Method and system for elastically scaling MongoDB database cluster instance nodes in cloud environment

Abstract

The invention provides a method and a system for elastically scaling a MongoDB database cluster instance node in a cloud environment, and provides the method for elastically scaling the MongoDB database cluster instance node in the cloud environment, which consists of a MongoDB database deployment process in a public cloud environment, a database monitoring data training prediction process and a database node elastic scaling process. The system automatically judges the appropriate node number of MongoDB replica set instances in the current time period, elastically expands and contracts read-only nodes of a database cluster, optimizes the node resource number of the instances, ensures that database services are not down, establishes a monitoring data training module by analyzing monitoring indexes of large data volume in the past time period in the cloud environment, and achieves the real-time monitoring of the MongoDB replica set instances. And according to the proper read-only node, the read-only instance node is automatically created or deleted, and the MongoDB database replica set cluster is automatically configured, so that the resource cost of the user is saved, and the operation and maintenance cost for monitoring the database performance at any time is reduced.

Description

technical field [0001] The invention relates to the technical field of cloud databases, in particular to a method and system for elastic scaling of instance nodes of a MongoDB database cluster in a cloud environment. Background technique [0002] In the application scenario of the Internet, the read request data volume of the database is large and the concurrency requirement is high. Among them, the read-only instance group is an implementation of read-write separation. [0003] In an application scenario where there are a small number of write requests to the database but a large number of read requests, the read request of the database becomes the bottleneck of the database, and the existing database instance cannot satisfy both the read request and the fast response of the write operation at the same time. In order to improve the performance of the database, share the pressure on the database, increase the number of nodes in the database cluster, distribute the read requ...

AI Technical Summary

Problems solved by technology

[0003]In an application scenario where there are a small number of write requests to the database but a large number of read requests, the read requests of the data

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