Per-service metrics http server

* Organize metrics into their respective service
* Server per-service metrics on a per-service http server
* Increase prometheus client usage over our custom metrics fields

awx/main/analytics/analytics_tasks.py

@@ -2,7 +2,7 @@
 import logging
 
 # AWX
-from awx.main.analytics.subsystem_metrics import Metrics
+from awx.main.analytics.subsystem_metrics import DispatcherMetrics, CallbackReceiverMetrics
 from awx.main.dispatch.publish import task
 from awx.main.dispatch import get_task_queuename
 
@@ -11,4 +11,5 @@ logger = logging.getLogger('awx.main.scheduler')
 
 @task(queue=get_task_queuename)
 def send_subsystem_metrics():
-    Metrics().send_metrics()
+    DispatcherMetrics().send_metrics()
+    CallbackReceiverMetrics().send_metrics()

awx/main/analytics/subsystem_metrics.py

@@ -1,10 +1,15 @@
+import itertools
 import redis
 import json
 import time
 import logging
 
+import prometheus_client
+from prometheus_client.core import GaugeMetricFamily, HistogramMetricFamily
+from prometheus_client.registry import CollectorRegistry
 from django.conf import settings
-from django.apps import apps
+from django.http import HttpRequest
+from rest_framework.request import Request
 
 from awx.main.consumers import emit_channel_notification
 from awx.main.utils import is_testing
@@ -13,6 +18,30 @@ root_key = settings.SUBSYSTEM_METRICS_REDIS_KEY_PREFIX
 logger = logging.getLogger('awx.main.analytics')
 
 
+class MetricsNamespace:
+    def __init__(self, namespace):
+        self._namespace = namespace
+
+
+class MetricsServerSettings(MetricsNamespace):
+    def port(self):
+        return settings.METRICS_SUBSYSTEM_CONFIG['server'][self._namespace]['port']
+
+
+class MetricsServer(MetricsServerSettings):
+    def __init__(self, namespace, registry):
+        MetricsNamespace.__init__(self, namespace)
+        self._registry = registry
+
+    def start(self):
+        try:
+            # TODO: addr for ipv6 ?
+            prometheus_client.start_http_server(self.port(), addr='localhost', registry=self._registry)
+        except Exception:
+            logger.error(f"MetricsServer failed to start for service '{self._namespace}.")
+            raise
+
+
 class BaseM:
     def __init__(self, field, help_text):
         self.field = field
@@ -148,76 +177,40 @@ class HistogramM(BaseM):
         return output_text
 
 
-class Metrics:
-    def __init__(self, auto_pipe_execute=False, instance_name=None):
+class Metrics(MetricsNamespace):
+    # metric name, help_text
+    METRICSLIST = []
+    _METRICSLIST = [
+        FloatM('subsystem_metrics_pipe_execute_seconds', 'Time spent saving metrics to redis'),
+        IntM('subsystem_metrics_pipe_execute_calls', 'Number of calls to pipe_execute'),
+        FloatM('subsystem_metrics_send_metrics_seconds', 'Time spent sending metrics to other nodes'),
+    ]
+
+    def __init__(self, namespace, auto_pipe_execute=False, instance_name=None, metrics_have_changed=True, **kwargs):
+        MetricsNamespace.__init__(self, namespace)
+
         self.pipe = redis.Redis.from_url(settings.BROKER_URL).pipeline()
         self.conn = redis.Redis.from_url(settings.BROKER_URL)
         self.last_pipe_execute = time.time()
         # track if metrics have been modified since last saved to redis
         # start with True so that we get an initial save to redis
-        self.metrics_have_changed = True
+        self.metrics_have_changed = metrics_have_changed
         self.pipe_execute_interval = settings.SUBSYSTEM_METRICS_INTERVAL_SAVE_TO_REDIS
         self.send_metrics_interval = settings.SUBSYSTEM_METRICS_INTERVAL_SEND_METRICS
         # auto pipe execute will commit transaction of metric data to redis
         # at a regular interval (pipe_execute_interval). If set to False,
         # the calling function should call .pipe_execute() explicitly
         self.auto_pipe_execute = auto_pipe_execute
-        Instance = apps.get_model('main', 'Instance')
         if instance_name:
             self.instance_name = instance_name
         elif is_testing():
             self.instance_name = "awx_testing"
         else:
-            self.instance_name = Instance.objects.my_hostname()
+            self.instance_name = settings.CLUSTER_HOST_ID  # Same as Instance.objects.my_hostname() BUT we do not need to import Instance
 
