diff --git a/cerulean_cloud/cloud_run_orchestrator/clients.py b/cerulean_cloud/cloud_run_orchestrator/clients.py
index 3737f895..7749a436 100644
--- a/cerulean_cloud/cloud_run_orchestrator/clients.py
+++ b/cerulean_cloud/cloud_run_orchestrator/clients.py
@@ -1,6 +1,7 @@
 """Clients for other cloud run functions"""
 import asyncio
 import json
+import logging
 import os
 import zipfile
 from base64 import b64encode
@@ -74,28 +75,57 @@ async def get_base_tile_inference(
     ) -> InferenceResultStack:
         """fetch inference for base tiles"""
         async with semaphore:
+            logging.info("Fetching base tile.")
             img_array = await self.titiler_client.get_base_tile(
                 sceneid=self.sceneid, tile=tile, scale=self.scale, rescale=rescale
             )
+
+            logging.info("Reshaping image array.")
             img_array = reshape_as_raster(img_array)
+
+            logging.info("Getting tile bounds.")
             bounds = list(TMS.bounds(tile))
+
+            logging.info("Reading auxiliary datasets.")
             with self.aux_datasets.open() as src:
                 window = rasterio.windows.from_bounds(*bounds, transform=src.transform)
                 height, width = img_array.shape[1:]
                 aux_ds = src.read(window=window, out_shape=(height, width))
 
+            logging.info("Concatenating image arrays.")
             img_array = np.concatenate([img_array[0:1, :, :], aux_ds], axis=0)
 
+            logging.info("Encoding image to base64.")
             encoded = img_array_to_b64_image(img_array)
 
+            logging.info("Preparing payload for prediction.")
             inf_stack = [InferenceInput(image=encoded, bounds=TMS.bounds(tile))]
 
+            logging.info("Preparing payload for prediction.")
+
+            # Log the length of inf_stack
+            logging.info(f"Length of inf_stack: {len(inf_stack)}")
+
+            # Log a sample from inf_stack
+            logging.info(
+                f"Sample from inf_stack: {inf_stack[:1]}"
+            )  # adjust the slice as needed
+
+            # Log inf_parms
+            logging.info(f"inf_parms: {self.inference_parms}")
+
+            # Create and log the entire payload
             payload = PredictPayload(
                 inf_stack=inf_stack, inf_parms=self.inference_parms
             )
+            logging.info(f"Complete PredictPayload: {payload.dict()}")
+
+            logging.info(f"Sending request to {self.url + '/predict'}.")
             res = await self.client.post(
                 self.url + "/predict", json=payload.dict(), timeout=None
             )
+
+            logging.info("Processing response.")
         return InferenceResultStack(**res.json())
 
     async def get_offset_tile_inference(
diff --git a/cerulean_cloud/cloud_run_orchestrator/handler.py b/cerulean_cloud/cloud_run_orchestrator/handler.py
index e37f18d9..89e784d6 100644
--- a/cerulean_cloud/cloud_run_orchestrator/handler.py
+++ b/cerulean_cloud/cloud_run_orchestrator/handler.py
@@ -350,7 +350,7 @@ async def _orchestrate(
                     )
                     for base_tile in base_tiles
                 ],
-                return_exceptions=True,
+                return_exceptions=False,
             )
 
             logging.info("Inference on offset tiles!")
@@ -364,7 +364,7 @@ async def _orchestrate(
                     )
                     for offset_tile_bounds in offset_tiles_bounds
                 ],
-                return_exceptions=True,
+                return_exceptions=False,
             )
 
             if base_tiles_inference[0].stack[0].dict().get("classes"):
@@ -431,12 +431,10 @@ async def _orchestrate(
                     print(f"YYY error details: {e}")
                     print(f"YYY base_tiles_inference: {base_tiles_inference}")
                     print(f"YYY offset_tiles_inference: {offset_tiles_inference}")
-                    print(
-                        f"YYY [r for r in base_tiles_inference]: {[r for r in base_tiles_inference]}"
-                    )
-                    print(
-                        f"YYY [r for r in offset_tiles_inference]: {[r for r in offset_tiles_inference]}"
-                    )
+                    for r in base_tiles_inference:
+                        print(f"YYY [r for r in base_tiles_inference]: {r}")
+                    for r in offset_tiles_inference:
+                        print(f"YYY [r for r in offset_tiles_inference]: {r}")
                     raise e
 
             # XXXBUG ValueError: Cannot determine common CRS for concatenation inputs, got ['WGS 84 / UTM zone 28N', 'WGS 84 / UTM zone 29N']. Use `to_crs()` to transform geometries to the same CRS before merging."
@@ -453,6 +451,13 @@ async def _orchestrate(
             )
 
             for feat in merged_inferences.get("features"):
+                logging.info(
+                    f"XXX CHRISTIAN feat.get('properties') {feat.get('properties')}"
+                )
+                logging.info(f"XXX CHRISTIAN feat.get('id') {feat.get('id')}")
+                logging.info(
+                    f"XXX CHRISTIAN feat.get('geometry') {feat.get('geometry')}"
+                )
                 async with db_client.session.begin():
                     # mini_gdf = gpd.GeoDataframe(feat)
                     # if mini_gdf.intersects(land):