What is Performance Testing?
Software application Performance Testing is a somewhat subjective phrase that many people find difficult to define. For instance, what exactly is good performance? How to determine if something is fast, and what makes an application slow? The difficulty is that these are subjective terms that vary among users, applications, and devices.
If your goal is to create a fast web application, or you’re dealing with users complaining that the mobile app is slow, testing for this may prove challenging. The fact is that actual Performance Testing will help to determine if a system meets specific acceptance criteria for both responsiveness and robustness under reasonable load. Although responsiveness varies—it could be the amount of latency between server request/response cycles or the reaction time to user input. It’s typically something that can be measured directly. Robustness also varies by system, but it usually translates into a measurement of scalability, stability, and overall system reliability.
Instead of dealing with the subjective, an excellent approach to Performance Testing includes precise plans and well-thought-out goals. Start by defining test plans that include stress testing, load testing, availability testing, endurance testing, isolation testing, and configuration testing. Merge these plans with precise metrics regarding goals, thresholds, acceptable measurements, and plan to deal with the performance issues for the best results. Including measures such as average response time over predefined time frames, perfect timings, graphs of standard deviation, average latency.
Performance Testing is non-functional testing. It is performed to determine how a system performs regarding responsiveness and stability under a particular workload. It can serve to investigate, measure, validate or verify other quality attributes of the system, such as reliability, scalability and resource usage.
How Performance Testing Works?
These are few points which have to be kept in mind when defining the workflow of Performance Testing.
- Define Test Plan.
- Define Measurements and Control Pass-Fail Thresholds.
- Use Real-Time Analytics.
- Test Continuously, Develop Continuously, Review Continuously.
In the performance world, the user defines the load. A user wants the system to handle and configure it through thread groups, samplers, timers, ramp-ups, loops, etc. These defined targets and goals are specific, measurable, achievable and time framed.
Define Measurements and Control Pass-Fail Thresholds
After deciding on the test plan, the user needs to determine how user measure its success or failure. On a load test, use KPIs like response time, hits per second and error rate. Identifying and controlling pass-fail thresholds for load testing KPIs and work, highlight and alert which issues we need to engage in an address.
Use Real-Time Analytics
Define goals and identify performance gaps, but to make the work count and to improve user need to understand why it is succeeding or failing and what are the consequences.
In load testing, the user has Real-Time reports to understand and analyze the data and KPIs we measured. If the user sees errors in the reports, it can drill-down and figure out the origin of the bottlenecks he sees.If it is doing well, the user needs to analyze and understand the success factors to recreate them in the future. A user should also examine if the user needs to set a higher standard for next time, so we elevate its personal and organizational strengths.This analysis helps to make Data-Driven decisions, and also ensure to identify gaps in the Real-Time and not only at the end of the process.
Test Continuously, Develop Continuously, Review Continuously
Now it’s time to improve. In Performance Testing, integrating development with the Continuous Integration process and running automated load tests routinely ensures ongoing product improvements and time-saving. Relevant for personal and organizational routines as well. Continuous planning and ongoing self-examination and performance reviewing, avoid repeating existing destructive patterns and focus on efforts on the required places.
Benefits of Performance Testing
- Improve optimization and load capability.
- Identify discrepancies and resolve issues.
- Measure the accuracy, speed, and stability of the software.
- Validate the fundamental features of the software.
- Performance Testing allows keeping your users happy.
- Helps to identify the loopholes which make the system work less efficiently.
Why Performance Testing Matters?
Ever faced a situation when so many users want the same thing?When inbox flooded by so many questions and requests that you freeze and stop doing anything at all? Everyone has those days, and so does software application or website.
Unfortunately, those occasions can be extremely costly, hurting the bottom line. Software performance matters when –
Your solution has or will process a large volume of load. For example, if there are thousands of users in your organization who use it every day or your system is expected to process a large volume of transactions, then capacity matters.
A system outage linked to the revenue of your organization. What would the cost be if your software solution was down for an hour? A day? .Severe costs affect the stability of the solution.
The responsiveness of the solution is directly linked to the experience of customers, and therefore reputation and revenue. In this case response time matters.
