Manufacturing has been one of the most prominent industries worldwide since the Industrial Revolution. Since then, from producing textiles to computer chips, manufacturers have always looked for ways to innovate. In the age of AI and APIs (or application programming interfaces), tech companies are looking for technological breakthroughs to gain an edge over the competition.

Cloudera’s data-in-motion architecture is a comprehensive set of scalable, modular, re-composable capabilities that help organizations deliver smart automation and real-time data products with maximum efficiency while remaining agile to meet changing business needs. In this blog, we will examine the “why” behind streaming data and review some high-level guidelines for how organizations should build their data-in-motion architecture of the future.

Idempotent operations produce the same result even when the operation is repeated many times. The result of the 2nd, 3rd, and 1,000th repeat of the operation will return exactly the same result as the 1st time. In this post, we will demystify the concept of idempotency—a fundamental property that ensures consistency, predictability, and reliability in APIs and distributed systems.

Test automation is no longer a cutting-edge technology. It is now a standard for any QA team looking to bring product quality to the next level. However, some testers are hesitant. They pose questions: does test automation actually bring ROI? Or perhaps they’re wary of the struggle with maintaining automation test scripts that break every time a new update is rolled out. It is those questions that deter business leaders from making the final decision, but they have a reason to be wary.

At Ably, we provide a realtime messaging service that aims to deliver messages between globally-distributed participants with the lowest latency possible. When powering apps that enable realtime collaboration, or require time-critical updates, low and consistent latency is essential.

The open-source philosophy and principles have always been about the democratization of knowledge—giving everyone the opportunity to access, learn, modify, and share software freely. As we see AI technologies seemingly taking over our day-to-day lives, we need those benefits in AI as well. Open-source AI inherits the open-source principles. It fosters transparency and collaboration, allowing us to build robust and secure AI systems.

Modern data platforms enable enterprises to extract valuable business insights from data, sourced from various origins. Data engineers, data scientists, and other data practitioners utilize both data streaming and batch processing frameworks as a means to provide these insights. While batch processes work on historical data, stream processing extracts insights in real time, enabling businesses to react faster with respect to changing events.

History is full of dynamic duos like peanut butter and jelly or Batman and Robin—but is it time to add APIs and ERPs to the mix? According to a 2019 study by Cloud Elements, APIs and ERPs are essential to modern business strategy. 55 percent of respondents believe that API integrations are “critical” to their operations. What’s more, the survey’s participants say that ERPs are one of their top three business use cases for API integrations.

Internal app sharing is a crucial step in ensuring the quality and functionality of applications before their public release. With the upcoming discontinuation of Microsoft's App Center, developers are looking for robust alternatives that streamline the distribution process and address common challenges faced during internal testing phases. This post explores the intricacies of internal app sharing, highlighting common obstacles and reviewing platforms designed to simplify the process.

At the heart of BPA is automation, which drives efficiency and reduces manual effort. Key elements to look for include: Effective data management is crucial for informed decision-making and operational efficiency. The right platform will offer a strong data fabric architecture to make this possible. A data fabric combines data management, integration, automation, and low-code development tools to build impactful and data-rich digital solutions.