CN114153518A - Autonomous capacity expansion and reduction method for cloud native MySQL cluster - Google Patents
Autonomous capacity expansion and reduction method for cloud native MySQL cluster Download PDFInfo
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Abstract
The invention discloses a method for autonomously expanding and reducing capacity of a cloud native MySQL cluster, which comprises the following steps: collecting a plurality of resource indexes of container resources and a plurality of performance indexes of a database; if the resource index exceeds the preset resource threshold range, modifying the resource limit of the container resource based on the resource index, and adjusting the performance parameters of the database; and if the performance index exceeds the pre-configured performance threshold range, automatically modifying the resource limit of the container resource or automatically adjusting the number of nodes of the database cluster based on the performance index. The invention solves the technical problems that when the database cluster needs capacity expansion and capacity reduction in the related technology, a user needs to manually adjust resource configuration and database parameter configuration, and a great deal of energy and time are consumed by the user.
Description
Technical Field
The invention relates to the technical field of database control, in particular to a method for autonomously expanding and reducing capacity of a cloud native MySQL cluster.
Background
The MySQL database is one of the most popular open-source relational databases at present, and has been widely recognized for its stability, ease of use, and high performance. However, due to the open source property and the very flexible use mode, the user is difficult to ensure the environment to be uniform and the version to be consistent in the database architecture and use, one-key deployment cannot be realized, and the capacity expansion and the capacity reduction often need to consume a great deal of energy and time of the user. Kubernets is taken as a current mainstream container technology-based distributed architecture scheme, convenient arrangement such as stateless application deployment, capacity expansion and the like is mature, but the support for stateful application such as a database is limited.
At present, the original stateful set of Kubernetes supports state application, MySQL replication can be realized through certain configuration optimization, but the configuration is complex and the expansibility is poor. After a user creates a MySQL cluster and fixes a cluster architecture, if an application suddenly increases a MySQL cluster request, a performance bottleneck exists in the existing MySQL cluster, at this time, resource configuration needs to be manually adjusted or capacity expansion is needed, timeliness is low, and the cluster performance bottleneck is possibly aggravated by temporary capacity expansion.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a method for autonomously expanding capacity and reducing capacity of a cloud native MySQL cluster, so as to solve the technical problem that a user needs to manually adjust resource configuration and manually adjust database parameter configuration when a database cluster expands capacity and reduces capacity, which consumes a lot of time.
The purpose of the invention is realized by the following technical scheme:
a cloud native MySQL cluster autonomous capacity expansion and reduction method is characterized by comprising the following steps:
1) collecting a plurality of resource indexes of container resources and a plurality of performance indexes of a database; setting a first trigger threshold and a second trigger threshold for each resource index to be tested, wherein the first trigger threshold and the second trigger threshold are critical range thresholds of the resource index to be tested, and the first trigger threshold is larger than the second trigger threshold; configuring a resource threshold range based on the first trigger threshold and the second trigger threshold; setting a third trigger threshold and a fourth trigger threshold for each performance index to be tested, wherein the third trigger threshold and the fourth trigger threshold are critical range thresholds of the performance index to be tested, and the third trigger threshold is greater than the fourth trigger threshold; configuring a performance threshold range based on the third trigger threshold and a fourth trigger threshold;
2) if the resource index exceeds the preset resource threshold range, modifying the resource limit of the container resource based on the resource index, and adjusting the performance parameters of the database;
3) and if the performance index exceeds the pre-configured performance threshold range, automatically modifying the resource limit of the container resource or automatically adjusting the number of nodes of the database cluster based on the performance index.
Further, the step of modifying the resource limit of the container resource based on the resource index and adjusting the performance parameter of the database includes: and modifying the resource limit of the container resource based on the resource index and the preset resource change proportion.