-        # metric name, help_text
-        METRICSLIST = [
-            SetIntM('callback_receiver_events_queue_size_redis', 'Current number of events in redis queue'),
-            IntM('callback_receiver_events_popped_redis', 'Number of events popped from redis'),
-            IntM('callback_receiver_events_in_memory', 'Current number of events in memory (in transfer from redis to db)'),
-            IntM('callback_receiver_batch_events_errors', 'Number of times batch insertion failed'),
-            FloatM('callback_receiver_events_insert_db_seconds', 'Total time spent saving events to database'),
-            IntM('callback_receiver_events_insert_db', 'Number of events batch inserted into database'),
-            IntM('callback_receiver_events_broadcast', 'Number of events broadcast to other control plane nodes'),
-            HistogramM(
-                'callback_receiver_batch_events_insert_db', 'Number of events batch inserted into database', settings.SUBSYSTEM_METRICS_BATCH_INSERT_BUCKETS
-            ),
-            SetFloatM('callback_receiver_event_processing_avg_seconds', 'Average processing time per event per callback receiver batch'),
-            FloatM('subsystem_metrics_pipe_execute_seconds', 'Time spent saving metrics to redis'),
-            IntM('subsystem_metrics_pipe_execute_calls', 'Number of calls to pipe_execute'),
-            FloatM('subsystem_metrics_send_metrics_seconds', 'Time spent sending metrics to other nodes'),
-            SetFloatM('task_manager_get_tasks_seconds', 'Time spent in loading tasks from db'),
-            SetFloatM('task_manager_start_task_seconds', 'Time spent starting task'),
-            SetFloatM('task_manager_process_running_tasks_seconds', 'Time spent processing running tasks'),
-            SetFloatM('task_manager_process_pending_tasks_seconds', 'Time spent processing pending tasks'),
-            SetFloatM('task_manager__schedule_seconds', 'Time spent in running the entire _schedule'),
-            IntM('task_manager__schedule_calls', 'Number of calls to _schedule, after lock is acquired'),
-            SetFloatM('task_manager_recorded_timestamp', 'Unix timestamp when metrics were last recorded'),
-            SetIntM('task_manager_tasks_started', 'Number of tasks started'),
-            SetIntM('task_manager_running_processed', 'Number of running tasks processed'),
-            SetIntM('task_manager_pending_processed', 'Number of pending tasks processed'),
-            SetIntM('task_manager_tasks_blocked', 'Number of tasks blocked from running'),
-            SetFloatM('task_manager_commit_seconds', 'Time spent in db transaction, including on_commit calls'),
-            SetFloatM('dependency_manager_get_tasks_seconds', 'Time spent loading pending tasks from db'),
-            SetFloatM('dependency_manager_generate_dependencies_seconds', 'Time spent generating dependencies for pending tasks'),
-            SetFloatM('dependency_manager__schedule_seconds', 'Time spent in running the entire _schedule'),
-            IntM('dependency_manager__schedule_calls', 'Number of calls to _schedule, after lock is acquired'),
-            SetFloatM('dependency_manager_recorded_timestamp', 'Unix timestamp when metrics were last recorded'),
-            SetIntM('dependency_manager_pending_processed', 'Number of pending tasks processed'),
-            SetFloatM('workflow_manager__schedule_seconds', 'Time spent in running the entire _schedule'),
-            IntM('workflow_manager__schedule_calls', 'Number of calls to _schedule, after lock is acquired'),
-            SetFloatM('workflow_manager_recorded_timestamp', 'Unix timestamp when metrics were last recorded'),
-            SetFloatM('workflow_manager_spawn_workflow_graph_jobs_seconds', 'Time spent spawning workflow tasks'),
-            SetFloatM('workflow_manager_get_tasks_seconds', 'Time spent loading workflow tasks from db'),
-            # dispatcher subsystem metrics
-            SetIntM('dispatcher_pool_scale_up_events', 'Number of times local dispatcher scaled up a worker since startup'),
-            SetIntM('dispatcher_pool_active_task_count', 'Number of active tasks in the worker pool when last task was submitted'),
-            SetIntM('dispatcher_pool_max_worker_count', 'Highest number of workers in worker pool in last collection interval, about 20s'),
-            SetFloatM('dispatcher_availability', 'Fraction of time (in last collection interval) dispatcher was able to receive messages'),
-        ]
         # turn metric list into dictionary with the metric name as a key
         self.METRICS = {}
-        for m in METRICSLIST:
+        for m in itertools.chain(self.METRICSLIST, self._METRICSLIST):
             self.METRICS[m.field] = m
 
