diff --git a/build/ci/jenkins/Nightly.groovy b/build/ci/jenkins/Nightly.groovy
index c6fb8f2766..a1f4d9a1eb 100644
--- a/build/ci/jenkins/Nightly.groovy
+++ b/build/ci/jenkins/Nightly.groovy
@@ -144,6 +144,7 @@ pipeline {
                                                     --set dataNode.replicas=2 \
                                                     --set dataCoordinator.gc.missingTolerance=86400 \
                                                     --set dataCoordinator.gc.dropTolerance=86400 \
+                                                    --set indexCoordinator.gc.interval=1 \
                                                     --version ${chart_version} \
                                                     -f values/${mqMode}.yaml \
                                                     -f values/nightly.yaml "
diff --git a/tests/python_client/testcases/test_index.py b/tests/python_client/testcases/test_index.py
index f1a4347baf..46cc5a4023 100644
--- a/tests/python_client/testcases/test_index.py
+++ b/tests/python_client/testcases/test_index.py
@@ -978,6 +978,26 @@ class TestNewIndexBase(TestcaseBase):
         collection_w.drop_index(index_name=default_field_name, check_task=CheckTasks.err_res,
                                 check_items={ct.err_code: 0, ct.err_msg: "Index doesn\'t exist."})
 
+    @pytest.mark.tags(CaseLabel.L1)
+    def test_index_collection_with_after_load(self):
+        """
+        target: Test that index files are not lost after loading
+        method: create collection and add entities in it, create index, flush and load
+        expected: load and search successfully
+        """
+        collection_w = self.init_collection_wrap(cf.gen_unique_str(prefix))
+        nums = 20
+        tmp_nb = 5000 
+        for i in range (nums) :
+            df = cf.gen_default_dataframe_data(nb=tmp_nb, start=i * tmp_nb)
+            insert_res, _  = collection_w.insert(df)
+            assert collection_w.num_entities ==(i+1) * tmp_nb
+        collection_w.create_index(ct.default_float_vec_field_name, default_index_params)
+        collection_w.load()
+        vectors = [[random.random() for _ in range(default_dim)] for _ in range(default_nq)]
+        search_res, _ = collection_w.search(vectors, default_search_field, default_search_params, default_limit)
+        assert len(search_res[0]) == ct.default_limit
+            
 
 class TestNewIndexBinary(TestcaseBase):