Systems | Development | Analytics | API | Testing

The AI agent revolution is transforming how we work, but most analytics platforms are stuck in the past—forcing you to context-switch between your agents and separate BI tools to get data insights. This fragmented approach creates friction, breaks workflows, and ultimately slows down decision-making. When speed matters most, you need your AI agents to seamlessly access and analyze enterprise data without the traditional barriers of maintaining custom integrations and limited API functionality.

Imagine you’re closing a big deal with a Fortune 500 client. Everything looks good until they ask, “Are you SOC 2 compliant?” If you can’t answer with confidence, that deal might slip away. By 2025, with a threat landscape that evolves daily and customer trust is challenging to acquire, SOC 2 compliance has become the new baseline for doing business for SaaS, cloud services, fintech, and digital health vendors.

It’s 2 AM. Your release just broke again. CI pipelines were green, tests appeared clean, and the dashboard looked harmless. Yet, staging is down, and no one knows why. You're staring at static HTML reports and generic error logs. They show what failed, but give no clue why, no context, no trace, no help. It's like debugging in the dark. This is what outdated test reporting costs: lost hours, broken releases, and reactive firefighting when you should be sleeping or shipping.

If your organization has a complex Oracle deployment, or you are on a modernization journey — migrating to the cloud, preparing quarterly updates, or consolidating systems, you already know the stakes are high. Oracle systems and transformations are strategic, complex, and costly. But too often, they’re derailed by one silent saboteur: outdated, manual testing.

Regression test cases are a core part of any stable release cycle. They help you confirm that what used to work still works, even after new features are added or bug fixes are applied. But not every regression test case should be automated. Some are too brittle. Some don’t run often enough. Others are simply not worth the maintenance effort. So how do you decide which ones are worth automating? This article will guide you through exactly that.

Filtering events in REST APIs lets you request only the data you need, improving efficiency, reducing server load, and speeding up responses. The process involves using query parameters and operators to define conditions for retrieving specific records, like filtering by date, category, or status. Here's the core idea: Query Parameters: Add key-value pairs to the URL (e.g., ?date=2022-03-01) to filter events by specific fields.

Operational and analytical estates have been separated since data warehouses were first introduced in the 1990s. The operational estate includes microservices, software-as-a-service (SaaS) apps, and enterprise resource planning systems (ERPs) that have become the beating heart of an organization. The analytical estate consists of the data warehouses, lakehouses, artificial intelligence (AI)/machine learning (ML) platforms, and other custom batch workloads that support business analysis and reporting.

Imagine your development team just released a new feature to collect user preferences. Within hours, a data protection complaint from the EU lands on your legal team’s desk. The user claims they can’t delete their account—and worse, their data is being shared without consent. This isn’t a rare occurrence in today’s data-rich world. When GDPR compliance breaks, it’s not just about fines; it’s also about damaged reputation and lost customer trust.

As artificial intelligence (AI) reshapes industries, it’s quietly revolutionizing the heart of IT: The data center. The explosive growth of AI workloads is driving up power usage, challenging cooling systems, and demanding a fundamental rethink of how we store and move data. In this new landscape, flash storage stands out – delivering the performance, efficiency, and scalability that AI needs to truly accelerate.

At the 2025 instalment of its WWDC event, Apple set out its long-term vision for how we think about platform strategy, AI integration and multi-device architecture. If you’re a CTO, staff engineer, or mobile lead, this wasn’t just a conference to watch, it was one to plan your entire roadmap around. What Apple revealed at this year’s WWDS will affect everything from your frontend stack to how your systems talk to hardware.