Further, automatically modifying resource limits of the container resources or automatically adjusting the number of nodes of the database cluster based on the performance indicators includes: judging whether the residual node resources meet the capacity expansion requirement or not; if the residual node resources do not meet the capacity expansion requirement, triggering an exclusive mode, wherein in the exclusive mode, the target service instance using the container resources singly occupies all available container resources; migrating other service instances to other database clusters or deleting the other service instances.
Acquiring a capacity reduction node; executing cluster capacity reduction by adopting the capacity reduction node; updating the configuration of the middleware cluster, the database service and the high-availability component; and updating the cluster information in the management library to finish the capacity reduction operation of the database.
The method comprises the steps of collecting a plurality of resource indexes of container resources and a plurality of performance indexes of a database, modifying resource limits of the container resources based on the resource indexes and adjusting performance parameters of the database if the resource indexes exceed a preset resource threshold range, and automatically modifying the resource limits of the container resources or automatically adjusting the number of nodes of a database cluster based on the performance indexes if the performance indexes exceed the preset performance threshold range.
According to the invention, when the change of the database cluster load (corresponding container resource index and performance index) exceeds the threshold, user intervention is not required, the configured threshold and the management resource are compared according to the cluster type and the load condition, and database cluster expansion or contraction is automatically realized, so that the change of the database cluster load demand can be responded, and the efficiency of database cluster expansion and contraction can be improved, thereby solving the technical problem that a user needs to manually adjust resource configuration and database parameter configuration when the database cluster needs to expand and contract in the related technology, and a great deal of energy and time are consumed by the user.
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FIG. 1 is a flow chart of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention can be applied to database containerization cluster service, and provides an autonomous capacity expansion and reduction method based on different dimensional loads, which is compatible with a plurality of versions of MySQL mirror images and a plurality of architectures (single instance, master-slave copy, MGR single master and MGR multi-master), for MySQL containerization clusters managed under a Kubernets platform.
The capacity expansion and reduction in the invention not only includes the increase (capacity expansion) and limitation (capacity reduction) of container resources (such as CPU, memory, disk and IO), but also includes the increase and reduction of MySQL cluster node number, database performance indexes (such as connection number, concurrent thread number, TPS and QPS) and the increase and reduction of custom resources.
According to the embodiment of the invention, when the MySQL cluster load change exceeds the threshold, user intervention is not needed, the configured threshold is compared according to the cluster type and the load condition, and cluster expansion or contraction is automatically realized according to the resources managed by kubernates, so that the MySQL cluster load change can be responded in time, and the MySQL cluster load demand and the lower resource use demand can be balanced. Depending on providing more accurate node control scheduling, the controller selects the capacity expansion and reduction strategies of different dimensions of the MySQL cluster, and balance of resource use and service response is achieved.
The present invention will be described with reference to examples.
Examples
FIG. 1 is a general flow diagram of the present invention, the method comprising the steps of:
1) first, a plurality of resource indicators of container resources and a plurality of performance indicators of a database are collected.
2) And if the resource index exceeds the preset resource threshold range, modifying the resource limit of the container resource based on the resource index, and adjusting the performance parameters of the database.
When the resource index of the container source exceeds the preset resource threshold range, the limitation of the container resource is adjusted based on the resource index, and the corresponding parameter of the database is automatically adjusted.
3) And if the performance index exceeds the pre-configured performance threshold range, automatically modifying the resource limit of the container resource or automatically adjusting the number of nodes of the database cluster based on the performance index.
That is, when the performance index of the database exceeds the pre-configured performance threshold range, the resource limit of the container is automatically adjusted based on the performance index or the database cluster is automatically scaled (embodied as automatically adjusting the number of nodes of the database cluster).
