Capacity Planning Process – Part 1

This article is the first part in a series of blogs where we will talk about capacity planning for IT systems. In this part, we will start with an overview of capacity planning, why we need capacity planning, the capacity planning process, and common pitfalls in capacity planning.

In the remaining articles of this series, we will see examples of capacity planning using a couple of techniques/approaches, which are discussed in this part.

Introduction

Simply put, capacity planning can help in answering some of the following –

• What is the maximum load level that the system can handle?
• What would the average response time, throughput, and CPU utilization be for a particular workload?
• How much resources (servers, CPUs, memory) would be required to meet the Service Level Agreements (SLAs)?
• Which components of the system affect performance the most? Are they potential bottlenecks?

What Is Capacity?

Capacity term can be used in multiple contexts, but at high level, it can be understood as

• Number of transactions/users that can be supported by available resources during peak time of the day.
• CPU utilization, memory utilization, and transaction response time are of interest here.
• When capacity numbers do not meet the expectations, there are two options:
  • Optimize application architecture and code.
  • Add more resources.
    • Of course, infrastructure architecture needs to support this.

What Is Capacity Planning?

Capacity Planning is an important part of IT Management. It helps in identifying what kind of hardware/software and when it is required, and when, to meet the business needs. A capacity plan is important input to the IT budget process - it helps in allocating the appropriate budget to meet the capacity requirements

Without a capacity plan, organizations are either grossly under-prepared or over-prepared. Capacity planning is the process of determining the production capacity needed by an organization to meet changing demands for its products. A discrepancy between the capacity of an organization and the demands of its customers results in inefficiency, either in under-utilized resources or unfulfilled customers.

The goal of capacity planning is to minimize this discrepancy. Capacity can be increased through introducing new techniques, equipment, and materials, increasing the number of workers or machines, increasing the number of shifts, or acquiring additional production facilities.

Approaches to Capacity Planning

Various techniques and approaches are used by practitioners to do capacity planning. These vary in terms of efforts required/accuracy levels and also the phase in the development cycle, when the capacity planning is done.

Approach 1: Make an Educated Guess

• Rely on intuition, expert opinions, past experience, ad hoc procedures and general rules of thumb.
• PROS: Quick, easy and cheap.
• CONS: Very inaccurate and risky

Approach 2: Generate Load and Measure Performance

• Use load-testing tools that generate artificial workloads and measure performance.
• PROS: Provides accurate and realistic data. Could help to identify bottlenecks and fine-tune system prior to production.
• CONS: Extremely expensive and time-consuming. Assumes that the system is available for testing.

Approach 3: Build a Performance Model of the System

• Build and analyze performance models which capture the performance and scalability characteristics of the system.
• PROS: Often much cheaper and quicker than load-testing. Could be applied during early phases (arch/design).
• CONS: Extremely complex. Accuracy depends on how representative models are.

Capacity Planning Process

• Determine service level requirements
  • From a capacity planning perspective, a computer system processes workloads and delivers service to users.
  • During the first step in the capacity planning process, these workloads must be defined and a definition of satisfactory service must be created.
  • A workload is a logical classification of work performed on a computer system. If you consider all the work performed on your systems as pie, a workload can be thought of as some piece of that pie. Workloads can be classified by a wide variety of criteria.
  • Who is doing the work (particular user or department).
  • What type of work is being done (order entry, financial reporting).
  • How the work is being done (online inquiries, batch database backups).
• Determine the unit of work
  • What "transaction" really means.
  • Can vary from an OLTP application to a batch system.
  • "Business Transaction" vs "Technical Transaction."
• Establish service levels
  • A service level agreement is an agreement between the service provider and service consumer that defines acceptable service.
  • The service level agreement is often defined from the user’s perspective, typically in terms of response time or throughput.
  • Using workloads often aids in the process of developing service level agreements, because workloads can be used to measure system performance in ways that make sense to clients/users.
  • If you want to base your service level requirements on present actual service levels, then you may want to analyze your current capacity before setting your service levels.
• Analyze current capacity. Note that these steps are generally done for an existing system during load testing phase. but similar steps can be done using APM data for a live system or using performance modeling for a system which is still in early phases of development life cycle.

  • First, compare the measurements of any items referenced in service level agreements with their objectives. This provides the basic indication of whether the system has adequate capacity.

  • Next, check the usage of the various resources of the system (CPU, memory, and I/O devices). This analysis identifies highly used resources that may prove problematic now or in the future.

  • Look at the resource utilization for each workload. Ascertain which workloads are the major users of each resource. This helps narrow your attention to only the workloads that are making the greatest demands on system resources.

  • Determine where each workload is spending its time by analyzing the components of response time, allowing you to determine which system resources are responsible for the greatest portion of the response time for each workload.

• Plan for the future
  • Determine future processing requirements
  • Systems may be satisfying service levels now, but will they be able to do that while at the same time meeting future organizational needs?
  • Future processing requirements can come from a variety of sources. Input from management may include:
    • Expected growth in the business, Requirements for implementing new applications.
    • Planned acquisitions, IT budget limitations.

Problems in the Capacity Planning Process

• No standard technology.
• No standard workload.
• Forecasting future applications/technologies is difficult.
• Each vendor has their own benchmarks.
• Distributed environments make modeling even more complex.

Common Mistakes in the Capacity Planning Process

• Wrong workload.
• Startup /shutdown time is generally ignored.
• Monitoring overheads are ignored.
• Too much data/too little analysis.