We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
allow output artifact store configuration (vs hard coded)
it seems like the output artifacts are always stored in a specific minio service, port, namespace, bucket, secrets, etc (`minio-service.kubeflow:9000`). 

see: https://github.com/kubeflow/pipelines/blob/f40a22a3f4a8e06d20cf3e3f425b5058d5c87e0b/sdk/python/kfp/compiler/_op_to_template.py#L148

it would be great to make it flexible, e.g. allow using S3, or change namespace or bucket names.
i suggest making it configurable, i can do such PR if we agree its needed. 
flexible pipeline service (host) path in client SDK 
when creating an SDK `Client()` the path to `ml-pipeline` API service is loaded from a hard coded value (`ml-pipeline.kubeflow.svc.cluster.local:8888`) which indicate a specific k8s namespace. it can be valuable to load that default value from an env variable, i.e. changing the line in `_client.py` from:

`config.host = host if host else Client.IN_CLUSTER_DNS_NAME`

to:

`config.host = host or os.environ.get('ML_PIPELINE_DNS_NAME',Client.IN_CLUSTER_DNS_NAME)`

also note that when a user provide the `host` parameter, the ipython output points to the API server and not to the UI service (see the logic in `_get_url_prefix()`), it seems like a potential bug

if its acceptable i can submit a PR for the line change above
 

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `samples/core/loop_parallelism/loop_parallelism.py`
Content:
```
1 # Copyright 2020 Google LLC
2 #
3 # Licensed under the Apache License, Version 2.0 (the "License");
4 # you may not use this file except in compliance with the License.
5 # You may obtain a copy of the License at
6 #
7 #      http://www.apache.org/licenses/LICENSE-2.0
8 #
9 # Unless required by applicable law or agreed to in writing, software
10 # distributed under the License is distributed on an "AS IS" BASIS,
11 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 # See the License for the specific language governing permissions and
13 # limitations under the License.
14 
15 import kfp.dsl as dsl
16 import kfp
17 
18 
19 @kfp.components.create_component_from_func
20 def print_op(s: str):
21     print(s)
22 
23 @dsl.pipeline(name='my-pipeline')
24 def pipeline2(my_pipe_param=10):
25     loop_args = [{'A_a': 1, 'B_b': 2}, {'A_a': 10, 'B_b': 20}]
26     with dsl.ParallelFor(loop_args, parallelism=1) as item:
27         print_op(item)
28         print_op(item.A_a)
29         print_op(item.B_b)
30 
31 
32 if __name__ == '__main__':
33     kfp.compiler.Compiler().compile(pipeline, __file__ + '.yaml')
34
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/samples/core/loop_parallelism/loop_parallelism.py b/samples/core/loop_parallelism/loop_parallelism.py
--- a/samples/core/loop_parallelism/loop_parallelism.py
+++ b/samples/core/loop_parallelism/loop_parallelism.py
@@ -21,9 +21,9 @@
     print(s)
 
 @dsl.pipeline(name='my-pipeline')
-def pipeline2(my_pipe_param=10):
+def pipeline():
     loop_args = [{'A_a': 1, 'B_b': 2}, {'A_a': 10, 'B_b': 20}]
-    with dsl.ParallelFor(loop_args, parallelism=1) as item:
+    with dsl.ParallelFor(loop_args, parallelism=10) as item:
         print_op(item)
         print_op(item.A_a)
         print_op(item.B_b)

{"golden_diff": "diff --git a/samples/core/loop_parallelism/loop_parallelism.py b/samples/core/loop_parallelism/loop_parallelism.py\n--- a/samples/core/loop_parallelism/loop_parallelism.py\n+++ b/samples/core/loop_parallelism/loop_parallelism.py\n@@ -21,9 +21,9 @@\n     print(s)\n \n @dsl.pipeline(name='my-pipeline')\n-def pipeline2(my_pipe_param=10):\n+def pipeline():\n     loop_args = [{'A_a': 1, 'B_b': 2}, {'A_a': 10, 'B_b': 20}]\n-    with dsl.ParallelFor(loop_args, parallelism=1) as item:\n+    with dsl.ParallelFor(loop_args, parallelism=10) as item:\n         print_op(item)\n         print_op(item.A_a)\n         print_op(item.B_b)\n", "issue": "allow output artifact store configuration (vs hard coded)\nit seems like the output artifacts are always stored in a specific minio service, port, namespace, bucket, secrets, etc (`minio-service.kubeflow:9000`). \r\n\r\nsee: https://github.com/kubeflow/pipelines/blob/f40a22a3f4a8e06d20cf3e3f425b5058d5c87e0b/sdk/python/kfp/compiler/_op_to_template.py#L148\r\n\r\nit would be great to make it flexible, e.g. allow using S3, or change namespace or bucket names.\r\ni suggest making it configurable, i can do such PR if we agree its needed. \nflexible pipeline service (host) path in client SDK \nwhen creating an SDK `Client()` the path to `ml-pipeline` API service is loaded from a hard coded value (`ml-pipeline.kubeflow.svc.cluster.local:8888`) which indicate a specific k8s namespace. it can be valuable to load that default value from an env variable, i.e. changing the line in `_client.py` from:\r\n\r\n`config.host = host if host else Client.IN_CLUSTER_DNS_NAME`\r\n\r\nto:\r\n\r\n`config.host = host or os.environ.get('ML_PIPELINE_DNS_NAME',Client.IN_CLUSTER_DNS_NAME)`\r\n\r\nalso note that when a user provide the `host` parameter, the ipython output points to the API server and not to the UI service (see the logic in `_get_url_prefix()`), it seems like a potential bug\r\n\r\nif its acceptable i can submit a PR for the line change above\r\n \n", "before_files": [{"content": "# Copyright 2020 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#      http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport kfp.dsl as dsl\nimport kfp\n\n\n@kfp.components.create_component_from_func\ndef print_op(s: str):\n    print(s)\n\n@dsl.pipeline(name='my-pipeline')\ndef pipeline2(my_pipe_param=10):\n    loop_args = [{'A_a': 1, 'B_b': 2}, {'A_a': 10, 'B_b': 20}]\n    with dsl.ParallelFor(loop_args, parallelism=1) as item:\n        print_op(item)\n        print_op(item.A_a)\n        print_op(item.B_b)\n\n\nif __name__ == '__main__':\n    kfp.compiler.Compiler().compile(pipeline, __file__ + '.yaml')\n", "path": "samples/core/loop_parallelism/loop_parallelism.py"}], "after_files": [{"content": "# Copyright 2020 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#      http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport kfp.dsl as dsl\nimport kfp\n\n\n@kfp.components.create_component_from_func\ndef print_op(s: str):\n    print(s)\n\n@dsl.pipeline(name='my-pipeline')\ndef pipeline():\n    loop_args = [{'A_a': 1, 'B_b': 2}, {'A_a': 10, 'B_b': 20}]\n    with dsl.ParallelFor(loop_args, parallelism=10) as item:\n        print_op(item)\n        print_op(item.A_a)\n        print_op(item.B_b)\n\n\nif __name__ == '__main__':\n    kfp.compiler.Compiler().compile(pipeline, __file__ + '.yaml')\n", "path": "samples/core/loop_parallelism/loop_parallelism.py"}]}