Add serve stress test (#7076)

ci/long_running_tests/ray-project/project.yaml

@@ -9,8 +9,8 @@ commands:
     help: "Start a long running stress test."
     command: |
       # Install nightly Ray wheels.
-      source activate tensorflow_p36 && pip install -U {{wheel}}
-      source activate tensorflow_p36 && pip install ray[dashboard,debug,rllib,tune] gym[atari]
+      source activate tensorflow_p36 && pip install -q -U {{wheel}} Click
+      source activate tensorflow_p36 && pip install -q ray[all] gym[atari]
       source activate tensorflow_p36 && python workloads/{{workload}}.py
     params:
       - name: wheel
@@ -18,7 +18,18 @@ commands:
         default: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.9.0.dev0-cp36-cp36m-manylinux1_x86_64.whl
       - name: workload
         help: "Name of the workload to run."
-        choices: ["actor_deaths", "apex", "impala", "many_actor_tasks", "many_drivers", "many_tasks", "node_failures", "pbt"]
+        choices:
+          [
+            "actor_deaths",
+            "apex",
+            "impala",
+            "many_actor_tasks",
+            "many_drivers",
+            "many_tasks",
+            "node_failures",
+            "pbt",
+            "serve",
+          ]
     config:
       tmux: true
 
@@ -29,3 +40,13 @@ commands:
   - name: show-output
     command: tmux capture-pane -p
     help: "Show tail of the workoad output."
+
+# Pathnames for files and directories that should be saved
+# in a snapshot but that should not be synced with a# session. Pathnames can be relative to the project
+# directory or absolute. Generally, this should be files
+# that were created by an active session, such as
+# application checkpoints and logs.
+output_files: []
+# For example, uncomment this to save the logs from the
+# last ray job.
+# "/tmp/ray/session_latest",

ci/long_running_tests/workloads/serve.py

@@ -0,0 +1,71 @@
+import time
+import subprocess
+from subprocess import PIPE
+
+import requests
+
+import ray
+from ray.experimental import serve
+from ray.cluster_utils import Cluster
+from ray.experimental.serve.kv_store_service import RayInternalKVStore
+
+num_redis_shards = 1
+redis_max_memory = 10**8
+object_store_memory = 10**8
+num_nodes = 5
+cluster = Cluster()
+for i in range(num_nodes):
+    cluster.add_node(
+        redis_port=6379 if i == 0 else None,
+        num_redis_shards=num_redis_shards if i == 0 else None,
+        num_cpus=8,
+        num_gpus=0,
+        resources={str(i): 2},
+        object_store_memory=object_store_memory,
+        redis_max_memory=redis_max_memory,
+        webui_host="0.0.0.0")
+
+print("Downloading load testing tool")
+subprocess.call([
+    "bash", "-c", "rm hey_linux_amd64 || true;"
+    "wget https://storage.googleapis.com/hey-release/hey_linux_amd64;"
+    "chmod +x hey_linux_amd64"
+])
+
+ray.init(address=cluster.address, include_webui=True, webui_host='0.0.0.0')
+serve.init(blocking=True, kv_store_connector=lambda ns: RayInternalKVStore(ns))
+
+
+@serve.route('/echo')
+@serve.accept_batch
+def echo(_):
+    time.sleep(0.01)  # Sleep for 10ms
+    ray.show_in_webui(str(serve.context.batch_size), key="Current batch size")
+    return ['hi {}'.format(i) for i in range(serve.context.batch_size)]
+
+
+print("Scaling to 30 replicas")
+config = serve.get_backend_config("echo:v0")
+config.num_replicas = 30
+config.max_batch_size = 16
+serve.set_backend_config("echo:v0", config)
+
+print("Warming up")
+for _ in range(5):
+    resp = requests.get("http://127.0.0.1:8000/echo").json()
+    print(resp)
+    time.sleep(0.5)
+
+connections = int(config.num_replicas * config.max_batch_size * 0.75)
+proc = subprocess.Popen(
+    [
+        "./hey_linux_amd64", "-c",
+        str(connections), "-z", "360m", "http://127.0.0.1:8000/echo"
+    ],
+    stdout=PIPE,
+    stderr=PIPE)
+print("started load testing")
+proc.wait()
+out, err = proc.communicate()
+print(out.decode())
+print(err.decode())