Systems | Development | Analytics | API | Testing

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.

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.

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.

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.

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.

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

Outdated API documentation slows development and frustrates teams.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.

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.

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.

In modern web development, speed and reliability are combined you can deploy features quickly, but without proper testing, bugs might pass through and strike real users. That is where tools like Selenium IDE fit in – they enable you to automate browser interactions without writing a single line of code. As a person who just tried Selenium IDE on a test login form, I was amazed at how simple it is to create repeatable test flows in a matter of a few clicks.