Through the steps, a plurality of resource indexes of the container resources and a plurality of performance indexes of the database can be collected firstly, if the resource indexes exceed the preset resource threshold range, the resource limit of the container resources is modified based on the resource indexes, the performance parameters of the database are adjusted, and if the performance indexes exceed the preset performance threshold range, the resource limit of the container resources is automatically modified based on the performance indexes or the number of nodes of the database cluster is automatically adjusted. In the embodiment, when the change of the database cluster load (corresponding container resource index and performance index) exceeds the threshold, user intervention is not needed, the configured threshold and the management resources are compared according to the cluster type and the load condition, and cluster expansion or capacity reduction is automatically realized, so that the change of the database cluster load demand can be responded, and the efficiency of database cluster expansion and capacity reduction can be improved, thereby solving the technical problem that a user needs to manually adjust resource configuration and database parameter configuration when the database cluster needs to expand and reduce the capacity in the related technology, and a great deal of energy and time are consumed by the user.
When the autonomous capacity expansion and capacity reduction of the database container cluster is realized, a capacity expansion and capacity reduction judgment threshold value needs to be configured.
Before collecting a plurality of resource indexes of container resources and a plurality of performance indexes of a database, the control method comprises the following steps: determining a plurality of resource indexes to be tested of the container resource and a plurality of performance indexes to be tested of a plurality of databases; setting a first trigger threshold and a second trigger threshold for each resource index to be detected, wherein the first trigger threshold and the second trigger threshold are critical range thresholds of the resource index to be detected, and the first trigger threshold is larger than the second trigger threshold; configuring a resource threshold range based on the first trigger threshold and the second trigger threshold; setting a third trigger threshold and a fourth trigger threshold for each performance index to be tested, wherein the third trigger threshold and the fourth trigger threshold are critical range thresholds of the performance index to be tested, and the third trigger threshold is larger than the fourth trigger threshold; configuring a performance threshold range based on the third trigger threshold and the fourth trigger threshold.
The MySQL cluster is configured with the capacity expansion and capacity reduction threshold value, the capacity expansion and capacity reduction threshold value can be configured when the MySQL cluster is deployed, and the capacity expansion and capacity reduction threshold value can be configured after the cluster is deployed. Currently, the method supports the threshold based on container resource indexes (CPU, memory, disk, IO), database performance indexes (connection number, concurrent thread number, TPS, QPS) and self-defined resources.
The multiple resource metrics of the container resource to be tested include, but are not limited to: CPU, memory, disk, IO; the multiple measured performance indicators of the database include, but are not limited to: connection number, concurrent thread number, TPS, QPS.
A first trigger threshold and a second trigger threshold set for each resource index to be detected, where the first trigger threshold may be an expansion threshold (i.e., an upper threshold) of the resource index, and the second trigger threshold may be a contraction threshold (i.e., a lower threshold) of the resource index; a third trigger threshold and a fourth trigger threshold set for each performance index to be measured, where the third trigger threshold may be an expansion threshold (i.e., an upper threshold) of the performance index to be measured, and the fourth trigger threshold may be a contraction threshold (i.e., a lower threshold) of the performance index to be measured.
After the container resource index, the database performance index, and the custom resource threshold are set, an expansion/contraction action and a change ratio need to be set, a threshold is triggered for the change of the container resource, a resource limit is modified by default, a resource change ratio is set as a preset ratio parameter by default (for example, the resource change ratio is set as 10% by default), and an exclusive mode can be set. For the triggering threshold value of the change of the database resources, the resource limit is modified preferentially by default, and then the database cluster architecture is adjusted, for example, the expansion of 1 master 2 slave is 1 master 3 slave, and the like.
A plurality of resource indicators for the container resource and a plurality of performance indicators for the database are collected.
In this embodiment, the container-exporter may be relied on to collect each resource index of the container resource, and the mysqld-exporter may be relied on to collect each performance index of the MySQL database. Optionally, in this embodiment, an Operator listener component may also be used to obtain configured threshold indicator data (partial indicator) from the collected data, compare the current MySQL cluster resource configuration, and check whether to trigger the threshold.
And if the resource index exceeds the preset resource threshold range, modifying the resource limit of the container resource based on the resource index, and adjusting the performance parameters of the database.
