It is no secret that migrating to Mule 4 from Mule 3 is a challenge. Mule 4 saw the biggest change in the Mule runtime since its inception. However, with this series of “Mule 4 migration made easy” blogs, I will attempt to soothe any pain you might feel while migrating and provide tips and tricks on how to make the best from Mule 4.
After much hand wringing and collaborative sessions with teammates (most notably fellow Muleys Andrew Latham and Alison Jarris) and customers, a framework for how to think about agility has emerged that suggests a path about how to measure it (while not falling victim to Goodhart’s law).
This blog is the fourth and final part in a 4-part series on how to use a Slack bot to extract LaunchDarkly data. If you haven’t already, check out part one, part two, and part three of the series before pursuing the final steps of this demo.
This blog is the third part in a four-part series on how to use a Slack bot to extract LaunchDarkly data. If you haven’t already, check out part one and part two of the series before pursuing the steps in this demo.
This demo demonstrates how to use Anypoint Design Center’s flow designer to extract LaunchDarkly data (feature flags) using a Slack bot. The purpose of this demo is to provide a quick and efficient method to retrieve user profiles, including permissions. If you haven’t already, please check out part 1 of this blog series before moving on to part two.
In part two of the demo, we will create an API specification in API designer using the LD API,
In every software development process, there is always a need to test features and products before releasing them. This process can often be manual and requires providing specific users with permissions by ensuring that each user has the right security and governance. This process can become complex quickly, especially if you have a lot of users to manage and many features to flag.
When building DataWeave transformations for your Mule application, you will run into situations in which you will need to invoke external logic that may be encapsulated in a Java POJO, Groovy, Python, Ruby script, or really any lookup that uses a CSV file or database table as part of the transformation.
When integration involves different applications, systems, or databases, we face a common challenge: how do we bridge between data formats and how can we provide interoperability for fields that store dates and date/time values?
MuleSoft provides the most widely used integration platform for connecting any application, data source or API, whether in the cloud or on-premises. With Anypoint Platform®, MuleSoft delivers a complete integration experience built on proven open source technology, eliminating the pain and cost of point-to-point integration. Anypoint Platform includes CloudHub™ iPaaS, Mule ESB™, and a unified solution for API management™, design and publishing.