diff --git a/autoparallel/api.py b/autoparallel/api.py
index 387228a6..74a75a0c 100644
--- a/autoparallel/api.py
+++ b/autoparallel/api.py
@@ -13,6 +13,7 @@
 from torch._inductor.decomposition import select_decomp_table
 from torch._inductor.fx_passes.joint_graph import joint_graph_passes
 from torch._inductor.fx_passes.post_grad import remove_assert_ops
+from torch._logging import trace_structured
 from torch._subclasses import FakeTensorMode
 from torch.distributed.tensor import DeviceMesh
 
@@ -287,6 +288,14 @@ def build_model_graph(self):
         # give more room for optimizations
         _add_alias(gm)
         apply_node_renaming(gm, self.params_len, self.buffer_len, self.metadata)
+        trace_structured(
+            "artifact",
+            metadata_fn=lambda: {
+                "name": "autoparallel_joint_graph",
+                "encoding": "string",
+            },
+            payload_fn=lambda: str(gm.graph),
+        )
 
         self.gm = gm
 
@@ -330,7 +339,16 @@ def optimize_placement(self, verbose=True):
         self.sharding_placement = self.sharding_optimizer.get_solution(verbose=False)
 
         if verbose:
-            self.sharding_optimizer.print()
+            print(self.sharding_optimizer.get_log())
+
+        trace_structured(
+            "artifact",
+            metadata_fn=lambda: {
+                "name": "autoparallel_sharding_optimizer_log",
+                "encoding": "string",
+            },
+            payload_fn=lambda: self.sharding_optimizer.get_log(colored=False),
+        )
 
         if self.sharding_optimizer.prob.status == -1:
             raise RuntimeError("Didn't find solution")
@@ -347,6 +365,14 @@ def apply_placement(self, sharding_placement=None):
         # clean it up by removing the added aliases from previous pass
         # as well as redundant views
         parallel_gm = joint_graph_passes(parallel_gm)
+        trace_structured(
+            "artifact",
+            metadata_fn=lambda: {
+                "name": "autoparallel_parallel_graph",
+                "encoding": "string",
+            },
+            payload_fn=lambda: str(parallel_gm.graph),
+        )
         # now rename input/param/tangent/output/grad_param/grad_input nodes following
         # our convention
         apply_node_renaming(
diff --git a/autoparallel/optimize_sharding.py b/autoparallel/optimize_sharding.py
index 60de41d8..aa054ad0 100644
--- a/autoparallel/optimize_sharding.py
+++ b/autoparallel/optimize_sharding.py
@@ -313,15 +313,16 @@ def penalize_inefficient_collectives(self):
                                 # penalize case P -> S(1) as there are additional compute cost
                                 self.ds[(s_i, counter, oi, ii)]["cost"] *= 4
 
-    def print_violated_constraints(self):
+    def get_violated_constraints_log(self):
         violated_constraints = [
             (k, c) for k, c in self.prob.constraints.items() if not c.valid()
         ]
-        print(f"Violated constraints: {[x[0] for x in violated_constraints]}")
+        log_str = f"Violated constraints: {[x[0] for x in violated_constraints]}"
         for cname, c in violated_constraints:
-            print(f"========= {cname} =============")
+            log_str += f"\n========= {cname} ============="
             for cc, v in c.items():
-                print(f"{cc}, coeff={v}, value={cc.value()}")
+                log_str += f"\n{cc}, coeff={v}, value={cc.value()}"
+        return log_str
 
     def print_old(self):
         ds = self.ds
@@ -335,9 +336,10 @@ def print_old(self):
         )
         total_cost = sum(ds[x]["cost"] for x in res)
         print(f"total_cost: {total_cost:.2f}")
-        self.print_violated_constraints()
+        print(self.get_violated_constraints_log())
+
+    def get_log(self, colored=False):
 
-    def print(self, colored=False):
         from torch.fx.graph import _color_fns, _identity
 
         opt = {}
@@ -375,10 +377,10 @@ def print(self, colored=False):
             code[l_id] += line
             l_id += 1
         code = "\n".join(code)
-        print(code)
         total_cost = sum(self.ds[x]["cost"] for x in self.res)
-        print(f"total_cost: {total_cost:.2f}")
-        self.print_violated_constraints()
+        code += f"\ntotal_cost: {total_cost:.2f}"
+        code += "\n" + self.get_violated_constraints_log()
+        return code
 
     def print_costs_for_node(self, node, arg=0, **kwargs):
         from tabulate import tabulate  # type: ignore