Systems | Development | Analytics | API | Testing

Transforming DevOps for Scientific Innovation:Materials Project's Cloud-Native Journey to 500K Users

The Lawrence Berkeley National Laboratory (Berkeley Lab) stands at the forefront of scientific discovery, driving innovations across energy, physics, biology, and computational research. The project harnesses the power of supercomputing and state-of-the-art methods to provide open web-based access to computed information on known and predicted materials..

How Observability Tools Empower Developers to Succeed

Note: A version of this article was originally published on CIO Influence. Burnout is widespread in the world of software engineering. According to a 2023 report, 73% of developers have experienced burnout at least once in their careers, and work-life balance has been cited as a key driver of developer satisfaction. Luckily, there are tools and strategies that teams can implement to reduce mental load, prevent burnout, and improve overall developer wellbeing.

How AI's API Boom in 2025 Reinforces the Need for Automated API Generation

API traffic now accounts for 57% of all Internet activity, fueled by AI adoption and the growing demand for real-time data. But this surge comes with challenges: complex development, lack of standardization, and security risks. Automated API generation is the solution.

Real-Time Redefined: Rethinking Kafka's Potential

When you’ve worked with data at scale, you come to appreciate the beauty and the complexity of systems like Kafka. With nearly 30 years of experience navigating the evolution of technology and data platforms, I’ve seen firsthand how Kafka has revolutionized real-time data processing - and where it can challenge even the best teams. The real question is: How do you move past those challenges to unleash everything Kafka has to offer?

Building AI Agents and Copilots with Confluent, Airy, and Apache Flink

From automating routine tasks to providing real-time insights to inform complex decisions, AI agents and copilots are poised to become an integral part of enterprise operations. At least that’s true for the organizations that can figure out how to supply large language models (LLMs) with real-time, contextualized, and trustworthy data in a secure and scalable way.

Top 10 Low-code Testing Tools | Updated For 2025

Low-code testing tools simplify the testing process. All of the complexity of coding is taken care of by the features designed by the development team of the tool. Thanks to these low-code tools, a little bit of technical know-how is more than enough to start testing. It opens up QA to a broader audience. In this article, we review the top low-code testing tools in 2025.

Is AI Falling Short of Expectations?

AI tools like Copilot and ChatGPT promised to revolutionize development workflows, but are they delivering or just creating new headaches? The stats speak volumes: 92% of developers say AI increases the blast radius of bad code 67% are spending more time debugging AI-generated code 59% face deployment errors at least half the time when using AI tools So, are we making strides toward innovation or spinning in circles of hype? @Marcus Merrell put it best: “This stuff was supposed to already start paying off by now. So why isn’t it working?”

Streamlining Deployments: How To Master Gitops With Fluxcd

Kubernetes (or K8s) is inherently complex, making it challenging to grasp and even harder to implement in deployments—especially for developers new to the technology.In addition to that, managing code changes in a Kubernetes cluster can be complex, especially when multiple applications are involved, as keeping track of changes, versions, and dependencies can be challenging, leading to conflicts that may impact cluster stability.

Snowflake Data Transformation: Unlocking the Power of Cloud Data Processing

In the era of cloud data platforms, Snowflake has emerged as a market leader, revolutionizing the way businesses store, process, and analyze data. However, the true value of Snowflake lies not only in its cloud data warehousing capabilities but also in its robust data transformation features. These transformations are critical for turning raw data into actionable insights, fueling data-driven decisions.