![]() ![]() mule.env is an environment variable you should always aim to have by default (configured at the runtime level) so that you can easily tell which environment your application is running on. ![]() ) so that you can alter the logging behavior at runtime.Ĭ. ![]() While disabledFields doesn’t have a default value pointing to an environment variable, it might be a good idea to have it doing so (e.g. The recommended way to do it is by having your properties point to the pom.xml properties generated during build time leveraging something called “resource filtering.” In order to enable this, the snippet inside your pom.xml should look like: ī. Artifact Id: Equivalent to your application versionĪssuming you are following good SDLC practices, the chances are you are already maintaining your pom.xml thus, hard-coding or defining those exact same values elsewhere makes no sense.Artifact Name: Equivalent to your application name.Taking this a step further, we could assign an environment variable (e.g. The above example will effectively tell the JSON logger that it needs to skip any field defined here (you can add many comma-separated fields, e.g. PII or PCI data) in the message field, and any raw troubleshooting data into the content field, then we can leverage the “ disabled fields” feature to filter certain log fields from being printed (e.g. If somehow we are able to point our development team to the right direction and have them log valuable non-sensitive data (a.k.a. content: Field meant for raw data typically useful during development and test phases (e.g.message: Field meant for meaningful non-sensitive functional messages such as “Request received from Customer with ID: 1234”. ![]() For this purpose, JSON logger provides two very distinct fields out-of-the-box: troubleshooting data (typically raw data coming in and out of different components). What I propose is decoupling how we log functional data (data that provides meaningful application state information without including sensitive data) vs. After thinking about it for a long time, my answer is a combination of technology and development practices. Given an image (or JSON) says more than a thousand words, this is what it looks like:Īs you can see, critical troubleshooting information such as the name of the flow (rootContainer), name of the xml configuration file (fileName), and the exact line number where the logger is located (lineInFile) can now be part of the log metadata and configured through the global config element:Ī common request I’ve had ever since I published the first JSON logger was how to filter “sensitive” data, particularly in staging and production environments. This was one of my top wish list items from the DevKit era and something I was desperate to incorporate on the Mule 3 version of the JSON logger – and guess what? In Mule 4 with SDK, it is now a reality! As per the docs, now SDK offers the ability to obtain context information for our operations and have access, for instance, to the Location object which basically gives you everything you want to know about where are you in your application. How do we figure out where in our extensive beautiful code lies the specific log entry we are looking for? After all, we have tons of logger components throughout the application. Ok, we are set on the right path to logging our way to a better (devops) life, but then an issue arises and we need to figure out where inside the Mule application certain things are happening. If you ever used JSON logger in Mule 3, then these are some of the coolest changes in this release: If you did, then you will understand that the JSON logger connector had to be re-architected to keep the main tenet around customization through editing of JSON schemas (rather than having to fully understand the SDK innerworkings) and leverage all the new capabilities offered by the new SDK. You already read part 1 of this blog series.You already know about Mule 4’s new architecture and paradigms.If you are here, I’m assuming two things: ![]()
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