Test infrastructures change constantly. Your browsers update every few weeks, operating systems release frequent patches, and new device models keep entering the market.<\/p>\n\n\n\n
If you have your own test infrastructure, you already know that these modifications need reconfiguration. You have to update dependencies, validate compatibility, and ensure tests don\u2019t fail because of infrastructure changes.<\/p>\n\n\n\n
But this constant need to keep infrastructure in sync steals valuable engineering time.<\/p>\n\n\n\n
In this blog, we\u2019ll talk about the pain points of handling test infrastructure and explore some modern ways to eliminate this overhead.<\/p>\n\n\n\n
Start testing your apps on a scalable real device cloud with TestGrid. Request a free trial<\/a>.<\/p>\n\n\n\n Anyone who has been in the software testing<\/a> space would know that configuring and maintaining your test infrastructure is a core part of your quality assurance process. And it\u2019s important because after all, your test results depend largely on how stable and scalable the infrastructure is.<\/p>\n\n\n\n But what happens when setting up the test infrastructure<\/a> becomes your full-time job?<\/p>\n\n\n\n You have to constantly provision, debug, and maintain these systems. You don\u2019t even realize how much velocity you\u2019re losing when you\u2019re continuously context-switching between testing critical features and infrastructure upkeep.<\/p>\n\n\n\n Before testing, you need to:<\/p>\n\n\n\n Doing all of this manually can be overwhelming.<\/p>\n\n\n\n Routine infrastructure maintenance can actually negatively affect your QA engineer\u2019s productivity because they get caught up in analyzing environment failures, reproducing these failures locally, and validating environment parity rather than focusing on building test strategies<\/a>.<\/p>\n\n\n\n Your test environment needs regular updates to remain relevant. Which means you\u2019ll have to upgrade operating systems, drivers, and dependencies to match the real environment.<\/p>\n\n\n\n This task can be hectic, and in case any existing configurations or tests fail because of these changes, you\u2019ll end up spending a considerable amount of time fixing them.<\/p>\n\n\n\n Any app that you build today must run consistently across hundreds of different devices, browsers, and OS combinations. Now the tough part is replicating this diversity. On top of that, you also have to manage the tools and data involved in testing.<\/p>\n\n\n\n This can lead to coverage gaps and make it hard for you to reproduce issues associated with specific configurations.<\/p>\n\n\n\n Scaling your test infrastructure needs coordinated orchestration. You\u2019ll require additional compute resources, intelligent load balancing, and queue management for parallel testing<\/a>. And as a result, this increases your costs.<\/p>\n\n\n\n Your custom-built test infrastructure is flexible, but it can gradually turn into a legacy system. Closely interlinked testing frameworks<\/a>, bespoke test scripts, and environment-specific configurations can be hard to refactor or replace. So if you want to upgrade your tooling or adopt new testing platforms, you may need a lot of rework.<\/p>\n\n\n\n Your test coverage takes a hit when infrastructure is limited. Teams prefer a smaller set of devices and browsers to keep execution manageable, but as a result of this, many scenarios can go untested, particularly the ones tied to configurations you didn\u2019t consider during testing.<\/p>\n\n\n\n Because of limited capacity and scheduling constraints in self-managed infrastructure, your test execution can often get delayed. This can, in turn, build queues, limit parallelism, and delay retries, which stalls feedback loops and makes it hard for your developers to find and fix issues.<\/p>\n\n\n\n Network latency, resource contention, or misconfigured environments are issues that can cause intermittent failures, which may not be linked to actual defects. These false negatives can lead to misleading test results, and your team will have to rerun tests and invest time in verifying outcomes.<\/p>\n\n\n\n Realistic infrastructure setup, data states, network conditions, and external integrations can be really tough to simulate and resource-heavy, not to mention expensive. And without production-like parity, your test results may not show real-world behavior.<\/p>\n\n\n\n This gives your team on-demand scalability and removes the need for managing physical hardware. You can spin up environments when you need, execute tests in parallel, and tear them down once you\u2019re done with the execution.<\/p>\n\n\n\n Also Read<\/strong>: What is Cloud Testing? Tools, Examples, Use Cases & Best Practices<\/a><\/p>\n\n\n\n This approach helps you balance control and scalability. If you operate in regulated industries, hybrid deployment will give you a combination of on-premise infrastructure and cloud environments so you can scale testing while keeping your sensitive data in-house.<\/p>\n\n\n\n You can adopt version control systems like Git to maintain a history of the infrastructure changes. This will help your teams easily review the modifications, roll back when needed, and reduce configuration drift.<\/p>\n\n\n\n Speed and accuracy are critical in agile setups for continuous delivery. But manually configuring test infrastructure can be a lengthy process. You can leverage tools like Docker or Kubernetes to create reproducible test environments, minimize configuration errors, and integrate environment setup scripts into your CI\/CD pipeline<\/a>.<\/p>\n\n\n\n Now, here\u2019s a quick glimpse of the differences between traditional and cloud-based test environments.<\/p>\n\n\n\n\n\n\nWhat Managing Your Test Infrastructure Looks Like in Practice<\/strong><\/h2>\n\n\n\n
\n
The Operational Burden Test Infrastructure Management Creates<\/strong><\/h2>\n\n\n\n
1. Drains engineering bandwidth<\/strong><\/h3>\n\n\n\n
2. The compounding maintenance cost of test infrastructure<\/strong><\/h3>\n\n\n\n
3. Complex device and environment fragmentation<\/strong><\/h3>\n\n\n\n
4. Expensive scaling<\/strong><\/h3>\n\n\n\n
5. Creates long-term technical debt<\/strong><\/h3>\n\n\n\n
How This Hurts Your Testing Process<\/strong><\/h2>\n\n\n\n
1. Lower test coverage<\/strong><\/h3>\n\n\n\n
2. Slower feedback<\/strong><\/h3>\n\n\n\n
3. Flaky and unreliable tests<\/strong><\/h3>\n\n\n\n
4. Harder to replicate production issues<\/strong><\/h3>\n\n\n\n
Modern Alternatives to Efficiently Manage Test Infrastructure<\/strong><\/h2>\n\n\n\n
1. Use cloud-based infrastructures<\/strong><\/h3>\n\n\n\n
2. Choose hybrid deployment models if you need control<\/strong><\/h3>\n\n\n\n
3. Implement version control of test infrastructure configurations<\/strong><\/h3>\n\n\n\n
4. Automate test environment provisioning<\/strong><\/h3>\n\n\n\n