Lessons from the CrowdStrike outage: A wake-up call for software testing

A wake-up call for prioritizing effective software testing

News By Mav Turner published 11 October 2024

In what might be perceived as the world's most significant IT outage, the CrowdStrike incident is likely to cost upwards of $5 billion in damages, also erasing billions from the cybersecurity company's own share price almost overnight. For organizations attempting to update and release software more quickly than ever, the lessons learned from the havoc wreaked by a single "buggy" endpoint security software update are poignant.

The CrowdStrike outage is the definitive illustration of the complications of software development and delivery today. The growing intricacies of the modern digital environment and the velocity and scope of software change make quality and reliability ever more challenging. Even when quality is a primary focus, as it was for CrowdStrike, delivering consistently high standards is no easy feat. Effective testing strategies are essential.

However, it's not uncommon for teams to push testing to the bottom of the priority pile in order to keep pace with delivery expectations. It's unfortunately considered a burden rather than a significant value driver.

Mav Turner

Chief Product and Strategy Officer at Tricentis.

From bottleneck to business enabler

With the right approach, testing can harness automation to ensure continuous and actionable feedback, and identify and target risks and defects early. Far from hindering speed, testing can actually shorten and enhance release cycles for high-quality products and services.

Automated testing has revolutionized software development, enabling teams to keep pace with projects' increasing speed and scale. It improves test coverage and accuracy when compared to manual approaches, as well as while delivering faster feedback - crucial for continuous integration and deployment (CI/CD) processes.

Particularly effective for regression testing and change validation, automated testing also pinpoints code changes for a more precise and efficient workflow. The advent of GenAI-powered testing tools further elevates this process by significantly reducing testing time and freeing up resources to identify complex issues that AI alone might miss.

But it's not just building test automation coverage; it's about ensuring the right development environments are in place to test changes, from development and staging to pre-production and production. In order to create a testing strategy that provides quality while limiting exposure to risk and downtime, it's vital to adapt testing according to the problem to be solved. That means looking at who and where the user is, their risk profile, how they are using the application, and whether it's on-prem or in the cloud.

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