         # track last time metrics were sent to other nodes
@@ -230,7 +223,7 @@ class Metrics:
             m.reset_value(self.conn)
         self.metrics_have_changed = True
         self.conn.delete(root_key + "_lock")
-        for m in self.conn.scan_iter(root_key + '_instance_*'):
+        for m in self.conn.scan_iter(root_key + '-' + self._namespace + '_instance_*'):
             self.conn.delete(m)
 
     def inc(self, field, value):
@@ -297,7 +290,7 @@ class Metrics:
     def send_metrics(self):
         # more than one thread could be calling this at the same time, so should
         # acquire redis lock before sending metrics
-        lock = self.conn.lock(root_key + '_lock')
+        lock = self.conn.lock(root_key + '-' + self._namespace + '_lock')
         if not lock.acquire(blocking=False):
             return
         try:
@@ -307,9 +300,10 @@ class Metrics:
                 payload = {
                     'instance': self.instance_name,
                     'metrics': serialized_metrics,
+                    'metrics_namespace': self._namespace,
                 }
                 # store the serialized data locally as well, so that load_other_metrics will read it
-                self.conn.set(root_key + '_instance_' + self.instance_name, serialized_metrics)
+                self.conn.set(root_key + '-' + self._namespace + '_instance_' + self.instance_name, serialized_metrics)
                 emit_channel_notification("metrics", payload)
 
                 self.previous_send_metrics.set(current_time)
@@ -331,14 +325,14 @@ class Metrics:
         instances_filter = request.query_params.getlist("node")
         # get a sorted list of instance names
         instance_names = [self.instance_name]
-        for m in self.conn.scan_iter(root_key + '_instance_*'):
+        for m in self.conn.scan_iter(root_key + '-' + self._namespace + '_instance_*'):
             instance_names.append(m.decode('UTF-8').split('_instance_')[1])
         instance_names.sort()
         # load data, including data from the this local instance
         instance_data = {}
         for instance in instance_names:
             if len(instances_filter) == 0 or instance in instances_filter:
-                instance_data_from_redis = self.conn.get(root_key + '_instance_' + instance)
+                instance_data_from_redis = self.conn.get(root_key + '-' + self._namespace + '_instance_' + instance)
                 # data from other instances may not be available. That is OK.
                 if instance_data_from_redis:
                     instance_data[instance] = json.loads(instance_data_from_redis.decode('UTF-8'))
@@ -357,6 +351,120 @@ class Metrics:
         return output_text
 
