Systems | Development | Analytics | API | Testing

Agentic coding tools like Cursor, GitHub Copilot, and OpenAI’s Codex are reshaping how software is developed. They enable developers to offload routine tasks and accelerate feature delivery. However, these tools also introduce new challenges – particularly in how we test and validate the code they produce.

API gateway federation refers to the integration and management of multiple API gateways within a unified control plane. This approach allows organizations to use different API gateways, which may be from various vendors or tailored to specific environments (e.g., cloud-based, on-premises), while centrally managing their configurations, policies, and monitoring. Figure 1: API gateway federation with a unified control plane.

Outdated API documentation slows development and frustrates teams. Automating API documentation updates within your CI/CD pipelines solves this by keeping docs accurate, reducing errors, and saving time. Here's how.

AI failures rarely look like crashes. More often, they appear as confident but incorrect answers, subtle bias, or culturally inappropriate responses.

SAP’s business practices impact how enterprises access and integrate their data. This is the first blog in a multi-part series exploring how to access and best leverage your SAP data.

Another day, another API. Fueled by AI-assisted coding and agile workflows, the speed of innovation has never been higher. But for the compliance team? It’s panic mode. Every new API must follow a minefield of internal rules: security protocols, naming conventions, reuse policies, documentation standards. And while the dev team is flying forward, compliance is stuck doing manual reviews, chasing specs, and untangling inconsistencies often after the code is already written.

Everyone thinks AI is getting cheaper. But is it really? At first glance, the economics of AI seem to be improving for everyone. Thanks to continued model optimization and advances in hardware, the cost of running LLMs (also known as inference) is steadily decreasing. Developers today can access incredibly powerful models at a fraction of what it cost just a year ago. But there’s a catch.

Business intelligence platforms analyze vast amounts of data, requiring visualization engines that balance performance, flexibility, and ease of use. Traditional charting libraries treat each chart type as a distinct entity, requiring separate logic and code for each. This approach leads to code duplication, limited reusability, and reduced maintainability. Additionally, it’s cumbersome to effectively layer or combine visual elements due to these libraries’ rigid composability.

Whether you're exploring trends, uncovering outliers, or designing presentations that tell a compelling story, your insights should be connected and pervasive. It's no longer enough to simply see your data. You need a fluid, intuitive experience that empowers you to find next-level insights faster. We’re thrilled to announce ThoughtSpot’s new-and-improved visualization platform, built with integrated intelligence to empower limitless interactivity.

Let’s start with DevOps, the buzzword that changed how we think about building and shipping software. These days, every college student and other professional wants to become a DevOps engineer. If you are an aspiring DevOps engineer or already working as a DevOps engineer, this blog will help you understand the difference between Platform engineering and Devops Platform engineering is really changing every company’s perspective on developing platforms.