This lab introduces the concepts around logging.
After completing the lab, you will be able to:
Review the Logs slides.
You must have completed (or fast-forwarded to) the
Health Monitoring lab.
You must have your
pal-tracker application associated with the
actuator-solution codebase deployed and running on
Tanzu Application Service.
In a terminal window,
make sure you start in the
There are no code changes for this lab. It is discussion and demo only.
Logs are a crucial part of monitoring and observability in a modern cloud native application.
Tanzu Application Service (TAS) has rich support for handling logs in the following ways:
Tanzu Application Service has a rich log aggregation subsystem that supports cloud native applications writing to log streams.
The Diego subsystem takes care of capturing your application instance log streams and putting them into a single log stream for the application.
The Loggregator subsystem manages the aggregation of the log stream, including:
Loggregator is also used to stream Tanzu Application Service system metrics. You can read more about the architecture.
Tanzu Application Service does not perform the roles of log collection or analytics tools. It supports the ability to configure “drains” to output to a log collection or analytics tool of your choice, such as Splunk or Fluentd.
You can read more about the Tanzu Application Service Loggregator Architecture.
Review the Logs slides about how logging is handled on Tanzu Application Service.
Now that you have completed the lab, you should be able to: