Thirty years ago, Sun Microsystems released Java to the world. In technology years, that makes Java ancient — older than Google, Facebook, and the iPhone combined. While countless Java "Killers" have come and gone, Java has done more than just survive the relentless pace of technological change; it has thrived by consistently solving the operational challenges that define modern DevOps ...
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Applications have become the foundation of today's enterprise, powering customer experiences, operational workflows, and core business services. But as application footprints grow, fueled by open-source components, third-party APIs, and AI-generated code, their risk surface expands just as fast. Traditional approaches to securing code late in the pipeline can no longer keep up ...
In the fast-evolving landscape of software development, 2025 marks a turning point: artificial intelligence is no longer just a tool — it's a central strategy. According to new findings from the 2025 Reveal Software Development Challenges Survey part two, a remarkable 73% of technology leaders now cite expanding AI use as their top priority ...
Prompt-based development is already changing how engineers get things done. Tasks that once took multiple manual steps — spinning up environments, writing scripts, or debugging errors — now start with a simple instruction, with an agent handling the rest, looping in the developer only when needed. This shift isn't about replacing engineers; it's about changing how they work. Instead of manually executing every step, engineers now focus more on orchestrating workflows ...
Behind every piece of software that lands in the hands of a customer is a story of chaotic collaboration, shifting priorities, and heroic project rescue missions. And the thing holding it together? It's not just process or tooling. It's strategy ...
Firewalls were built for a different world — static networks, predictable traffic, and clear perimeters ... The firewall has finally evolved, but only out of necessity. The newest generation isn't an appliance or virtual machine; it's cloud-native, AI-driven, and always-on. It doesn't guard a border; it lives where your workloads live. And if it's not doing that, it's irrelevant. But an evolved firewall by itself isn't enough, and you can't secure what you can't see — that's where most organizations are still exposed ...
Once, the castle-and-moat model of traditional firewalls offered a sense of safety, but the rules of network security have been rewritten. Static, perimeter-focused defenses are no longer sufficient in our cloud-first reality. Let's be clear: firewalls aren't going away; they're undergoing a metamorphosis to be more dynamic and integrated with application-level security, hand-in-hand with zero trust ...
A new survey from Lineaje revealed that nearly a third of security professionals (32%) believe they can deliver zero-vulnerability software despite the myriad threats and increasing compliance regulations. While 68% are more realistic, the initial number highlights some critical blind spots in organizations’ software supply chain defenses. Here are the other top findings from the research ...
AI has emerged as the newest "must-have" technology for companies, resulting in rising speculation into whether it will eventually replace low-code/no-code tools altogether. However, according to the 2025 App Development Trends Report from App Builder, that is not the case, with the report revealing that 76% of tech leaders are looking to AI to make their existing low-code/no-code tools more efficient instead of replacing them ...
DevOps teams are readily embracing modern tools that utilize large language models (LLMs), generative AI (GenAI), and the very buzzy agentic AI to accelerate their continuous integration/continuous delivery (CI/CD) pipelines ... But AI's tremendous potential business value is currently outshining some very real risks to mobile applications and the broader software supply chain ...
As the European Accessibility Act (EAA) deadline draws closer, my organization, Applause, just released the results of our fifth annual State of Digital Quality in Accessibility survey ... Let's start with the good news. Digital accessibility awareness has steadily grown over the past four years, with the majority of organizations considering it a priority ...
For many B2B and B2C enterprise brands, technology isn't a core strength. Relying on overly complex architectures (like those that follow a pure MACH doctrine) has been flagged by industry leaders as a source of operational slowdown, creating bottlenecks that limit agility in volatile market conditions ...
Over the past two years, code assistants based on generative AI have transformed software coding, accelerating the generation of code on an unprecedented level. Developers are deploying more code than ever, but at a cost: exponential growth in security vulnerabilities. New research points to a 3X increase in repositories containing Personally Identifiable Information (PII) and payment data, a 10X increase in APIs without authorization and input validation, and more sensitive API endpoints exposed, all threats proliferated by AI-generated code. Though AI code assistants boost productivity, they possess no understanding of organizational risk, compliance policies, or security best practices, leaving companies more exposed ...
CISA's Product Security Bad Practices paper is one that every company should review as it details the "exceptionally risky software development activities" that are all too common in the industry ... While CISA's efforts can help companies navigate the "need for speed" in a fast-moving DevOps environment, IT and security leaders across the private sector must do their part to prepare their companies for the necessary changes ...
Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...
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