diff --git a/vissl/hooks/log_hooks.py b/vissl/hooks/log_hooks.py
index 3fcaa462e..a3f66f830 100644
--- a/vissl/hooks/log_hooks.py
+++ b/vissl/hooks/log_hooks.py
@@ -18,6 +18,7 @@
 from fvcore.common.file_io import PathManager
 from vissl.utils.checkpoint import is_checkpoint_phase
 from vissl.utils.env import get_machine_local_and_dist_rank
+from vissl.utils.events import VisslEventStorage
 from vissl.utils.io import create_file_symlink, save_file
 from vissl.utils.logger import log_gpu_stats
 from vissl.utils.perf_stats import PerfStats
@@ -153,6 +154,7 @@ def on_update(self, task: "tasks.ClassyTask") -> None:
             train_phase_idx = task.train_phase_idx
             log_freq = task.config["LOG_FREQUENCY"]
             iteration = task.iteration
+            evt_stg: VisslEventStorage = task.event_storage
 
             if torch.cuda.is_available():
                 peak_mem_used = int(torch.cuda.max_memory_allocated() / 1024.0 / 1024.0)
@@ -172,22 +174,21 @@ def on_update(self, task: "tasks.ClassyTask") -> None:
                 avg_time = sum(batch_times) / len(batch_times)
 
                 eta_secs = avg_time * (task.max_iteration - iteration)
-                eta_string = str(datetime.timedelta(seconds=int(eta_secs)))
                 if isinstance(task.optimizer.options_view.lr, set):
                     lr_val = list(task.optimizer.options_view.lr)
                 else:
                     lr_val = round(task.optimizer.options_view.lr, 5)
                 batch_time = int(1000.0 * avg_time)
                 rank = get_rank()
-                log_str = (
-                    f"Rank: {rank}; "
-                    f"[ep: {train_phase_idx}] "
-                    f"iter: {iteration}; "
-                    f"lr: {lr_val}; "
-                    f"loss: {loss_val}; "
-                    f"btime(ms): {batch_time}; "
-                    f"eta: {eta_string}; "
-                    f"peak_mem: {peak_mem_used}M"
+                evt_stg.put_scalars(
+                    rank=rank,
+                    epoch=train_phase_idx,
+                    iteration=iteration,
+                    lr=lr_val,
+                    loss=loss_val,
+                    batch_time=batch_time,
+                    eta=eta_secs,
+                    peak_mem_used=peak_mem_used,
                 )
                 if self.btime_freq and len(batch_times) >= self.btime_freq:
                     rolling_avg_time = (
@@ -200,12 +201,11 @@ def on_update(self, task: "tasks.ClassyTask") -> None:
                         datetime.timedelta(seconds=int(rolling_eta_secs))
                     )
                     rolling_btime = int(1000.0 * rolling_avg_time)
-                    log_str = (
-                        f"{log_str}; "
-                        f"btime({self.btime_freq}iters): {rolling_btime} ms; "
-                        f"rolling_eta: {rolling_eta_str}"
+                    evt_stg.put_scalars(
+                        rolling_btime=rolling_btime, rolling_eta=rolling_eta_str
                     )
-                logging.info(log_str)
+                for writer in task.event_storage_writers:
+                    writer.write()
 
 
 class LogLossMetricsCheckpointHook(ClassyHook):
diff --git a/vissl/trainer/train_task.py b/vissl/trainer/train_task.py
index 9a4780732..a614e03d4 100644
--- a/vissl/trainer/train_task.py
+++ b/vissl/trainer/train_task.py
@@ -111,6 +111,7 @@ def __init__(self, config: AttrDict):
         # communication as much as possible
         self.set_ddp_bucket_cap_mb()
         self.use_gpu = self.device.type == "cuda"
+        self.event_storage_writers = []
 
     def initiate_vissl_event_storage(self):
         from vissl.utils.events import create_event_storage, get_event_storage
@@ -118,6 +119,13 @@ def initiate_vissl_event_storage(self):
         create_event_storage()
         self._event_storage = get_event_storage()
 
+    def build_event_storage_writers(self):
+        from vissl.utils.events import JsonWriter
+
+        self.event_storage_writers = [
+            JsonWriter(f"{self.checkpoint_folder}/stdout.json")
+        ]
+
     @property
     def event_storage(self):
         return self._event_storage
diff --git a/vissl/trainer/trainer_main.py b/vissl/trainer/trainer_main.py
index b6b08aba4..94181ab96 100644
--- a/vissl/trainer/trainer_main.py
+++ b/vissl/trainer/trainer_main.py
@@ -89,6 +89,7 @@ def __init__(
 
         self.local_rank, self.distributed_rank = get_machine_local_and_dist_rank()
         self.task.initiate_vissl_event_storage()
+        self.task.build_event_storage_writers()
         self.setup_distributed(self.task.device.type == "cuda")
 
     def setup_distributed(self, use_gpu: bool):
@@ -186,7 +187,7 @@ def train(self):
                         logging.info("CUDA cache cleared")
                     task = train_step_fn(task)
                     iteration_num += 1
-                    task.local_iteration_num = iteration_num
+                    task.local_iteration_num = task.event_storage.iter = iteration_num
                     task.run_hooks(SSLClassyHookFunctions.on_step.name)
                 except StopIteration:
                     break
diff --git a/vissl/utils/events.py b/vissl/utils/events.py
index 7a698b8ad..adc06eaea 100644
--- a/vissl/utils/events.py
+++ b/vissl/utils/events.py
@@ -1,5 +1,7 @@
+import json
 from collections import defaultdict
 
+from fvcore.common.file_io import PathManager
 from fvcore.common.history_buffer import HistoryBuffer
 
 
@@ -114,3 +116,28 @@ def put_histogram(self, hist_name, hist_tensor, bins=1000):
     def put_image(self, img_name, img_tensor):
         # implement later for tensorboard
         return NotImplementedError
+
+
+class JsonWriter(VisslEventWriter):
+    def __init__(self, json_file):
+        """
+        Args:
+            json_file: path to the json file. New data will be appended if the file
+                       exists.
+        """
+        self._file_handle = PathManager.open(json_file, "a")
+
+    def write(self):
+        storage: VisslEventStorage = get_event_storage()
+        to_save = defaultdict(dict)
+
+        for k, (v, iter) in storage.latest().items():
+            # keep scalars that have not been written
+            to_save[iter][k] = v
+        for itr, scalars_per_iter in to_save.items():
+            scalars_per_iter["iteration"] = itr
+            self._file_handle.write(json.dumps(scalars_per_iter, sort_keys=True) + "\n")
+        self._file_handle.flush()
+
+    def close(self):
+        self._file_handle.close()