Capacity planning allocates system cluster resources based on business requirements and performance metrics—including user volume, data volume, and concurrency. A solid capacity plan tells you how many users and concurrent requests your system can handle, and helps you prevent resource shortages and performance bottlenecks before they occur.
The process covers five key activities:
Collect requirements and data: Clarify system requirements and business forecasts—user count, data volume, concurrent requests, and response time targets. Collect historical data and analyze trends to improve forecast accuracy.
Analyze system architecture and resource consumption: Map how the system consumes CPU, memory, disk space, and network bandwidth. Monitor performance metrics and resource utilization to identify bottlenecks.
Assess and plan capacity: Using the analysis results, determine the hardware, software configurations, and network bandwidth required to meet your performance and availability targets.
Test and validate: Simulate real-world load to test performance and resource consumption under peak conditions. If results deviate from the plan, adjust and retest.
Manage and monitor: Capacity planning is an ongoing process, not a one-time exercise. Establish continuous monitoring to track performance and resource utilization, and revise the plan as usage patterns change.
Plan capacity across every product in your system's critical path. Increasing capacity at all nodes—rather than only the obvious bottleneck—achieves high performance and high availability, avoids wasted spend, and protects overall availability. Base your initial estimates on historical data and business forecasts, then make dynamic adjustments as actual usage data comes in.
Capacity planning spans three core areas: compute, storage, and networking. The key assessment metrics for each are described below.
Compute products
Elastic Compute Service (ECS) provides scalable compute resources. Instance families vary in their compute, network, storage, and security specifications—choose the family and type that matches your application scenario and performance requirements.
For workloads that cannot tolerate virtualization overhead, consider bare metal servers or Dedicated Hosts. Serverless options such as Elastic Container Instance (ECI) are also available, providing more efficient and flexible compute resources.
Storage products
Object Storage Service (OSS) is suited to unstructured data such as images, audio, video, and documents. Size your OSS capacity based on current data volume, access frequency, and projected data growth rate.
File Storage NAS provides shared storage for multiple ECS instances and is suitable for file sharing, backup, and disaster recovery workloads. Key sizing inputs are the number of files, individual file sizes, and read/write frequency.
Elastic Block Storage (EBS) offers two types: cloud disks backed by a distributed storage architecture, and local disks backed by physical machine storage. Cloud disks support customizable provisioned performance and burst performance.
Storage specifications and types differ in their IOPS and throughput limits. Select the specification that matches your workload's I/O profile.
Database products
Select a database type that fits your user base and business scale before finalizing your architecture. A common pattern is to pair a caching layer—such as Redis—with a relational database to increase transactions per second (TPS) and handle concurrent requests in multi-user scenarios. For large data volumes or data mining needs, consider distributed databases, AnalyticDB, or dedicated big data analytics tools.
Once you select a database, identify the key metrics for your workload:
MySQL: Monitor queries per second (QPS), CPU utilization, I/O throughput, and storage space.
Redis: Monitor TPS, data volume, and bandwidth.
Collect these metrics through load and stress testing, then document the results in a capacity assessment report to support infrastructure procurement and deployment decisions.
Network products
Network capacity planning focuses on inbound/outbound bandwidth and latency.
Bandwidth requirements: Analyze historical traffic data and business forecasts to determine required bandwidth. Choose between pay-by-bandwidth and pay-by-traffic billing based on your traffic patterns.
Latency requirements: Select the region and zone closest to your users to minimize latency. Use Network Intelligence Service (NIS) to observe and assess inter-region network connectivity.
Security requirements: Match your network security products to the scale and risk profile of your business. Options include Cloud Firewall, cloud-native protection, Anti-DDoS, and Resource Access Management (RAM).
Combine these product capabilities based on your architecture needs. Allocate resources at each layer to build a system that performs reliably under high load.