 
+class DispatcherMetrics(Metrics):
+    METRICSLIST = [
+        SetFloatM('task_manager_get_tasks_seconds', 'Time spent in loading tasks from db'),
+        SetFloatM('task_manager_start_task_seconds', 'Time spent starting task'),
+        SetFloatM('task_manager_process_running_tasks_seconds', 'Time spent processing running tasks'),
+        SetFloatM('task_manager_process_pending_tasks_seconds', 'Time spent processing pending tasks'),
+        SetFloatM('task_manager__schedule_seconds', 'Time spent in running the entire _schedule'),
+        IntM('task_manager__schedule_calls', 'Number of calls to _schedule, after lock is acquired'),
+        SetFloatM('task_manager_recorded_timestamp', 'Unix timestamp when metrics were last recorded'),
+        SetIntM('task_manager_tasks_started', 'Number of tasks started'),
+        SetIntM('task_manager_running_processed', 'Number of running tasks processed'),
+        SetIntM('task_manager_pending_processed', 'Number of pending tasks processed'),
+        SetIntM('task_manager_tasks_blocked', 'Number of tasks blocked from running'),
+        SetFloatM('task_manager_commit_seconds', 'Time spent in db transaction, including on_commit calls'),
+        SetFloatM('dependency_manager_get_tasks_seconds', 'Time spent loading pending tasks from db'),
+        SetFloatM('dependency_manager_generate_dependencies_seconds', 'Time spent generating dependencies for pending tasks'),
+        SetFloatM('dependency_manager__schedule_seconds', 'Time spent in running the entire _schedule'),
+        IntM('dependency_manager__schedule_calls', 'Number of calls to _schedule, after lock is acquired'),
+        SetFloatM('dependency_manager_recorded_timestamp', 'Unix timestamp when metrics were last recorded'),
+        SetIntM('dependency_manager_pending_processed', 'Number of pending tasks processed'),
+        SetFloatM('workflow_manager__schedule_seconds', 'Time spent in running the entire _schedule'),
+        IntM('workflow_manager__schedule_calls', 'Number of calls to _schedule, after lock is acquired'),
+        SetFloatM('workflow_manager_recorded_timestamp', 'Unix timestamp when metrics were last recorded'),
+        SetFloatM('workflow_manager_spawn_workflow_graph_jobs_seconds', 'Time spent spawning workflow tasks'),
+        SetFloatM('workflow_manager_get_tasks_seconds', 'Time spent loading workflow tasks from db'),
+        # dispatcher subsystem metrics
+        SetIntM('dispatcher_pool_scale_up_events', 'Number of times local dispatcher scaled up a worker since startup'),
+        SetIntM('dispatcher_pool_active_task_count', 'Number of active tasks in the worker pool when last task was submitted'),
+        SetIntM('dispatcher_pool_max_worker_count', 'Highest number of workers in worker pool in last collection interval, about 20s'),
+        SetFloatM('dispatcher_availability', 'Fraction of time (in last collection interval) dispatcher was able to receive messages'),
+    ]
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(settings.METRICS_SERVICE_DISPATCHER, *args, **kwargs)
+
+
+class CallbackReceiverMetrics(Metrics):
+    METRICSLIST = [
+        SetIntM('callback_receiver_events_queue_size_redis', 'Current number of events in redis queue'),
+        IntM('callback_receiver_events_popped_redis', 'Number of events popped from redis'),
+        IntM('callback_receiver_events_in_memory', 'Current number of events in memory (in transfer from redis to db)'),
+        IntM('callback_receiver_batch_events_errors', 'Number of times batch insertion failed'),
+        FloatM('callback_receiver_events_insert_db_seconds', 'Total time spent saving events to database'),
+        IntM('callback_receiver_events_insert_db', 'Number of events batch inserted into database'),
+        IntM('callback_receiver_events_broadcast', 'Number of events broadcast to other control plane nodes'),
+        HistogramM(
+            'callback_receiver_batch_events_insert_db', 'Number of events batch inserted into database', settings.SUBSYSTEM_METRICS_BATCH_INSERT_BUCKETS
+        ),
+        SetFloatM('callback_receiver_event_processing_avg_seconds', 'Average processing time per event per callback receiver batch'),
+    ]
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(settings.METRICS_SERVICE_CALLBACK_RECEIVER, *args, **kwargs)
+
+
 def metrics(request):
-    m = Metrics()
-    return m.generate_metrics(request)
+    output_text = ''
+    for m in [DispatcherMetrics(), CallbackReceiverMetrics()]:
+        output_text += m.generate_metrics(request)
+    return output_text
+
+
+class CustomToPrometheusMetricsCollector(prometheus_client.registry.Collector):
+    """
+    Takes the metric data from redis -> our custom metric fields -> prometheus
+    library metric fields.
+
+    The plan is to get rid of the use of redis, our custom metric fields, and
+    to switch fully to the prometheus library. At that point, this translation
+    code will be deleted.
+    """
+
+    def __init__(self, metrics_obj, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self._metrics = metrics_obj
+
+    def collect(self):
+        my_hostname = settings.CLUSTER_HOST_ID
+
+        instance_data = self._metrics.load_other_metrics(Request(HttpRequest()))
+        if not instance_data:
+            logger.debug(f"No metric data not found in redis for metric namespace '{self._metrics._namespace}'")
+            return None
+
+        host_metrics = instance_data.get(my_hostname)
+        for _, metric in self._metrics.METRICS.items():
+            entry = host_metrics.get(metric.field)
+            if not entry:
+                logger.debug(f"{self._metrics._namespace} metric '{metric.field}' not found in redis data payload {json.dumps(instance_data, indent=2)}")
+                continue
+            if isinstance(metric, HistogramM):
+                buckets = list(zip(metric.buckets, entry['counts']))
+                buckets = [[str(i[0]), str(i[1])] for i in buckets]
+                yield HistogramMetricFamily(metric.field, metric.help_text, buckets=buckets, sum_value=entry['sum'])
+            else:
+                yield GaugeMetricFamily(metric.field, metric.help_text, value=entry)
+
+
+class CallbackReceiverMetricsServer(MetricsServer):
+    def __init__(self):
+        registry = CollectorRegistry(auto_describe=True)
+        registry.register(CustomToPrometheusMetricsCollector(DispatcherMetrics(metrics_have_changed=False)))
+        super().__init__(settings.METRICS_SERVICE_CALLBACK_RECEIVER, registry)
+
+
+class DispatcherMetricsServer(MetricsServer):
+    def __init__(self):
+        registry = CollectorRegistry(auto_describe=True)
+        registry.register(CustomToPrometheusMetricsCollector(CallbackReceiverMetrics(metrics_have_changed=False)))
+        super().__init__(settings.METRICS_SERVICE_DISPATCHER, registry)
+
+
+class WebsocketsMetricsServer(MetricsServer):
+    def __init__(self):
+        registry = CollectorRegistry(auto_describe=True)
+        # registry.register()
+        super().__init__(settings.METRICS_SERVICE_WEBSOCKETS, registry)

