Picture this scenario: you are a Rails developer and have spent the last couple of days developing that awesome feature that everyone is waiting for. It's big and complex, but it went through rigorous testing, so you are confident everything works as it should. There are deadlines to meet, so you deploy. Immediately, all hell breaks loose. Your feature straight up breaks the entire app for some of your users. It's hard to say why. No bugs showed up during testing.
In our final year as undergraduates, we researched how to use human affect and behaviors to anticipate threats posed by other humans. We built a simple website that demonstrated the capabilities of the model we designed.
Like most modern programming languages, Java includes the concept of exceptions to handle both errors and "exceptional events." When an exception occurs in your code, it disrupts the normal instruction logic and abnormally terminates the process. However, with a little foresight and code, you can often handle these exceptions gracefully, allowing your code to continue running and providing insight for tracking down the root cause of the unexpected result.
We’ve recently supported an organization who wanted to expose its Google Kubernetes Engine (GKE) backend behind Apigee X. A quite common architecture, which most of the users delivering modern web applications on Google Cloud tend to build upon. In this scenario, Google’s API gateway, Apigee, receives requests and performs L7 routing, redirecting you to the correct backend application, running as one or more pods on GKE.
ATLANTA, Ga. — June 6, 2022 — Katalon, Inc., the provider of a leading test automation platform, today announced the availability of the Katalon Test Automation Platform through AWS Marketplace as a SaaS contract, enabling customers to buy and immediately start using the test automation, orchestration, and management solution to be agile & innovative to support business requirements and to provide superior customer experience.
The algorithm team at WSC Sports faced a challenge. How could our computer vision model, that is working in a dynamic environment, maintain high quality results? Especially as in our case, new data may appear daily and be visually different from the already trained data. Bit of a head-scratcher right? Well, we’ve developed a system that is doing just that and showing exceptional results!
Today, we’re excited to announce the general availability of Continual, the missing AI layer for the modern data stack. We’ve also raised a $14.5M Series A, led by Innovation Endeavors and joined by Amplify Partners, Illuminate Ventures, Inspired Capital, Data Community Fund, Activation, New Normal, GTMfund, and angels Tomer Shiran, the founder of Dremio, and Tristan Handy, the founder of dbt Labs.
