Weekly Technical Report for the second week of December 2022

This week’s work is mainly a sorting out of this aspect of the work I am responsible for, and many problems have been identified so far. These problems are mainly focused on the data on the cloud, the current problem is mainly how to safely on the cloud, how to transform the current single-geography deployment scheme, how to fix the inconsistency between the data under the cloud and the data on the cloud. In addition, it is found that there are still some services using under-cloud databases, and these under-cloud databases are reasonably to be abandoned. However, these services are some old services, and code changes will bring some risks, which need to be investigated before taking action.

The aspects of the investigation include the basic principles of the existing data to the cloud auxiliary services and related code logic details, and it is best to find out the problems as early as possible and repair them in a timely manner. On the other hand, the data to the cloud process requires real-time monitoring, as comprehensive as possible on the service interface call quality, timeout rate, write failure rate, inconsistency rate, etc. have a clear grasp. This aspect is best done from the report monitoring and log monitoring. Multi-location deployment program, the current intention to use a master multi-slave, master-slave unilateral replication, only write the master library, read only from the library these principles to start. The main purpose of using a multi-location deployment scheme is to improve service stability, reduce the latency of most requests, improve service quality, and eliminate the impact of cross-regional link instability. Multi-location deployment of data synchronization delays can not be ignored, there must be an acceptable delay, this piece of theory and monitoring from two aspects to grasp.

Then again, it is important to master a scripting language. Especially when there are a lot of repetitive things need to be processed, or need to analyze some data to obtain a conclusion. Being able to be more proficient in a scripting language like Python has a big advantage. However, I don’t think it would be wise to say that it would be a good idea to take Python and write a large program. Each programming language is like a different knife, all can be used to cut vegetables, but some knives are better suited for cutting meat or bones.