5 tips for achieving performance engineering at scale

Enterprise application performance testing requires a high level of expertise because today’s applications are complex and require numerous supporting applications and systems. With each release, testers and developers must ensure that each one outperforms the last and doesn’t degrade in performance. But only a handful of experts within an organization can reliably measure the performance of a system as complex as the modern application stack.

And in today’s environment, the expertise required to tackle an organization’s performance engineering is not always readily available. As a result, companies find quality assurance a bottleneck as they struggle to keep up with release cycles. Or worse, experience outages that impact their business.

This predicament requires companies to consider how to scale daily published applications with limited resources. Because personal expertise is difficult to scale, organizations can leverage technology to help and support the needs of different types of teams, applications, and deployment models. This approach not only empowers DevOps teams, but strengthens and simplifies repeatability for project success.

What exactly does this approach look like? Where should companies start? And are there any major considerations for implementation? Let’s answer these questions through five key aspects of a successful implementation of performance engineering at scale.

1: Encouraging collaboration between experts and laypeople

Company-wide performance engineering is a team sport. A highly collaborative approach drives efficiency and effectiveness, and enables performance expertise to scale without the need for additional experts. Developers, performance engineers, business analysts, and others working as a team make it easy to design tests with agreed service level objectives (SLOs) that define measurable performance metrics. This ensures that everyone is measuring performance consistently and getting consistent results in the most efficient way. With consistent reporting, aspects such as root-cause analysis and trend reporting can be generated more easily across the board.

When operated effectively, performance engineering professionals assume more of an enabler role. Instead of taking responsibility for all testing themselves, they create the strategy and building blocks that enable non-professionals to test quickly and extensively. You can structure the testing environment, implement quality control guardrails, improve delivery pipelines, and embed best practices in performance engineering processes that empower distributed teams.

2: Automate performance testing in continuous integration (CI) pipelines

With today’s rapid development cycles, it’s impossible for performance engineers to manually create, run, and analyze daily performance tests for hundreds of code pushes. These skilled engineers should instead focus on more strategic tasks. By integrating automated performance testing into CI pipelines as part of pass/fail criteria, development teams can begin testing APIs, microservices, and components early in the development process and continue testing as the application develops.

3: Use no-code/low-code tools

When different teams need to tailor their performance testing approach to their unique needs, testing needs to be user-friendly. Widespread acceptance of testing tools correlates with ease of use and a shorter learning curve. Teams should look for tools that use no-code/low-code approaches that leverage intuitive drag-and-drop and point-and-click capabilities to maximize adoption and ensure high quality.

In addition to testing via a codeless GUI, the platform should specifically allow DevOps teams to run tests in the command line interface (CLI) or in their everyday integrated development environment (IDE). It’s important to use no-code/low-code tools to test quickly and release applications even faster. However, how quickly tests can be created is directly related to how easy the testing tool is to use, which is why tools with a simpler user interface are required.

4: Consider a cloud-native approach

Today’s organizations need to ensure their performance engineering approach is cloud-ready as more and more applications, processes, and tools move to the cloud. A company’s approach to performance engineering in the cloud should address several complexities.

First, performance engineering tools should be vendor neutral so that performance and scalability can be measured across different cloud providers such as Azure, Amazon Web Services and Google. If a cloud provider experiences a problem, organizations must have their applications ready to move quickly from one cloud provider to another to prevent their users from noticing a change. While this is mostly true for larger companies, understanding the impact your cloud service provider has on the provider is important to ensure your business success.

Additionally, when organizations are working on a migration initiative, whether it’s a lift-and-shift to the cloud, a new platform, or a refactoring, they must establish a performance baseline prior to migration and then validate it post-migration. Despite its complexity, it is important to run performance tests alongside any significant changes.

5: Choose a solution that covers all the bases

In adopting a unified approach to performance engineering, an organization should first standardize on a performance testing solution that is designed to support a wide range of enterprise testing needs. A typical organization employs a range of technologies and methodologies, executed by either centralized teams of internal and external experts, autonomous development teams, or a combination of both. A standardized platform must work equally well for each of these groups. Additionally, the chosen platform must test everything from legacy, enterprise-class monolithic core systems to dynamic, microservices-based applications and application packages to ensure the migrations or transitions do not result in performance degradation.

When targeting the solution, there should be a similarly broad technology coverage, from the latest frameworks to proven technologies. Organizations should be able to use the same solution to test individual APIs at the component level and the performance of all apps end-to-end. A standardized platform must work equally well for every scenario.

Finally, the platform you choose shouldn’t limit organizations to a single deployment option. Virtually every organization’s environment is a combination of network types: on-premises and multiple public cloud providers. As organizations continue to modernize their business, they need a solution that can test performance for complex migrations. For example, the switch from SAP to an S/4 HANA implementation.

Today’s companies not only demand, but expect the highest level of trust in the quality of their software releases. While there simply aren’t enough seasoned DevOps professionals to keep up with the rapid pace of development, an agile performance engineering approach enables organizations to empower non-skilled performance engineers to give organizations the predictability, validation, scalability, and security that they need. When companies create high levels of collaboration, use no-code/low-code tools and automation, think cloud-native, and choose solutions that can be used in all environments, they ensure their business and critical applications are ready for the are scalable for years to come.

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