CN106603618A - Cloud platform-based application auto scaling method - Google Patents

Abstract

The invention discloses an application elastic scaling method based on a cloud platform, which relates to the field of cloud computing. On the cloud platform, an elastic scaling strategy with timing, periodicity, and scaling according to performance parameters is set on the application service that has been set with load balancing. Through the elastic scaling Policies dynamically add and delete nodes to implement elastic scaling of applications, and provide management services that automatically adjust customer computing resources. The invention can realize the user's purpose of automatically adjusting the application of computing resources according to business and performance requirements, effectively improves the utilization rate of computing resources, improves work efficiency, and ensures stable and efficient operation of machines.

Description

A cloud platform-based application elastic scaling method

technical field

The invention relates to the field of cloud computing, in particular to a cloud platform-based application elastic scaling method.

Background technique

Cloud computing is the growth, usage, and delivery model of Internet-based related services, usually involving the provision of dynamically scalable and often virtualized resources over the Internet. Cloud computing is to distribute computing on a large number of distributed computers instead of local computers or remote servers, and the operation of enterprise data centers will be more similar to the Internet. This enables enterprises to switch resources to required applications and access computers and storage systems as needed.

Auto Scaling is a management service that economically and automatically adjusts its elastic computing resources according to the user's business needs and strategies. It can automatically increase virtual machine instances when the business grows to ensure the smooth and healthy operation of the business; when the business declines Automatically reduce virtual machine instances to save corresponding computing resources.

Load Balance (Load Balance) is a collection of servers composed of multiple servers in a symmetrical manner. Each server has an equivalent status and can provide external services independently without the assistance of other servers. Through a certain load sharing technology, the requests sent from the outside are evenly distributed to a certain server in the symmetrical structure, and the server that receives the request independently responds to the client's request. Load balancing can evenly distribute customer requests to the server array, thereby providing fast access to important data and solving the problem of a large number of concurrent access services.

Contents of the invention

Aiming at the needs and shortcomings of the current technological development, the present invention provides a cloud platform-based application elastic scaling method.

According to the cloud platform-based application elastic scaling method of the present invention, the technical solution adopted to solve the above technical problems is as follows: the cloud platform-based application elastic scaling method is set on the cloud platform on the application service with load balancing , set the timing, period, and elastic scaling policy based on performance parameters, dynamically add and delete nodes through the elastic scaling policy to achieve elastic scaling of applications, and provide management services that automatically adjust customer computing resources.

Preferably, the elastic scaling strategy mainly includes two operations of capacity expansion and capacity reduction. The expansion operation mainly includes: starting, waking up, and creating a virtual machine, or opening and expanding a specified virtual machine or a node of a specified virtual machine. The capacity reduction operation mainly includes: shutting down, hibernating, and destroying the virtual machine, or shutting down or reducing the capacity of a specified virtual machine or a node of a specified virtual machine.

Preferably, when increasing or reducing capacity from the specified virtual machine, the IP, ssh user password, application software, and software installation/stop script of the specified virtual machine are set.

Preferably, the elastic scaling strategy is used in conjunction with load balancing. After the scaling is completed, the load balancing node can be dynamically added or deleted, that is, the load balancing node can be added or deleted to perform elastic scaling of web services.

Compared with the prior art, the cloud platform-based application elastic scaling method of the present invention has the beneficial effect that: the present invention sets the timing, period, and performance-based The elastic scaling strategy of parameter scaling realizes the elastic scaling of applications by dynamically adding and deleting nodes, and provides management services for automatically adjusting customer computing resources, so as to realize the purpose of users automatically adjusting their computing resource applications according to business and performance needs; it can effectively improve computing power. The utilization rate of resources, improve work efficiency, ensure the stable and efficient operation of the machine, and have good use and promotion value.

Description of drawings

Accompanying drawing 1 is a schematic diagram of setting the elastic scaling strategy;

Accompanying drawing 2 is a schematic diagram of the method of applying elastic stretching.

detailed description

In order to make the purpose, technical solution and advantages of the present invention clearer, the method for elastic scaling of applications based on the cloud platform in the present invention will be further described in detail in conjunction with specific embodiments.

According to the cloud platform-based application elastic scaling method of the present invention, on the cloud platform, in the application service with load balancing set, the elastic scaling strategy can be set regularly, periodically or according to the application load (CPU utilization rate, memory utilization rate, etc.) data , by dynamically adding and deleting nodes to achieve elastic scaling of applications, enabling users to automatically adjust their computing resource applications according to business and performance needs. The basis of this method is to apply a load balancing strategy that has been set, and can set timing, periodicity, and elastic scaling strategies that scale according to performance parameters to provide customers with management services that automatically adjust customer computing resources.

