The Single Machine Performance 'Workload Checks' tool performs a nightly run of the Agent and compares that run to a series of 'checks' to determine if the Agent is fit for purpose: did we consume too much memory, did we achieve our throughput goals etc. This is done relative to a 'machine class', with the intention of simulating whether we are fit-for-purpose on a given type of machine, for a given type of workload that our customers would run.

In order for SMP's tooling to properly read a experiment directory please adhere to the following structure. Starting at the root:

• MACHINE_CLASS/ -- Required The directory that contains experiments for each class of machine. Please note that MACHINE_CLASS metasyntactic variable. For instance, we have typical for a "typical" machine class.

The structure of each machine class is as follows:

• machine.yaml -- Required The definition of the machine class, lays out resource limitations.
• cases/ -- Required The directory that contains each workload check experiment for the parent machine class. Each sub-directory is a separate experiment and the name of the directory is the name of the experiment, for instance tcp_syslog_to_blackhole. We call these sub-directories 'cases'.

The structure of each case is as follows:

• lading/lading.yaml -- Required The [lading] configuration inside its own directory. Directory will be mount read-only in the container built from Dockerfile above at /etc/lading.
• datadog-agent/ -- Required This is the configuration directory of your program. Will be mounted read-only in the container build from Dockerfile above at /etc/datadog-agent.
• experiment.yaml -- Optional This file can be used to set a single optimization goal for each experiment.