Modifying resource limits of the container resources based on the resource indicators and adjusting performance parameters of the database, comprising: and modifying the resource limit of the container resource based on the resource index and the preset resource change proportion.
For the container resource index change triggering threshold, Mysqld-operator defaults to rounding and modifying resource limitation according to a resource change proportion, if the residual resource of the bottom-layer physical machine node is not enough for capacity expansion, an exclusive mode may be triggered, and other service instances are migrated or deleted (configured according to instances) to complete the capacity expansion.
And if the performance index exceeds the pre-configured performance threshold range, automatically modifying the resource limit of the container resource or automatically adjusting the number of nodes of the database cluster based on the performance index. The method comprises the following steps: judging whether the residual node resources meet the capacity expansion requirement or not; if the residual node resources do not meet the capacity expansion requirement, triggering an exclusive mode, wherein in the exclusive mode, the target service instance using the container resources singly occupies all available container resources; migrating other service instances to other database clusters or deleting other service instances.
And for the change triggering threshold of the database performance index, the container resource limit is preferably modified by a Mysqld-operator calculation and expansion mode. If the database cluster needs to be adjusted, the adjustment mode and the number of changed nodes can be calculated, single-instance support adjustment is master-slave and MGR, and the master-slave and MGR support adjustment of the number of nodes. For example, in a cluster with master-slave replication, if the QPS trigger threshold needs to be expanded, different numbers of slave nodes may need to be added to complete expansion.
And when the MySQL cluster expansion and capacity reduction is required for the change of the database performance index, the Mysqld-operator calculates the capacity reduction node according to the number of the managed instances on the node and the vacant resource of the node. And selecting the node for capacity expansion by the kube-scheduler according to an algorithm, wherein if the node currently managed by the kube-schedules is insufficient or the vacant resource of the node is insufficient, the capacity expansion fails.
Through the embodiment, the MySQL containerized cluster managed under the Kubernets platform can be subjected to an autonomous capacity expansion and reduction method compatible with multiple versions of MySQL mirror images and multiple architectures (single instance, master-slave copy, MGR single master and MGR multiple masters), based on different dimensionality loads, so that the cluster capacity expansion or reduction is autonomously realized, and the change of the MySQL cluster load demand can be timely responded.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (3)
1. A cloud native MySQL cluster autonomous capacity expansion and reduction method is characterized by comprising the following steps:
1) collecting a plurality of resource indexes of container resources and a plurality of performance indexes of a database; setting a first trigger threshold and a second trigger threshold for each resource index to be tested, wherein the first trigger threshold and the second trigger threshold are critical range thresholds of the resource index to be tested, and the first trigger threshold is larger than the second trigger threshold; configuring a resource threshold range based on the first trigger threshold and the second trigger threshold; setting a third trigger threshold and a fourth trigger threshold for each performance index to be tested, wherein the third trigger threshold and the fourth trigger threshold are critical range thresholds of the performance index to be tested, and the third trigger threshold is greater than the fourth trigger threshold; configuring a performance threshold range based on the third trigger threshold and a fourth trigger threshold;
2) if the resource index exceeds the preset resource threshold range, modifying the resource limit of the container resource based on the resource index, and adjusting the performance parameters of the database;
3) and if the performance index exceeds the pre-configured performance threshold range, automatically modifying the resource limit of the container resource or automatically adjusting the number of nodes of the database cluster based on the performance index.
2. The method according to claim 1, wherein in step 2), modifying resource limitations of container resources based on resource indicators and adjusting performance parameters of the database includes: and modifying the resource limit of the container resource based on the resource index and the preset resource change proportion.
3. The method according to claim 1, wherein the step 3) includes: judging whether the residual node resources meet the capacity expansion requirement or not; if the residual node resources do not meet the capacity expansion requirement, triggering an exclusive mode, wherein in the exclusive mode, the target service instance using the container resources singly occupies all available container resources; migrating other service instances to other database clusters or deleting the other service instances.
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