Example:

This embodiment is an application elastic scaling method based on the cloud platform. On the application service that has been set up for load balancing on the cloud platform, an elastic scaling policy with timing, periodicity, and scaling according to performance parameters is set, and dynamically added and deleted through the elastic scaling policy. Nodes implement elastic scaling of applications and provide management services that automatically adjust customer computing resources.

Accompanying drawing 1 is a schematic diagram of setting the elastic scaling strategy, as shown in Figure 1, the process of setting the elastic scaling strategy is as follows on the application service with load balancing set on the cloud platform: first, the threshold value is input by the customer Information, capacity increase/decrease, specified host IP, ssh user name/password and other information, and then, the system authenticates the policy information entered by the customer, if the authentication is passed, the storage database is set, and if the authentication fails, an error is returned.

In the application scaling method described in this embodiment, the elastic scaling strategy mainly includes two operations of capacity expansion and capacity reduction. The expansion operation mainly includes: starting, waking up, and creating a virtual machine, or opening and expanding a specified virtual machine or a node of a specified virtual machine. The capacity reduction operation mainly includes: shutting down, hibernating, and destroying the virtual machine, or shutting down or reducing the capacity of a specified virtual machine or a node of a specified virtual machine. Moreover, when increasing or reducing capacity from a specified virtual machine, the IP address, ssh user password, application software, and software installation/stop script of the specified virtual machine must be set. Thresholds are set when expanding or reducing capacity. The thresholds include: memory utilization, cpu utilization, disk read/write rate, inflow and outflow rate, and number of connections. The values of these items can be used in combination, and as long as any one Execution is triggered when the threshold is exceeded. Through the elastic scaling policy, set the information storage database. The elastic scaling strategy is used in conjunction with load balancing, and load balancing nodes can be added and deleted to realize elastic scaling of web services. When setting the auto-scaling policy, select the load-balancing node. After the application auto-scaling is completed, the application can be automatically added to or deleted from the load-balancing node.

Accompanying drawing 2 is a schematic diagram of the application elastic scaling method, as shown in Figure 2, the specific implementation process of the application elastic scaling method described in this embodiment is as follows: first call the system program, (using the real-time monitoring module of the system) The policy initiates monitoring, monitors the elastic scaling policy in real time, and regularly checks to determine whether the preset threshold is reached; when the elastic scaling policy reaches the threshold, the system further judges whether to increase or decrease the capacity according to the rules set by the customer. To operate, create, start, wake up the virtual machine, or increase the capacity to the specified virtual machine, that is, automatically deploy the software to the specified virtual machine through the edited script, and then add a load balancing node; if the capacity reduction operation is performed, shut down, Hibernate, destroy the virtual machine, or reduce the capacity of the specified virtual machine, that is, shut down the software process of the specified virtual machine through the edited script, and then delete it from the load balancing node. Through the above process, automatic elastic scaling of computing resources can be realized. At the same time, when the elastic scaling policy is executed, the system calls the task processing module to ensure that the background can view the execution and execution results of the task.

The above-mentioned specific embodiments are only specific cases of the present invention, and the scope of patent protection of the present invention includes but is not limited to the above-mentioned specific embodiments, any claims that meet the claims of the present invention and any ordinary skilled person in the technical field. Appropriate changes or substitutions should fall within the scope of patent protection of the present invention.

Claims (4)

1. An application elastic scaling method based on a cloud platform, characterized in that, on the application service that has been set up on the cloud platform for load balancing, an elastic scaling policy with timing, period, and scaling according to performance parameters is set, through which the elastic scaling policy dynamically Adding and deleting nodes realizes elastic scaling of applications, and provides management services for automatically adjusting customer computing resources. 2. A cloud platform-based application elastic scaling method according to claim 1, wherein the elastic scaling strategy mainly includes two operations of capacity expansion and capacity reduction; and the capacity expansion operation mainly includes: start, wake up, and create A virtual machine, or opening or expanding a specified virtual machine or a node of a specified virtual machine; the capacity reduction operation mainly includes: shutting down, hibernating, destroying the virtual machine, or closing or reducing the capacity of the specified virtual machine or the node of the specified virtual machine. 3. According to claim 2, a cloud platform-based application elastic scaling method is characterized in that, when increasing or decreasing the capacity of the specified virtual machine, the IP of the specified virtual machine, ssh user password, application software, and software are set. Install/stop script. 4. A cloud platform-based application elastic scaling method according to claim 3, characterized in that, the elastic scaling strategy is used in conjunction with load balancing, and after the scaling is completed, it can be dynamically added or deleted to the load balancing node, that is, adding , Delete the load balancing node for elastic scaling of web services.