In this article, we’re diving deep into the nuts and bolts of creating a private API gateway. From the initial installation to securing your API with keys and roles, we’ll walk you through every step of the process. Whether you’re looking to connect to a Microsoft SQL Server database or any other popular database, DreamFactory makes it a breeze, automating the tedious parts and letting you focus on what matters most: your data.

Welcome back to Yellowfin Japan’s ‘How to?’ blog series! In our previous blog, we went through how to capture data using Yellowfin's Data Transformation flow, and the preparation and steps for creating reports using Yellowfin View. It may seem like a lot of simple work, but as the number of reports to be created increases, the importance of data preparation becomes far more apparent. So, what about after you’ve done all the setup? Well, it’s now time to create reports!

The class of 2027 saw a massive influx of applications at top universities across the United States. Harvard received close to 57,000 applications for the class of 2027, while MIT received almost 27,000. UC Berkeley and UCLA, meanwhile, received 125,874 and 145,882 respectively. Manual transcript processing is an uphill battle for educational institutions at every level.

Did you know that the average enterprise utilizes over 1,500 APIs to drive its digital operations? APIs play a pivotal role in today’s data-driven landscape. However, few know the impact API architecture has in enhancing API performance.

Application programming interface (API) automation testing is a type of automated testing that focuses on the performance and functionality of APIs. This process can test APIs for correctness, compatibility, and efficiency. API automation testing can ensure that APIs function properly and meet consumers’ expectations. Here’s the key things to know about API automation testing: Table of Contents.

Here at SmartBear, our motto is that quality isn’t just the goal, it’s the whole point. The software development process is intricate and dynamic, with constant changes being made to meet evolving user requirements and address defects. However, with these changes come potential risks. One of the most significant challenges in software development is ensuring that making modifications to an application does not inadvertently break existing functionality.

Diving into the world of GitHub Actions can be like opening a treasure chest for your projects. Imagine having a magic wand that automates all the tedious bits of software development, from testing to deployment, all within GitHub’s cozy ecosystem. Let’s embark on this adventure together, shall we?

According to the U.S. Energy Information Administration (EIA), world energy consumption is forecasted to surge by almost 50% by 2050. This prediction underscores the urgent need for a concerted global push towards smarter, more efficient energy grids and resource management. According to the International Energy Agency (IEA), the global Internet of Things (IoT) deployment in power systems is expected to save $80 billion annually from 2016 to 2040, making up 5% of the total global power generation costs.

In this post, we're going to explore Karpenter, the ultimate solution for Node Autoscaling. Karpenter provides a cost-effective capability to implement your Kong Konnect Data Plane layer using the best EC2 Instances Types options available for your Kubernetes Nodes. See the previous posts in this series for more on Data Plane Elasticity and Pod Autoscaling with VPA, HPA, and Node Autoscaling with Cluster Autoscaler on Amazon EKS 1.29.

In the rapidly evolving landscape of API management, understanding the raw performance and reliability of your API gateway is not just an expectation — it's a necessity. At Kong, we're dedicated to ensuring our users have access to concrete, actionable data to guide their operational and development strategies.