Systems | Development | Analytics | API | Testing

From personal AI to the data that’ll train it, browse our bets on how AI develops in 2024 and beyond.

In the previous blog post we covered the high availability feature of Cloudera Operational Database (COD) in Amazon AWS. Cloudera recently released a new version of COD, which adds HA support to Microsoft Azure-based databases in the Cloud. In this post, we’ll perform a similar test to validate that the feature works as expected in Azure, too.

Snowflake kicked off 2024 with exciting releases, including Snowpark Model Registry, Streamlit in Snowflake for Azure, and new enhancements around security features in Snowflake Horizon. Read on to learn more about everything we announced in January.

Why does API architecture matter, and how can you excel at it? It’s an important question to ask as you are trying to improve existing APIs or write new ones. In this article, we will create a high-level roadmap to understanding the foundations of API architecture, from API Gateways and data management to architectural styles like RESTful and GraphQL. We will look at best practices to enhance scalability and security and look closer at tools that support robust API development.

Imagine your software transforming from merely a tool into a strategic partner that can automatically alert your users to trends, provide explanations of data with a click, and help you ask the right questions of your data-sets - in addition to delivering data-led insights. This is the power of AI analytics solutions for independent software vendors (ISV). Today's users demand more than just functionality. They crave intelligent software that analyzes data, surfaces insights, and empowers them to act.

At Honeybadger, we use Ahoy for first-party analytics in Rails. Ahoy is excellent for developers because it lives in your Rails application alongside your other data and code. Want to answer a specific question about your product or website visitors? It's just one ActiveRecord query away: Ahoy also works with Chartkick and Groupdate to visualize your data.

In my previous post, we discussed how to take advantage of VPA to implement automatic vertical scaling for our Konnect Data Planes. In this post, we'll focus on HPA for horizontal Kubernetes Pods autoscaling.

Since semiconductor design comes with complex challenges and high stakes – including strict regulations, tight time-to-market timelines, and an immense cost of error – teams need strong, trusted design tools. These teams turn to electronic design automation (EDA) software to streamline and automate chip design, predict certain elements of the design process, and test their technology as they develop it.