9 Questions to Ask When Considering Automated Performance Testing

The single metric of load time can make or break your conversion, user satisfaction, and revenue. Imagine what combined performance criteria can do to your app. You’re well aware of the impact performance testing has on your product. And you know that it’s tricky to run. That’s why we’re here to figure out how to simplify and refine it. So, let’s learn how to productively couple automated software testing services and performance tests.

Can Performance Testing Be Automated?

Anything can be automated. The real question is, will that “anything” produce quality results when automated? Luckily, in the case of performance automation testing, the active phase (test runs and report generation) is fully executable by tools. You can even use AI to design investigation scenarios and analyze the outcomes.

But automated software performance testing doesn’t necessarily presuppose taking care of the entire cycle.

What Is Automated Performance Testing?

To figure out what automated performance testing services actually mean, let’s take a look at their behind-the-scenes.

Preparation Phase

1. You plan your testing efforts by defining objectives, identifying test scenarios, and setting goals/thresholds.
2. You prepare the environment, tweak performance configurations, and set up your tools.
3. You create automated test scripts, parametrize them, fix proper assertions, and ready version control systems.

Execution Phase

1. Your tools of choice run the tests.
2. They capture real-time metrics, like response times, error rates, throughput, etc.
3. They monitor the environment (watch servers, networks, and databases for any performance degradation or failures).
4. Lastly, automated performance testing tools generate reports with key findings.

Support Phase

1. Your team analyzes the results to determine the root cause of an issue.
2. They fix the bottlenecks and set test re-runs.
3. Finally, they report to stakeholders to highlight areas of concern and inform decisions related to product readiness, necessary optimization, potential redesigns, etc.

As you can see, automation performance testing is test execution and report generation only. We’re not saying that it’s too little of a contribution. This seemingly small part is insanely useful. But to make something out of it, you still need a dedicated QA team. Engineers do the bulk of the work. They:

• Design the test plan (define what and how to test).
• Write and automate scripts so they accurately simulate user behavior.
• Ensure properly configured environments.
• Monitor test execution to secure accurate results.
• Analyze results and work with the team to optimize performance.
• Report findings and help with continuous improvement.

These steps are where the actual results happen, and thanks to which your app advances. Automation, on the other hand, supports your efforts. It:

• Unloads your team to focus on other tasks.
• Ensures consistent test execution.
• Speeds up the entire process, especially via overnight or off-hours runs and parallel execution.
• Simplifies scalability and offers greater flexibility (what tests to run, how many, and how often).
• Allows for continuous testing and improvement.
• Saves long-term costs with reusable scripts and less reliance on manual labor.

Overall, automation and performance testing are a powerful combo. But they don’t become one unless you have a skilled crew to make them collaborate.

Which Types of Tests Are Used in Automated Performance Testing?

Automated load and performance testing are often used interchangeably. That’s a bit misleading, so let’s resolve this right away. Performance is an umbrella term. Load testing is a type of performance testing. That’s it.

As a practice, automated high performance testing is very multifaceted. It includes different types of checks to give you the best understanding of your system. And, of course, to make sure there’s nothing to frustrate your customers.

• Load testing checks how the system handles normal traffic (the usual number of users).
• Stress testing pushes the system beyond its limits (like thousands of users) to see when it breaks.
• Spike testing rapidly increases the load (suddenly adding a lot of users) to test how the system reacts to quick traffic surges.
• Endurance testing runs the system under a constant load for a long time (days or weeks) to see if it gets slower or crashes.
• Scalability testing assesses how well the system handles growth, like adding more users or data.
• Volume testing investigates how the system deals with large amounts of data (big files or huge databases).
• Configuration testing checks how the system performs with different settings or setups (like different server or network configurations).
• Reliability testing analyzes how consistently the system performs over time without crashing or slowing down.
• Baseline testing sets a performance benchmark (a baseline) to know what the system’s normal performance looks like.
• Failover testing identifies how the system recovers when something goes wrong, like a server crash.
• Longevity testing shows how the system performs over long periods of continuous use.

All of these test types have their nuances and require a great deal of skill. The good news is that automated performance testing specialists can easily handle them. The only trouble is finding talent that can cover all that.

