The second big drawback is speed. There will be more latency in this scenario. How much latency depends upon the environment. If there is RDBMS in the source, AWS Data Migration Service will at worst take around 60 seconds to replicate. That cost needs to be accounted for. Secondarily, many triggering events are leveraged which happen fairly quickly but they do add up. - Source: dev.to / 3 months ago

Amazon Database Migration Service might initially seem like a perfect tool for a smooth and straightforward migration to RDS. However, our overall experience using it turned out to be closer to an open beta product rather than a production-ready tool for dealing with a critical asset of any company, which is its data. Nevertheless, with the extra adjustments, we made it work for almost all our needs. - Source: dev.to / 4 months ago

Does AWS DMS make sense here? Doesn't the aforementioned "snapshot+restore to provisioned and upgrade" method suffice? I wanted to get some opinions before deep diving into the docs for yet another AWS service. Source: 11 months ago

One easy solution is AWS DMS. I use it for on-going CDC replication with custom transforms, but you can use it for simple replication too. Source: about 1 year ago

Https://aws.amazon.com/dms/ Azure Database Migration Service. - Source: Hacker News / over 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 / 5 months ago

Services in general communicate via Thrift (and in some cases HTTP). Source: over 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