Human well-being is at stake, for example, many systems found in the healthcare industry. In that case stability, capacity, and response time all matter a great deal.
How to Adopt Performance Testing?
If any user is using any tool for Performance Testing for the first time in his product, first needs to understand the Performance metrics to know about Performance Testing.
Performance metrics commonly include.
These metrics and others help an organization to perform multiple types of performance tests –
- Throughput – It signifies the number of transactions or requests made in a given period. Throughput calculated as requests/unit of time.The formula is – Throughput = (number of requests) / (total time).
- Response time, or latency – Response Time measures the performance of an individual transaction or query. Response time is the amount of time from the moment that a user sends a request until the time that the application indicates that the request has completed. For example, let’s say you have API and you want to find how much time that API call takes to execute once requested, here you measure the response time.Response time is the whole time it takes from when a user requests until they receive a response.
- Bandwidth – Volume of data per second that move between workloads, usually across a network. CPU interrupts per second: The no. of hardware engaged with a process receives per second. These metrics and others help an organization to perform multiple types of performance tests.
Continuous testing for Website, API’s and Mobile apps
- Build – Use favorite open source tool to build tests.
- Scale – Run any combination of tests in parallel.
- Analyze – View and Analyze result in Real-Time.
- Automate – Configure Performance test, and integrate with Continuous Delivery platform.
Performance Testing Best Practices
- Test Early and Often.
- Take a DevOps Approach.
- Consider Users, Not Just Servers.
- Understand Performance Test Definitions.
- Build a Complete Performance Model.
- Include Performance Testing in Development Unit Tests.
- Define Baselines for Important System Functions.
- Consistently Report and Analyze the Results.
- Test as early as possible in development. Do not wait and rush Performance Testing as the project winds down.
Follow DevOps Approach
Soon after the lean movement inspired agile, IT organizations saw the requirement to unify development and IT operations activities. The outcome is the DevOps approach, where developers and IT work together to define, build, and deploy software as a team. Just as agile organizations frequently embrace a continuous, test-driven development process, DevOps should include IT operations, developers, and testers working together to build, deploy, tune and configure applicable systems, and execute performance tests against the end-product as a team.
Consider Users, Not Just Servers
Performance tests frequently focus on the results of servers and clusters running software. Don’t forget that actual people use software, and that performance tests should determine the human element as well. For instance, specifying the performance of clustered servers may return acceptable outcomes, but users on a single overloaded server may experience a satisfactory outcome. Instead, tests should contain the per-user experience of performance, and user interface timings should capture orderly with server metrics.
To exemplify, if only one percent of one million requests/response cycles are latent, ten thousand people an alarming no. will have experienced poor performance with the application. Driving the Performance Testing from the single user point of view helps you understand what each user of your system will suffer before it’s an issue.
Understanding Performance Testing Definitions
It’s crucial to have a standard definition of the types of performance tests executed against the applications, such as –
- Single User Tests – Testing with single active user produce the most suitable possible performance, and response times used for baseline measurements.
- Load Tests – The action of the system under average load, containing the expected no. of concurrent users doing a particular number of transactions within an average hour. Measure system capacity, and know the actual maximum load of the system while it still meets performance goals.
- Peak Load Tests – Understand system behavior under the most massive demand anticipated for the concurrent number of users.
- Endurance (Soak) Tests – Endurance testing determines the longevity of components, and if the system can withstand average to peak load over a predefined duration. Memory utilization should be observed to detect potential failures. The testing will also measure that throughput and response times after sustained activity continues to meet performance goals.
- Stress Tests – Under stress testing, several activities to overload the existing resources with excess jobs are carried out in an attempt to break down the system. Understand the upper limits of capacity inside the system by purposely pushing it to its breaking point. The goal of stress testing is to ascertain the failure of the system and to observe how the system recovers back gracefully. The challenge is to set up a private environment before launching the test so that you can precisely capture the behavior of the system repeatedly under the most unpredictable scenarios.