awx/main/consumers.py

@@ -106,7 +106,7 @@ class RelayConsumer(AsyncJsonWebsocketConsumer):
         if group == "metrics":
             message = json.loads(message['text'])
             conn = redis.Redis.from_url(settings.BROKER_URL)
-            conn.set(settings.SUBSYSTEM_METRICS_REDIS_KEY_PREFIX + "_instance_" + message['instance'], message['metrics'])
+            conn.set(settings.SUBSYSTEM_METRICS_REDIS_KEY_PREFIX + "-" + message['metrics_namespace'] + "_instance_" + message['instance'], message['metrics'])
         else:
             await self.channel_layer.group_send(group, message)
 

awx/main/dispatch/worker/base.py

@@ -168,7 +168,7 @@ class AWXConsumerPG(AWXConsumerBase):
         init_time = time.time()
         self.pg_down_time = init_time - self.pg_max_wait  # allow no grace period
         self.last_cleanup = init_time
-        self.subsystem_metrics = s_metrics.Metrics(auto_pipe_execute=False)
+        self.subsystem_metrics = s_metrics.DispatcherMetrics(auto_pipe_execute=False)
         self.last_metrics_gather = init_time
         self.listen_cumulative_time = 0.0
         if schedule:

awx/main/dispatch/worker/callback.py

@@ -72,7 +72,7 @@ class CallbackBrokerWorker(BaseWorker):
     def __init__(self):
         self.buff = {}
         self.redis = redis.Redis.from_url(settings.BROKER_URL)
-        self.subsystem_metrics = s_metrics.Metrics(auto_pipe_execute=False)
+        self.subsystem_metrics = s_metrics.CallbackReceiverMetrics(auto_pipe_execute=False)
         self.queue_pop = 0
         self.queue_name = settings.CALLBACK_QUEUE
         self.prof = AWXProfiler("CallbackBrokerWorker")

awx/main/management/commands/run_callback_receiver.py

@@ -3,6 +3,7 @@
 
 from django.conf import settings
 from django.core.management.base import BaseCommand
+from awx.main.analytics.subsystem_metrics import CallbackReceiverMetricsServer
 
 from awx.main.dispatch.control import Control
 from awx.main.dispatch.worker import AWXConsumerRedis, CallbackBrokerWorker
@@ -25,6 +26,9 @@ class Command(BaseCommand):
             print(Control('callback_receiver').status())
             return
         consumer = None
+
+        CallbackReceiverMetricsServer().start()
+
         try:
             consumer = AWXConsumerRedis(
                 'callback_receiver',

awx/main/management/commands/run_dispatcher.py

@@ -10,6 +10,7 @@ from awx.main.dispatch import get_task_queuename
 from awx.main.dispatch.control import Control
 from awx.main.dispatch.pool import AutoscalePool
 from awx.main.dispatch.worker import AWXConsumerPG, TaskWorker
+from awx.main.analytics.subsystem_metrics import DispatcherMetricsServer
 
 logger = logging.getLogger('awx.main.dispatch')
 
@@ -62,6 +63,8 @@ class Command(BaseCommand):
 
         consumer = None
 
+        DispatcherMetricsServer().start()
+
         try:
             queues = ['tower_broadcast_all', 'tower_settings_change', get_task_queuename()]
             consumer = AWXConsumerPG('dispatcher', TaskWorker(), queues, AutoscalePool(min_workers=4), schedule=settings.CELERYBEAT_SCHEDULE)

awx/main/management/commands/run_wsrelay.py

@@ -16,6 +16,7 @@ from awx.main.analytics.broadcast_websocket import (
     RelayWebsocketStatsManager,
     safe_name,
 )
+from awx.main.analytics.subsystem_metrics import WebsocketsMetricsServer
 from awx.main.wsrelay import WebSocketRelayManager
 
