diff --git a/scouter/activities/gates.py b/scouter/activities/gates.py
index bc6f471..3815063 100644
--- a/scouter/activities/gates.py
+++ b/scouter/activities/gates.py
@@ -89,8 +89,8 @@ class Gates(BaseActivity):
             # Convert input data to DataFrame
             df = DataFrame(input_data['data'])
 
-            self.debug(
-                f"Aggregating time series data: {df.to_string()}",
+            self.info(
+                f"Aggregating time series data for {len(df)} rows",
                 metadata=metadata
             )
 
@@ -147,10 +147,16 @@ class Gates(BaseActivity):
                 }
 
             result_df = DataFrame(list(result.values()))
-            self.debug(
-                f"Aggregated data:\n {result_df.to_string()}",
+            self.info(
+                f"Aggregated data has {len(result_df)} rows",
                 metadata=metadata
             )
+
+            self.debug(
+                f"Aggregated data: {result_df.to_string()}",
+                metadata=metadata
+            )
+
             return result_df.to_dict()
 
         except Exception as e:
@@ -195,8 +201,8 @@ class Gates(BaseActivity):
         data = DataFrame(input_data['data'])
         model_tags = input_data['model_tags']
 
-        self.debug(
-            f"Applying quality gate to data: {data.to_string()}",
+        self.info(
+            f"Applying quality gate to data to {len(data)} rows",
             metadata=metadata
         )
 
@@ -249,8 +255,8 @@ class Gates(BaseActivity):
                 if policy == "DISCARD":
                     data = data[~data.index.isin(filtered_data.index)]
 
-        self.debug(
-            "Data quality gate applied",
+        self.info(
+            f"Data quality gate applied, final data has {len(data)} rows",
             metadata=metadata
         )
 
@@ -265,8 +271,18 @@ class Gates(BaseActivity):
         """
         metadata = input_data['metadata']
 
+        self.info(
+            f"Writing metrics for {metadata['model_name']}",
+            metadata=metadata
+        )
+
         metrics.LABORIOUS_DATA_WRITTEN_COUNT.labels(
             pod_id=self.pod_id,
             model_name=metadata['model_name'],
             pipeline_name=metadata['workflow_name']
         ).inc()
+
+        self.info(
+            f"Metrics written for {metadata['model_name']}",
+            metadata=metadata
+        )
diff --git a/scouter/activities/mongodb.py b/scouter/activities/mongodb.py
index 206df33..e36c563 100644
--- a/scouter/activities/mongodb.py
+++ b/scouter/activities/mongodb.py
@@ -87,7 +87,7 @@ class MongoDB(BaseActivity):
         collection_name = input_data['collection_name']
         last_data_timestamp = input_data['last_data_timestamp']
 
-        self.debug(
+        self.info(
             f"Loading data from MongoDB: {input_data}",
             metadata=metadata
         )
diff --git a/scouter/activities/redis.py b/scouter/activities/redis.py
index c3c504f..fb3f556 100644
--- a/scouter/activities/redis.py
+++ b/scouter/activities/redis.py
@@ -29,6 +29,8 @@ class Redis(RedisBase):
         metadata = input_data['metadata']
         key = f"last_data_timestamp_{input_data['workflow_name']}_{input_data['schedule_name']}"
 
+        self.info(f"Getting last data timestamp for {key}")
+
         try:
             data_hold = self.get(key)
         except Exception as e:
@@ -42,7 +44,7 @@ class Redis(RedisBase):
             )
             raise e
 
-        self.debug(
+        self.info(
             f"Last collected timestamp: {data_hold}",
             metadata=metadata
         )
@@ -60,6 +62,8 @@ class Redis(RedisBase):
         metadata = input_data['metadata']
         key = f"last_data_timestamp_{input_data['workflow_name']}_{input_data['schedule_name']}"
 
+        self.info(f"Putting last data timestamp for {key}")
+
         data = DataFrame(input_data['data'])
 
         if data.empty:
@@ -70,7 +74,7 @@ class Redis(RedisBase):
 
         last_data_timestamp = data['inserted_at'].max()
 
-        self.debug(
+        self.info(
             f"Last collected timestamp to insert: {last_data_timestamp}",
             metadata=metadata
         )
@@ -116,6 +120,8 @@ class Redis(RedisBase):
 
         key = f"held_data_{input_data['workflow_name']}_{input_data['schedule_name']}"
 
+        self.info(f"Getting held data for {key}")
+
         try:
             data_hold = self.get(key)
         except Exception as e:
@@ -137,6 +143,8 @@ class Redis(RedisBase):
                              )
                 return data_hold
 
+        self.info(f"Grouping and holding data for {len(data)} rows")
+
         try:
 
             # Remove possibly removed tags
@@ -195,8 +203,10 @@ class Redis(RedisBase):
             )
             raise e
 
+        self.info(f"Data held and melted has {len(data_hold_melted)} rows")
+
         self.debug(
-            f"Data grouped and held successfully:\n {data_hold_melted.to_string()}",
+            f"Data held and melted:\n {data_hold_melted.to_string()}",
             metadata=metadata
         )
 
diff --git a/scouter/worker/worker.py b/scouter/worker/worker.py
index cb1013d..9bdfcc2 100644
--- a/scouter/worker/worker.py
+++ b/scouter/worker/worker.py
@@ -1,5 +1,5 @@
 from temporalio import workflow, client
-from temporalio.worker import Worker
+from temporalio.worker import Worker, PollerBehaviorAutoscaling
 from temporalio.runtime import Runtime, TelemetryConfig, PrometheusConfig
 
 with workflow.unsafe.imports_passed_through():
@@ -99,11 +99,12 @@ async def main():
                 activities.write_metrics,
                 activities.store_data_package,
             ],
-            max_concurrent_workflow_tasks=100,
-            max_concurrent_activities=100,
-            max_concurrent_local_activities=100,
-            max_concurrent_workflow_task_polls=100,
-            max_cached_workflows=50,
+            max_concurrent_workflow_tasks=50,
+            max_concurrent_activities=50,
+            max_concurrent_local_activities=50,
+            max_cached_workflows=200,
+            workflow_task_poller_behavior=PollerBehaviorAutoscaling(),
+            activity_task_poller_behavior=PollerBehaviorAutoscaling()
         ),
         Worker(
             temporal_client,