Systems | Development | Analytics | API | Testing

Unaccounted data copies within non-production environments can make enterprises vulnerable to cyber theft. Non-production environments — which are often less secure than production environments — are treasure troves for hackers seeking to steal customer data. How many copies of test data are currently floating around your organization’s non-production environments?

FTI audits are designed to ensure sensitive tax data is properly protected. But in modern enterprises, they’re about much more than passing inspections. Today, you need to manage FTI securely while still enabling fast, reliable access to data across DevOps, analytics, and increasingly, AI workflows. Treating FTI audits as part of a broader data strategy helps teams reduce risk without slowing innovation or creating bottlenecks.

Software defects don’t just drain budgets; they cost businesses customer loyalty. Poor software quality can lead to poor customer experience and drive customer churn, resulting in missed revenue and increased expenses. Learn how better processes, such as test data management, can reduce the cost of software defects and protect your business outcomes.

With the rise of AI use in vehicle software development, concerns arise around its presence in safety-critical applications, especially when it comes to functional safety and regulatory compliance. ISO 26262, the essential standard for automotive development that requires processes for managing, designing, and verifying safety-critical systems, still applies. However, it can fall short when applied to AI models, which are inherently non-deterministic and continuously evolving.

The automotive industry has been undergoing significant changes as it works to adapt growing market demands and challenges associated with vehicles that are becoming much more software-defined. Here, we take a look at some notable automotive trends 2026, including highlights from our report, the 2026 State of Automotive Software Development, in partnership with Auto IQ and the Eclipse Foundation.

Data privacy laws continue to evolve and expand their reach, touching consumers, businesses, and regions of the world. The European Union’s General Data Protection Regulation (GDPR) has inspired many countries to establish their own regulations and set similar parameters for data collection. The Chile Data Protection Law is one of these regulations. While staying compliant isn’t always simple, it’s necessary for your operations and maintaining customer trust.

Organizations over the years have seen the writing on the wall: The future is cloud. Now, these companies and their DevOps teams areevolving, innovating, and pursuing new technologies, to gain a competitive edge and create new efficiencies. One of the ways they’re doing this is through application migration to cloud. In this blog, I’ll detail the nuances of application migration and how to best manage data during it, including various challenges and their solutions.

According to Perforce's 2026 State of DevOps report, there is a direct correlation between DevOps maturity and AI success. In a highly mature DevOps environment, AI accelerates innovation, optimizes workflows, and enhances security. In an immature environment, it scales chaos, multiplies risk, and inflates costs. So, before we ask ourselves how to make the most of our AI solutions, we must assess if our foundational processes are prepared for the challenge ahead.