift (and in some cases HTTP). Source: about 1 year ago

Protocol Buffers is the most popular one, but there are many others such as Apache Thrift and my own Typical. Source: over 1 year ago

RPC is not strictly OO, but you can think of RPC calls like method calls. In general it will reflect your interface design and doesn't have to be top-down, although a good project usually will look that way. A good contrast to REST where you use POST/PUT/GET/DELETE pattern on resources where as a procedure call could be a lot more flexible and potentially lighter weight. Think of it like defining methods in code... Source: over 1 year ago

The information can be stored in a database or as files, serialized in a standard format and with a schema agreed with your Data Engineering team. Depending on your information and requirements, it can be as simple as CSV, XML or JSON, or Big Data formats such as Parquet, Avro, ORC, Arrow, or message serialization formats like Protocol Buffers, FlatBuffers, MessagePack, Thrift, or Cap'n Proto. - Source: dev.to / over 1 year ago