Platform engineering is a software development approach that combines DevOps principles to elevate the developer experience. It focuses on designing and constructing toolchains and workflows that promote self-service capabilities for software engineering teams. By addressing security, compliance, and operational efficiency, platform engineering enables organizations to build robust internal systems tailored to the needs of both developers and operations teams.

Welcome to the first installment of a series of posts discussing the recently announced Cloudera AI Inference service. Today, Artificial Intelligence (AI) and Machine Learning (ML) are more crucial than ever for organizations to turn data into a competitive advantage. To unlock the full potential of AI, however, businesses need to deploy models and AI applications at scale, in real-time, and with low latency and high throughput. This is where the Cloudera AI Inference service comes in.

Snowflake leaders offer insight on AI, open source and cybersecurity development — and the fundamental leadership skills required — in the years ahead. As we come to the end of a calendar year, it’s natural to contemplate what the new year will hold for us. It’s an understatement to say that the future is very hard to predict, but it’s possible to both prepare for the likeliest outcomes and stay ready to adapt to the unexpected.

In the new age of Industry 4.0 the shopfloor is no longer an isolated environment. It’s the heartbeat of manufacturing operations, responsible for producing, monitoring, and refining goods. But since the lines blur between operational technology (OT) on the shopfloor and information technology (IT) in the enterprise, integrating these systems has become a formidable challenge.

For many organizations, Workday is a core system housing vital data on HR, payroll, finance, and more. However, extracting and utilizing that data for analysis can be a challenge. The new Simba Workday ODBC and JDBC Drivers simplify this process, enabling seamless access to Workday data through standard database interfaces. With Simba Drivers, you can effortlessly integrate Workday data into your analytics tools, ETL workflows, or custom applications, unlocking its full potential for decision-making.

Democratizing and sharing data inside and outside your organization, as a real-time data stream, has never been more in demand. Treating data as-a-product and adopting Data Mesh practices is leading the way. Here, we explain the concept through a real-life example of an airline building applications that process data across different domains.

In today’s digital world, user experience (UX) plays a key role in a product’s success. Studies show that 88% of online users are less likely to return to a website after a poor experience.

SmartBear is thrilled to announce our acquisition of QMetry, a leader in AI-enhanced test management solutions, into the family. This merger is not merely about expanding our already robust solutions—it’s about revolutionizing the delivery of software quality across industries. In today’s fast-paced tech landscape, addressing software quality issues is critical; they can significantly impact customer satisfaction and financial growth, while flattening the quality cost curve.

The need to democratize and share data inside and outside your organization, as a real-time data stream, has never been more in demand. Treating real-time data as a product, and adopting Data Mesh practices, is the way forward. Here, we explain the concept through a real-life example of an airline building applications that process data across different domains.