Systems | Development | Analytics | API | Testing

If you're working with APIs, chances are that the term "API gateway" has popped up in a conversation or web search at least once. Although they are not new, many developers that are new to creating APIs (or deploying them into a production environment) haven't heard of them or don't fully understand what the technology does. In the most simple terms, an API gateway is a single entry point where API traffic comes in and is then proxied to your actual APIs.

Finance professionals aren’t afraid of AI taking their jobs, they’re afraid of being left behind while keeping them. The real anxiety in today’s finance teams isn’t automation, but irrelevance: the fear that the profession is evolving faster than their skills. This sentiment is increasingly common across organizations that acknowledge AI’s rising influence but haven’t yet aligned their training, expectations, or workflows with the new reality.

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Modern data platforms combine automation and generative AI to make data operations for every use case more accessible and scalable than ever.

Modern enterprise data strategies require seamless integration across cloud warehouses, legacy systems, and operational applications. Organizations report that 89% now operate multi-cloud environments, creating architectural complexity that traditional point solutions cannot address.

ETL tools automate the process of extracting data from source systems like Salesforce, transforming it into analysis-ready formats, and loading it into data warehouses, BI platforms, or other business applications. This automation eliminates the manual export/import cycles that drain resources and introduce inconsistencies.

In today’s world of software development, API-first has become more than a trend it is a best practice that allows teams to build scalable, modular and best of all future-ready applications. In an API-first approach, the Application Programming Interface (APIs) are not an afterthought, they are envisioned, documented and agreed upon before the development of an project in begins.

By Erez Schnaider, Technical Product Marketing Manager, ClearML Slurm has powered HPC environments for years. It is battle tested, widely adopted, and deeply embedded in research and engineering workflows. Over 60% of the TOP500 supercomputers use it to manage their large infrastructure, orchestrate workloads and schedule jobs, as it is powerful and versatile with over 20 years of engineering behind it.

Ably AI Transport is now in early access. It gives your AI the continuity, awareness, and multi-device reliability users actually expect. Drop it in, keep your existing stack, and start shipping Gen-2 AI right away.

The meeting started with a question I wasn't expecting. "Dragan, if AI can write tests now, what exactly will your team be doing next year?" Q1 2025, six months before I founded Quantum Quality Engineering. The executive wasn't hostile, just genuinely curious. Behind that curiosity lurked a more complex question: Do we still need QA leaders in an AI-driven world?