Build a Complete Performance Model
Measuring the application’s performance includes understanding the system’s capacity which provides for planning what steady state will be concerning concurrent users, average user sessions, simultaneous requests, and server utilization during peak periods of the day. Additionally, it should describe performance goals, such as maximum response times, system scalability, acceptable performance metrics, user satisfaction marks, and the maximum capacity for all of these metrics. It’s critical to define related thresholds that will alert you to potential performance issues as you pass those thresholds. Multiple thresholds described with increasing levels of risk. An effective planning processing contains the definition of success criteria, such as –
- Key Performance Indicators (KPI), comprising request/response times, average latency, and server utilization.
- Business Process Completion Rate, containing transactions per second, and system throughput load profiles for average, peak, and spike tests.
- Hardware metrics, containing memory usage, CPU usage, and network traffic.
- Include Performance Testing in Development Unit Tests.
Waiting up to the time a system built or complete to run performance tests can make it tough to isolate where problems exist. It’s frequently more expensive to correct performance issues later in the development process, and riskier to make changes if functional testing completed.
As a result, developers should involve Performance Testing as part of their unit tests, in addition to committed Performance Testing. There is a significant difference in the testing approaches, as unit testing frequently focuses on sections of code, not only application functionality or the integrated system. Developers will be involved with the performance of their code throughout the development process, and each one will have a leg up on knowing how to monitor individual components for issues in production.
Define Baselines for Important System Functions
In most cases, QA systems do not match production systems. Having baseline performance measurements of each system gives you the right goals for each environment used for testing. They specifically provide an essential starting point for response time goals where there are no previous metrics, without having to predict or base them on another application. Baseline performance tests and measurements, such as single user login time, the request/response time for people’s screens and so on, should occur with system load as none.
Consistently Report and Analyze the Results
Performance test design and execution are significant, but test reports are essential as well. Reports announce the results of your application’s behavior to everyone within the organization, and can even serve as bragging rights for project developers and owners. Analyzing and reporting results consistently also assist in defining attack plans for fixes. Remember to consider the audience, since reports for developers should be different from reports sent to managers, project owners, corporate executives, and even customers if applicable. With every report, note obvious software changes made as well as any other changes tested (third-party software upgrades, changes to the environment, hardware, and so on).
Top Performance Testing Tools
List of some Performance Testing Tools –
- BlazeMeter for People Who Know JMeter
- Taurus- Working with Multiple JMeter Tests
An Apache Performance Testing tool can generate load tests on application services and the web. Jmeter plugins provide flexibility in load testing, and cover areas such as logic controllers, graphs, thread groups, functions, and timers. Jmeter supports an integrated development environment (IDE) for test recording for web applications or browsers, as well as a command line mode for load testing Java-based operating systems.
Persons familiar with JMeter know that it’s one of the best open source Performance Testing tools available in today’s market. But no device is foolproof, and there are always pros and cons to finding with each one.
BlazeMeter is ‘JMeter in the Cloud.’ It is not only 100% compatible with JMeter, but it also addresses its limitations like scalability, stability, and reporting.
With BlazeMeter, all you need is to upload your JMeter scripts directly, choose the no. of load engines you wish to run the test. BlazeMeter takes care of everything else! You will have an unlimited no. of pre-configured load engines available at your convenience. Detailed graphical reports generated during load.
Taurus – Working with Multiple JMeter Tests
With the help of Taurus, combining several JMeter scripts into a single unified test is not only achievable but easy.
Developed by Micro Focus, tests and measures the performance of applications under load. LoadRunner can simulate thousands of concurrent users using application software, recording and later analyzing the performance of key components of the application, as well as record and analyze load tests. LoadRunner can generate the scripts by recording them, such as logging HTTP requests between a client web browser and an application’s web server. LoadRunner also involves versions geared toward Cloud use.
Developed by Neotys, provides stress and load tests for web and mobile applications and is specifically designed to test apps before releasing for DevOps and Continuous Delivery pipelines. NeoLoad offers pragmatic solutions for developers to help them optimize performance before the application goes into production. Monitor database, application servers, and web. NeoLoad simulates millions of users, performs tests in-house or via the Cloud.
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