COVID-19 and its impact have demonstrated that change can be rapid, disruptive, and non-negotiable. This is especially relevant to enterprise risk management, where the challenge can be summed up in one word: recalibration. Many financial institutions have been investing in model-driven analysis and data-anchored approaches. We know that the models themselves must adapt as situations change. But what about the processes and policy governance that surround these models?

There’s no doubt that cloud has become ubiquitous, and thank goodness for that in 2020. We wouldn’t have survived the challenges of this year without cloud. It’s supported everything, from the sudden changes in the way we work to the way we access healthcare and even shop for vital goods. While cloud is the vehicle, it’s what sits on it that makes it so valuable — data.

Go ahead, search the interwebs. There are more posts and articles on “The Ten Commandments of Test Automation” than you can shake a test case at. Go ahead…I’ll wait. Welcome back! To set the stage, I have not read any of those articles. Well, more accurately, I’ve not read any of them recently; most of them I’ve not read at all. I probably read one or two of them in the “before times,” but I don’t remember any of the specific commandments.

With a modern data stack, Branch Insurance joins data from its transactional database and apps to visualize acquisition cost and lifetime value in real time.

Data from GitHub can help your engineers quantify how they are doing.

Today, we are proud to announce the general availability (GA) of one of the most important releases of Kong Enterprise we’ve had to date — Kong Enterprise 2.1 is here! This release represents a fundamental shift in how customers can deploy, manage and scale Kong Enterprise across their organizations.

Maintaining the performance and reliability of your API platform are two of the most important issues to ensure the continuing success of your product. APIs should run as efficiently as possible, and one way of safeguarding that is to rate limit, or constrain, the number of HTTP requests made in a given time period.

Automating repetitive processes is a key attribute in whole-product design. By combining payload observability with behavioral emails, Moesif is able to make you more productive through sophisticated workflows on many functional, performance and product issues. This article walks through how to set up playbooks that can save you time, resources and energy. We’ve highlighted a small number of key areas where our playbooks can assist you in the management of your product.