Capacity planning refers to planning and configuring the system cluster resources based on business needs and system performance indicators, including user numbers, data volume, concurrent requests, etc., to meet the requirements of system expansion, user growth, and increased workload. Capacity planning can determine the maximum user capacity and concurrent request volume that the system can support, and proactively prevent resource shortages and performance bottlenecks. The implementation plan for capacity planning includes the following steps:
Collect requirements and data: First, the system's needs and predictions need to be clearly defined, including user numbers, data volume, concurrent request volume, and response time requirements. At the same time, historical data and trend analysis need to be collected to provide more accurate predictions of future needs.
Analyze system architecture and resource consumption: Analyze the system's architecture and resource consumption, including CPU, memory, disk space, network bandwidth, etc. By monitoring the system's performance indicators and resource utilization, identify performance bottlenecks and resource bottlenecks.
Capacity evaluation and planning: Based on the requirements and data analysis results, perform capacity evaluation and planning. Determine the required hardware equipment, software configuration, network bandwidth, and other resources to meet the system's performance and availability requirements.
Capacity testing and verification: Conduct capacity testing and verification based on the capacity planning results. Simulate real workload conditions to test the system's performance and resource consumption under high loads, and verify the accuracy of the capacity planning. If the test results do not match the planning, adjustments and optimizations can be made.
Capacity management and monitoring: Capacity planning is not a one-time task but a continuous process. It is necessary to establish capacity management and monitoring mechanisms to monitor and manage the system's performance and resource utilization, and adjust and optimize the capacity planning in a timely manner.
Capacity planning needs to comprehensively consider the various products used in the system architecture and their corresponding performance requirements. By collectively improving the capacity bottlenecks of each node in the system architecture, the goals of high performance and high availability can be achieved, avoiding resource waste and excessive costs. When conducting capacity planning, analysis and predictions can be made based on historical data, business forecasts, etc., or based on actual usage to dynamically adjust capacity planning.
Capacity planning involves fundamental capabilities such as computing, storage, and networking, and its specific evaluation indicators and contents are as follows:
Computing Services
Elastic Compute Service (ECS): Provides elastic and customizable computing resources, different instance families have variations in computing, networking, storage, security indicators, etc. Based on application scenarios and performance requirements, appropriate specifications and types can be chosen. Also, consider bare metal servers and dedicated hosts without virtualization overhead, as well as serverless Elastic Container Instance (ECI) types. These offerings can provide more efficient and flexible computing resource capabilities.
Storage Services
Object Storage Service (OSS): Suitable for storing and accessing unstructured data such as images, videos, documents, etc. When conducting capacity planning for object storage, factors such as data size, access frequency, data growth rate need to be considered to determine the required storage capacity.
File Storage NAS (NAS): Provides shared storage space for multiple ECS instances, suitable for file sharing, backup, and disaster recovery scenarios. When conducting capacity planning for file storage, factors such as the number of files, file sizes, read/write frequency need to be considered to determine the required storage capacity.
Elastic Block Storage (EBS): Provides cloud disks based on distributed storage architecture and local disks on physical servers. Customizable performance and burst capability for cloud disks can be provided based on business needs.
Different specifications and types of storage have different IOPS and throughput limits. Customers can flexibly choose based on their business requirements.
Database Services
For capacity planning of database products, the selection of a suitable database needs to be considered before the business determines the user scale and traffic levels. Common solutions include combining caching databases with relational databases to achieve higher TPS and meet the concurrency requirements of multi-user scenarios. Some companies may also have larger data capacity and data mining requirements, and may introduce distributed databases, analytical databases, and big data analysis tools.
After selecting the database, it is necessary to understand the specific indicators to consider for different databases based on business characteristics. Taking MySQL and Redis databases as examples, specific metrics to be considered include TPS, CPU, IO, storage space for MySQL databases, and bandwidth for Redis databases. These metrics need to be evaluated and reported based on specific business models and results of performance testing to facilitate procurement and deployment.
Network Services
When conducting capacity planning for network products, the following indicators related to inbound and outbound bandwidth and network latency need to be considered:
Network bandwidth requirements: Based on the network traffic and bandwidth requirements of the business, determine the required bandwidth capacity. The choice between fixed bandwidth and pay-as-you-go bandwidth can be analyzed and predicted based on historical data and business forecasts.
Network latency indicators: Based on business requirements and user distribution, choose appropriate regions and availability zones for service deployment. Network connection data between different regions can be observed and evaluated using network intelligent services.
Security requirements: Based on the scale and security requirements of the business, a series of network security products and strategies can be chosen, including cloud firewalls, cloud native security, DDoS protection, access control, and others, to enhance the security of the business.
The capabilities of different basic products can be flexibly combined and separated, and capacity planning and resource allocation can be conducted based on business needs to achieve system stability and high scalability.