 
@@ -91,6 +92,8 @@ class Command(BaseCommand):
         return host_stats
 
     def handle(self, *arg, **options):
+        WebsocketsMetricsServer().start()
+
         # it's necessary to delay this import in case
         # database migrations are still running
         from awx.main.models.ha import Instance

awx/main/scheduler/task_manager.py

@@ -68,7 +68,7 @@ class TaskBase:
         # initialize each metric to 0 and force metric_has_changed to true. This
         # ensures each task manager metric will be overridden when pipe_execute
         # is called later.
-        self.subsystem_metrics = s_metrics.Metrics(auto_pipe_execute=False)
+        self.subsystem_metrics = s_metrics.DispatcherMetrics(auto_pipe_execute=False)
         self.start_time = time.time()
 
         # We want to avoid calling settings in loops, so cache these settings at init time
@@ -105,7 +105,7 @@ class TaskBase:
             try:
                 # increment task_manager_schedule_calls regardless if the other
                 # metrics are recorded
-                s_metrics.Metrics(auto_pipe_execute=True).inc(f"{self.prefix}__schedule_calls", 1)
+                s_metrics.DispatcherMetrics(auto_pipe_execute=True).inc(f"{self.prefix}__schedule_calls", 1)
                 # Only record metrics if the last time recording was more
                 # than SUBSYSTEM_METRICS_TASK_MANAGER_RECORD_INTERVAL ago.
                 # Prevents a short-duration task manager that runs directly after a

awx/main/tasks/system.py

@@ -62,7 +62,7 @@ from awx.main.tasks.receptor import get_receptor_ctl, worker_info, worker_cleanu
 from awx.main.consumers import emit_channel_notification
 from awx.main import analytics
 from awx.conf import settings_registry
-from awx.main.analytics.subsystem_metrics import Metrics
+from awx.main.analytics.subsystem_metrics import DispatcherMetrics
 
 from rest_framework.exceptions import PermissionDenied
 
@@ -113,7 +113,7 @@ def dispatch_startup():
     cluster_node_heartbeat()
     reaper.startup_reaping()
     reaper.reap_waiting(grace_period=0)
-    m = Metrics()
+    m = DispatcherMetrics()
     m.reset_values()
 
 

awx/main/wsrelay.py

@@ -20,7 +20,6 @@ from awx.main.analytics.broadcast_websocket import (
     RelayWebsocketStats,
     RelayWebsocketStatsManager,
 )
-import awx.main.analytics.subsystem_metrics as s_metrics
 
 logger = logging.getLogger('awx.main.wsrelay')
 
@@ -54,7 +53,6 @@ class WebsocketRelayConnection:
         self.protocol = protocol
         self.verify_ssl = verify_ssl
         self.channel_layer = None
-        self.subsystem_metrics = s_metrics.Metrics(instance_name=name)
         self.producers = dict()
         self.connected = False
 

awx/settings/defaults.py

@@ -1076,6 +1076,35 @@ HOST_METRIC_SUMMARY_TASK_LAST_TS = None
 HOST_METRIC_SUMMARY_TASK_INTERVAL = 7  # days
 
 
+# TODO: cmeyers, replace with with register pattern
+# The register pattern is particularly nice for this because we need
+# to know the process to start the thread that will be the server.
+# The registration location should be the same location as we would
+# call MetricsServer.start()
+# Note: if we don't get to this TODO, then at least create constants
+# for the services strings below.
+# TODO: cmeyers, break this out into a separate django app so other
+# projects can take advantage.
+
+METRICS_SERVICE_CALLBACK_RECEIVER = 'callback_receiver'
+METRICS_SERVICE_DISPATCHER = 'dispatcher'
+METRICS_SERVICE_WEBSOCKETS = 'websockets'
+
+METRICS_SUBSYSTEM_CONFIG = {
+    'server': {
+        METRICS_SERVICE_CALLBACK_RECEIVER: {
+            'port': 8014,
+        },
+        METRICS_SERVICE_DISPATCHER: {
+            'port': 8015,
+        },
+        METRICS_SERVICE_WEBSOCKETS: {
+            'port': 8016,
+        },
+    }
+}
+
+
 # django-ansible-base
 ANSIBLE_BASE_TEAM_MODEL = 'main.Team'
 ANSIBLE_BASE_ORGANIZATION_MODEL = 'main.Organization'