chore: import upstream snapshot with attribution

tests/resources/example_docker_project/Dockerfile

@@ -0,0 +1,4 @@
+FROM python:3.10
+
+RUN apt-get update -y && apt-get install build-essential -y
+RUN pip install mlflow

tests/resources/example_docker_project/MLproject

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+name: docker-example
+
+docker_env:
+  image:  mlflow-docker-example
+
+entry_points:
+  main:
+    command: "echo 'Main entry point'"
+  test_tracking:
+    parameters:
+      use_start_run: bool
+    command: "python scripts/docker_tracking_test.py {use_start_run}"

tests/resources/example_docker_project/kubernetes_config.json

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+{
+  "kube-context": "docker-for-desktop",
+  "kube-job-template-path": "examples/docker/kubernetes_job_template.yaml",
+  "repository-uri": "username/mlflow-kubernetes-example"
+}

tests/resources/example_docker_project/scripts/docker_tracking_test.py

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+import sys
+import tempfile
+
+import mlflow
+
+
+def call_tracking_apis():
+    mlflow.log_metric("some_key", 3)
+    with tempfile.NamedTemporaryFile("w") as temp_file:
+        temp_file.write("Temporary content.")
+        mlflow.log_artifact(temp_file.name)
+
+
+def main(use_start_run):
+    if use_start_run:
+        with mlflow.start_run():
+            call_tracking_apis()
+    else:
+        call_tracking_apis()
+
+
+if __name__ == "__main__":
+    main(use_start_run=int(sys.argv[1]))