When Is the Right Time to Automate Performance Testing?

Manual software testing can be introduced at any point in development, and it’ll work just fine. If you do that with automation, you’ll only find trouble. To work, it needs a base. That means having a more or less stable baseline for your performance tests. When you ignore this, you’ll have to switch and tweak your scripts to account for any changes in the product.

So, first, you run manual tests to establish the benchmarks for response times, throughout, and system behavior. Then, you’ll have a steady flow to automate. And you can amplify it once you’ve added more stable scenarios.

If you’re wondering what’s a good moment to automate, i.e., when automation works the best, these would be your top picks.

Automate Once Core Features Are Stable

If your app is too buggy, performance issues might just be caused by broken features. Wait until the main elements work well. Then, automate to get accurate, meaningful results.

Automate When Preparing to Scale or Release Big Updates

More users or big changes can stress your app. Automated tests help you check performance quickly and often, so nothing breaks when traffic goes up or features roll out.

Automate When You Switch to CI/CD

CI/CD means fast, frequent updates. Automating performance tests lets you catch slowdowns before they reach users.

Automate When Manual Testing Slows You Down

Running the same performance tests by hand takes time. If it’s holding up your releases, automation saves time and keeps things moving smoothly.

Automate When Issues Get More Complex

Some problems only show up over time, like memory leaks or slowdowns under load. Automated tests can track these things consistently and alert you when something slips.

The thing about automated performance testing, is that you can’t really use it just because you want to see its benefits. For those to actually appear, you need to put in quite a bit of effort. So, before you decide to introduce automation, you need to think about whether it’s going to work out at all. You should also consider whether you have the resources to support it.

What Are the Phases for Automated Performance Testing?

Speaking of the effort going into automation, let’s break it down. Let’s say you already have your dream QA engineers, true specialists in automated website performance testing or what have you. What needs to happen before you get your first results?

#1 Planning

Before anything, you need to know what you’re testing and what problems you’re trying to catch.

• Figure out which parts of the system are most sensitive to load (e.g., checkout, login, reporting, database-heavy tasks).
• Set clear performance goals. Don’t focus solely on speed. Include metrics like error rate, system resource usage, and system behavior under pressure.
• Estimate expected usage: How many users at the same time? How often? What will they be doing?
• Choose what kinds of tests you’ll need: regular load, traffic spikes, long-term usage, etc.

Basically, here, you’re determining what your team will be doing and how.

#2 Test Design

Next, it’s time to design tests that simulate how people actually use your system.

• Create test scripts that represent common user flows (e.g., logging in, running a report, searching, uploading data). Include planned test types, like load, stress, or soak.
• Use realistic behavior patterns: mix of users, different actions, some idle time between steps, retries, etc.
• Parameterize test data so users don’t all do the exact same thing (e.g., different usernames, product IDs).

Remember that there are automated performance testing tools that let you create scripts without needing to code. But you’ll still need it if you’re dealing with complex user flows, dynamic data, custom logic, and fine-grained tuning. So, consider this during tool selection.

#3 Automation Setup

Once your tests are ready, you don’t want to run them by hand every time. This is where you automate them.

• Set up performance tests to run automatically during builds or on a schedule (e.g., nightly, before each release).
• Use CI/CD tools to integrate your tests into the development process.
• Make sure your performance testing environment is consistent so results don’t vary due to changes in infrastructure.

#4 Execution

This is when your scripts actually simulate traffic and hit your system with the planned load.

• Start with smaller tests to validate that scripts and systems are working.
• Ramp up the number of virtual users to match your scenarios.
• Monitor for unexpected behavior: errors, failed responses, system slowdowns.
• Run multiple rounds if needed, especially for different load levels or edge cases.

#5 Monitoring & Data Collection

As the test runs, you want to collect both user-facing and backend performance data.

• Track client-side metrics: response time, success rate, failed requests, timeouts.
• Track system-level metrics: CPU usage, memory usage, database queries, I/O wait times, queue lengths.
• Monitor the app during and after automated performance testing to catch slow recovery, memory leaks, or unstable services.

#6 Analysis & Reporting

All that data you collect needs to be turned into insights. At this stage, you start to figure out what went wrong, where, and why.

