In a flash, CrowdStrike went from cybersecurity titan to cautionary tale. A single flawed software update triggered what is likely a $5 billion disaster. As billions vanished from their stock price overnight, this incident underscores a crucial lesson for every organization pushing the limits of rapid software releases-no speed is worth the cost of cutting corners in testing and quality control.
Author: Mav Turner, Chief Product and Strategy Officer, Tricentis
As the digital landscape becomes increasingly more complex and software evolves at a rapid pace, maintaining quality and reliability is more challenging than ever. The CrowdStrike blackout showcases the hurdles software development and delivery face today – teams are expected to meet Olympic speed deadlines and, as a result, often deprioritize testing to stay on track. Consequently, testing frequently falls behind as it is mistakenly viewed as a burden rather than a value driver.
Even for established companies like CrowdStrike, where quality is a top priority, maintaining consistently high standards is challenging. Organizations must adopt a strong testing plan to stay at the forefront of innovation and performance.
From hurdle to competitive edge
With the right strategies in place, testing can effectively harness automation to provide ongoing, actionable insights, while identifying risks and defects early in the process. Rather than slowing down operations, testing speeds up and refines release cycles, enabling faster delivery of top-tier products and services.
We are seeing the use of automation enable teams to stay agile under growing demands, shifting the focus from merely catching errors to proactively enhancing development processes. This process significantly increases coverage and precision over manual methods, making it a reliable tool for catching errors. It also provides quicker feedback, which is essential for successful continuous integration and deployment (CI/CD) processes. Automated systems can also assist in regression testing and change validation, quickly identifying code modifications, ensuring a streamlined and accurate workflow. GenAI-driven testing tools further enhance this process by reducing testing times and freeing up resources to address complex issues that AI tools might overlook.
However, testing must go beyond just automation coverage-the appropriate testing environments must be in place at every stage, from development and staging to before and during production. A testing strategy to deliver high-quality results while minimizing risks and interruption must be tailored to specific challenges. Developers should consider who the end-user is, where they are located, their risk level, how they interact with the application, and whether their system operates on-premise or in the cloud.
Minimizing risks at every stage through user-focused testing strategies
Grasping how users interact with a product across various environments is critical for determining where to concentrate testing efforts. User personas can simulate real-world scenarios, thoroughly evaluating all relevant use cases and settings. By aligning testing with users’ behaviors, needs, and contexts, teams are able to establish a more focused approach that concentrates on high-priority areas to uncover problems early. This method also guarantees steady execution through a range of operating systems, devices, and application technologies. It helps prevent potential failures, ensuring a seamless and compatible user experience no matter how customers access the software.
Preparing for spikes in traffic and demand is essential to avoid disastrous outcomes. Under high loads, critical systems can slow to a crawl or even crash entirely. An example of this was Taylor Swift‘s concert ticket sales. An unprecedented amount of interest left systems overwhelmed and users stranded on the website, waiting hours to complete their purchase. This debacle shows why performance and load testing are so crucial; these tests can help mitigate the fallout from sudden surges in website and application traffic, ensuring that systems remain reliable and perform under pressure. By incorporating performance testing into every phase of the software development life cycle (SDLC), teams are better able to pinpoint potential obstacles early on, ensuring systems are equipped to handle real-world demands without failure.
Maximizing testing output amid resource limitations
Identifying the right areas to test can be challenging. This is especially true when resources are scarce, and prioritization is key. Furthermore, teams must remember that software testing does not just end within an organization’s own infrastructure. Third-party integrations like payment providers should be just as dependable and resilient. Reducing these external risks requires a proactive partnership between the organization with their third-party vendors who are managing critical business applications, and assessing their methods for addressing any defective code originating from their systems.
By employing service virtualization, teams can simulate external interactions, ensuring their applications perform optimally under different conditions. Integrating chaos testing into this process is also key to revealing vulnerabilities and reinforcing the system’s ability to handle unforeseen disruptions. Most of today’s SaaS applications push frequent updates, and when these rely on external providers, rapid and automated regression testing is essential to mitigate potential risks. As development speeds increase and testing requirements grow, adopting no-code or low-code platforms, paired with AI-generated code, allows teams to roll out updates and features at a faster pace.
Strengthening digital resilience through evolved software testing
Maintaining error-free software is no small feat in today’s fast-paced digital landscape. The Taylor Swift ticket sale fiasco and the CrowdStrike outage serve as a stark reminder to all businesses that they must rethink their software testing strategies. Ensuring consistent quality and reliability throughout the development lifecycle is important to prevent similar disruptions in the future. By acting now, companies can better prepare for upcoming challenges and safeguard against potential failures.
About the Author
Mav Turner is the Chief Product and Strategy Officer at Tricentis, a global leader in continuous testing. In his role, Mav oversees research and development as well as product growth and strategy aimed at enabling organizations to accelerate their digital transformation.
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