Capacity Evaluation

Analyze your current business situation to forecast cloud infrastructure demands

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Background

Capacity evaluation involves analyzing the current situation, and forecasting the future use and capacity of cloud infrastructure resources of the business application system. Capacity evaluation assesses business demands, service level, and application system performance, and establishes relationship models between these three aspects to help enterprises effectively manage their cloud infrastructure input costs, and improve service output capacity.

Solution Architecture

  1. Capacity evaluation is necessary to assess the current system for performance, load testing, and stress testing. Testing enables the business to analyze performance data, performance bottlenecks, and propose optimization recommendations. This includes tracking the entire architecture from user request, to public network, server-side WEB server, application server, database, operating system, and final storage request.
  2. General application performance is divided into design of frontend performance, application server performance, middleware performance, database performance and operating system performance.
  3. Suggested key performance indicators are listed below.
    Front-end: Request page size, number of requests, Start Render and First Byte, and full load time
    Network: Network latency, availability, and bandwidth
    Application: Application architecture and business process design, business logic implementation, efficiency of SQL and resource consumption
    JVM: Java Virtual Machine region usage, GC time and frequency, memory overflow and leakage
    Middleware: Database connection pool, thread pool, request queue and other operating conditions
    Database: Database table structure and index design, database instance operating status, database delays, slow SQL, connect session status
    Operating System: CPU, MEM, Network I/O, Disk I/O, kernel parameters running

Highlights

  • Specialized capacity assessment theory
  • Reduces risk of system breakdown

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