• Compare test results against your original goals: did the system stay within limits?
• Identify bottlenecks: slow endpoints, overwhelmed databases, resource exhaustion.
• Look for patterns like slower responses at higher load or resource usage increasing over time.
• Generate clear, focused reports for your team: include metrics, charts, and explanations, not just raw data.

#7 Tuning & Re-Testing

When you find issues, your team will fix them and run another round of testing to see if the errors have been amended.

• Developers might optimize code, change infrastructure, or fix bad queries.
• You re-run the same test scenarios to confirm that performance improved.
• Document what changed and how the system responded. This helps track improvements over time and avoid regressions later.

After these phases of automated performance testing comes support. It’s the upkeep of your tests and processes. You’ll:

• Revisit your targets based on user needs or business changes.
• Remove irrelevant tests to keep your suite clean and focused.
• Fix flaky or unreliable tests.
• Update your scripts to keep them effective and expand your suite as needed.

That’s another unique feature of automated software performance testing. It needs continuous maintenance. So, you should never overlook proper documentation. Keep everything organized and share found knowledge. Then, future work with automation will be much easier.

How to Choose an Automated Performance Testing Tool?

Deciding between hundreds of automated performance testing tools is hard enough. Well, allow us to complicate things a little more. When selecting a tool, there are four key aspects you should really consider.

How well does the tool cover your needs:

• Can it test what you need?
• Does it have good reporting capabilities?
• Does it require coding?

Can the tool integrate with your workflows:

• Does it support CI\CD tools?
• Does it work with version control?
• Does it include monitoring features?

Does the tool scale easily:

• Can it generate enough load?
• Does it support distributed testing?
• Can you control user behavior and timing?
• Is the infrastructure easy to manage?

Is the tool easy to work with:

• Is it user-friendly?
• What is its learning curve?
• Will your team need to be trained (which will take time), or can they operate it right away?

You’ll need to ask yourself and your team all these questions. Not just “what reviews does this tool have?” or “is it well-regarded?”. Another point over which you’ll debate is whether to go with a proprietary or open-source option.

Open-source automation tools for performance testing are:

• Free (a big plus, yes).
• Highly-customizable.
• Have ample community support. So, there’ll typically be lots of guides, forums, and plugins.

On the other hand, they:

• May lack polish, i.e., be less user-friendly or offer somewhat basic features.
• Rarely offer official support: you’re on your own if something goes wrong.
• Often require advanced skills to work with.

Proprietary automated performance testing tools are:

• Very user-oriented, hence better UI, simplified workflows, and sharper learning curves.
• More rich in their features (typically).
• Supplied with dedicated customer support.
• Easier to manage in terms of infrastructure.

Yet, they are not free of vices either:

• They cost money, and the price can range dramatically.
• They’re often less flexible (limited customization or scripting).
• It’s harder to integrate them with other platforms.
• There might be some hidden costs (it’s not a rule, but rather a warning).

Overall, be sure to conduct proper research on the tools and look at your options from different angles. Also, do ask your team for input. They might already have some great suggestions and their experience will help you pick faster and better.

What Are the Benefits of Outsourcing Performance Testing Automation?

While on the topic of teams, let’s take a look at how outsourced QA can help them. Cooperating with external expertise is rather common. In the case of automated performance testing, this approach is popular because you can have a sort of separate crew that takes care of a big chunk of work. All the while, the rest of the team focuses on other tasks. So, it’s mostly a matter of efficiency, especially given that some performance tests can run for months.

But that’s not all QA outsourcing services have to offer.

• You get instant access to experienced specialists who know the tools, strategies, and best practices.
• Outsourcing teams can quickly build test environments, create scripts, and run tests, speeding up your overall process.
• You avoid the costs of hiring full-time and buying tools or infrastructure you’ll only use occasionally.
• You don’t have to buy servers or set anything up yourself. External engineers can scale up fast and share their resources.
• Outsourced teams have as much involvement in your project as you want. They can set up automation, consult, train, or handle the entire testing process.
• As external engineers work, your in-house team is free to focus on anything else. This speeds up development and improves app quality faster.
• A third party brings a fresh perspective. This can help spot issues your internal crew might overlook.

