Systems | Development | Analytics | API | Testing

Greenfield Application Development Starts With Better Test Data

When teams start a greenfield application, they often face a simple problem with big consequences. They need to build and test fast, but they do not have production data to work with yet. That gap can slow down development, delay testing, and push teams into risky manual workarounds. In my experience working with App Dev leaders, this is where synthetic data has a clear role. It is not the answer to every test data challenge.

Perforce ALM vs Jira: Which is Best for Your Needs?

Atlassian Jira is an issue tracking tool for agile workflows. Perforce ALM is an all-in-one Application Lifecycle Management (ALM) solution that manages requirements, tests, and issues. Which will work best for your needs? While software development teams often start with simple issue tracking, their priorities change as projects scale and products become more complex. Choosing the tool that matches your needs now and in the future is key.

Why PHP LTS is a Lifeline for Companies Stuck on Unsupported Versions

Still running an older PHP version and not sure how to upgrade safely? In this clip from “The 2026 State of PHP” webinar, Zend PHP experts break down how to update PHP versions and discuss why it’s a critical part of legacy software modernization. For years, PHP was easy: install it, run it, and forget it. But today, organizations are being forced to rethink that approach as older versions reach end-of-life — leaving applications without security updates or support. And PHP LTS? It’s often the best answer.

The Truth About AI Web Development and Dev Productivity

Can AI solve the PHP talent shortage — or does it introduce new challenges? In this clip from a recent Zend webinar, “The 2026 State of PHP,” PHP experts Matthew Weier O’Phinney and Adam Culp explore how AI web development is changing the way teams modernize applications, and why AI alone isn’t the answer. AI is already accelerating development workflows, helping teams generate code, document processes, and move faster through modernization projects. But when it comes to replacing skilled engineers, the reality is more nuanced.

Why Static Analysis Is Still Essential in the Age of Claude AI Cybersecurity Scanning

It’s hard to keep up with how fast artificial intelligence is transforming organizations’ approach software security. Models like Claude Mythos Preview bring impressive new capabilities to the market, offering dynamic threat detection and adaptive learning. These advancements lead many engineering leaders to ask a critical question: Do we still need static analysis? The short answer is a definitive yes.

Data: The Key to Driving DevOps Business Success | Full IDC Webcast

More than 70% of organizations say DevOps strategy is a high or extremely high driver of business value. If you’re still struggling to reap such benefits and scale across the full application portfolio, this webinar will show you what leading teams are doing to close the gap.

7 Challenges Delivering Secure Aerospace Software in the Age of AI (with Solutions)

The challenge of any aerospace company is to deliver new capabilities without compromising safety, reliability, or precision. At our current juncture, legacy technology runs into conflict with modern tool stacks. Artificial intelligence (AI) creates fissures in compliance and auditability, and innovation and productivity gains come at a cost of greater complexity. Despite these seismic shifts, the central question remains the same.

The Push and Pull between Validation and Creativity

In this episode, Petr Nohejl of Warhorse Studios joins us to explore one of game development’s most constant tensions: creativity versus validation. From technical constraints like file naming limits and tooling rules to the challenge of keeping large teams productive, Petr shares real-world examples of why validation systems exist—and why they can feel frustrating to developers pushing creative boundaries. Together, we unpack how this “push and pull” ultimately leads to better-performing pipelines, more scalable production, and stronger games.

What Is Agile ALM (Application Lifecycle Management)?

Agile ALM manages the entire application lifecycle, including requirements, development, testing, and release, using Agile principles while maintaining end‑to‑end visibility and traceability. It supports iterative delivery, continuous feedback, and changing requirements to ensure that every decision and change is connected, auditable, and aligned with business and regulatory needs. The benefits of Agile ALM include.