Outsourced expertise is a genuinely foolproof way to advance your project. The only risk to this is accidentally partnering with a subpar company. Read on for a brief guide on how to avoid getting your team into the mess that unreliable providers can create.

What Do Performance Testing Automation Services Normally Include?

Remember the phases of automated performance testing we discussed earlier? An outsourced provider can cover all of it and more. That’s actually the best thing about working with a QA company — you can hire one to do anything:

• Designing a custom testing strategy.
• Helping with the environment setup.
• Creating automation scripts.
• Offering ongoing maintenance or monitoring.
• Providing post-implementation support.
• Mentoring your team.
• Finding or cultivating performance testing talent.
• Consulting and developing recommendations, etc.

You don’t have to collaborate with a provider fully. By that, we mean that you can hire specialists even if you need assistance with one specific part of automated performance testing. That’s a great way to get the exact perks you want and save money. And when you see QA outsource benefits in action, you can always request additional support.

How to Choose a Company for Automated Performance Testing?

If you’re considering working with a QA provider, you should always start with research (not search). Typing in “QA companies” might not work in your favor, as there are many ads, paid placements, and superficial AI advice. The best way to start is by heading to reputable sources, like G2, Gartner, or Clutch. These platforms keep all the info you might need organized. You can find service descriptions, reviews, and even prices in one place. Here are the key things to look for.

Relevant Experience

Focus on organizations with proven experience in performance testing, especially in your industry or with apps similar to yours. Look through testimonials to figure out what kinds of projects a company worked with and what was the result of the cooperation. Be sure to check the firms’ sites to find case studies. And don’t hesitate to ask for references or schedule an introductory call.

Tool Proficiency

Make sure the external team is skilled in tools that fit your needs. Keep in mind that they shouldn’t push for tools of their choice, e.g., something they’re used to. They should help you choose software that’s right for you. Also, be sure to check out the available tech stack.

Clear Testing Process

Ask about the company’s testing approach. A good partner should have a structured process and be able to walk you through it on the spot. If you’re looking into developing a testing strategy from scratch, keep an eye out on how the provider approaches it. When they immediately go for “the standard flow”, it might signal that the team doesn’t understand your unique challenges and needs.

Scalability & Infrastructure

Ask if the team can scale up tests quickly, run them from different geographic regions, or simulate complex user behavior over time. They should have access to cloud-based testing platforms. Those allow crews to run large, distributed performance tests without hardware limits.

Detailed Reporting & Insights

With automated performance testing, there’s no “we’ve tested it, goodbye”. So, you should pay extra attention to what a provider does after test execution. Do they offer post-testing support? Can they present all-stakeholder-friendly reports (as opposed to highly technical or raw data)? Can they develop recommendations that are grounded and actionable? Be sure to discuss these points before you decide on the QA company.

Communication & Support

You want a partner who explains things clearly, updates you regularly, and responds quickly. If a team is hard to reach or dodgy with their answers, you can be sure that the entire cooperation will be like it — delayed and careless. If a provider brings up the aspect of communication channels and availability times early, that’s usually a good sign.

Flexibility & Cost Transparency

Look for flexible pricing and engagement models (project-based, hourly, etc.). And make sure there are no hidden costs, especially for tooling or cloud usage. For example, QA Madness offers a few cooperation modes, such as part-time, dedicated team (a crew centered on your needs at any time), and estimate (paying only for what’s done, whatever it may be).

Apart from the above, you should also inquire about data and IP protection measures. Automated performance testing often involves access to sensitive environments or data. So, ask about NDAs, data handling policies, and how test data is stored and deleted.

Finally, we recommend scheduling a preliminary meeting. It doesn’t obligate you to anything. But you can learn a lot about the provider by how the representative carries themselves, answers your questions, and what they ask about your project.

To Sum Up

Often, when people hear “automation”, they immediately think about speed, accuracy, and less manual effort. The thought about the amount of work it all requires comes second. That’s exactly how companies end up with a stressed team, less-than-desired quality, and a potentially sabotaged app. So, with automated performance testing, your priority should be getting everything it needs ready. That “everything” is usually just one thing — skills.

Because once you have genuine specialists on your crew, the rest is a done deal.