diff --git a/amber/src/test/integration/org/apache/texera/amber/engine/e2e/ReconfigurationIntegrationSpec.scala b/amber/src/test/integration/org/apache/texera/amber/engine/e2e/ReconfigurationIntegrationSpec.scala
index 5d2ed7e5e4c..b4545a19b15 100644
--- a/amber/src/test/integration/org/apache/texera/amber/engine/e2e/ReconfigurationIntegrationSpec.scala
+++ b/amber/src/test/integration/org/apache/texera/amber/engine/e2e/ReconfigurationIntegrationSpec.scala
@@ -105,26 +105,31 @@ class ReconfigurationIntegrationSpec
   }
 
   /**
-    * Run a trivial pure-Scala workflow (TextInput → terminal) once before the
-    * timed tests start, so the first 5-second `startWorkflow` await in
-    * [[TestUtils.shouldReconfigure]] doesn't have to absorb JVM JIT
-    * warmup, pekko dispatcher first-touch, and `RegionExecutionCoordinator`
-    * class loading.
-    *
-    * Hard-capped at 10 seconds total, defensively wrapped: if warmup itself
-    * times out or throws, log and continue — the existing `Retries` mixin
-    * still backs up individual test cases. This ensures warmup can never
-    * hang the suite.
+    * Runs a TextInput -> Python UDF workflow once before the timed tests so
+    * Python worker cold-start is paid here, not inside a timed test. Capped and
+    * wrapped so warmup can never fail or hang the suite.
     */
   private def warmupOnce(): Unit = {
-    val warmupCap = Duration.fromSeconds(10)
+    val warmupCap = Duration.fromSeconds(60)
     setUpWorkflowExecutionData(specId)
     var client: AmberClient = null
     try {
       val src = new TextInputSourceOpDesc()
       src.textInput = "warmup"
+      val udf = TestOperators.pythonOpDesc()
       val warmupCtx = TestUtils.workflowContext(specId)
-      val workflow = buildWorkflow(List(src), List.empty, warmupCtx)
+      val workflow = buildWorkflow(
+        List(src, udf),
+        List(
+          LogicalLink(
+            src.operatorIdentifier,
+            PortIdentity(),
+            udf.operatorIdentifier,
+            PortIdentity()
+          )
+        ),
+        warmupCtx
+      )
       client = new AmberClient(
         system,
         workflow.context,
@@ -166,8 +171,13 @@ class ReconfigurationIntegrationSpec
   ): Map[OperatorIdentity, List[Tuple]] =
     TestUtils.shouldReconfigure(system, ctx, operators, links, targetOps, newOpExecInitInfo)
 
+  // Small source that emits slowly (30 rows, 0.25s apart) so a pause lands
+  // mid-run and the workflow still completes quickly after resume.
+  private def slowSource() =
+    TestOperators.slowRegionSourceOpDesc(numTuple = 30, delaySeconds = 0.25)
+
   "Engine" should "be able to modify a python UDF worker in workflow" in {
-    val sourceOpDesc = TestOperators.smallCsvScanOpDesc()
+    val sourceOpDesc = slowSource()
     val udfOpDesc = TestOperators.pythonOpDesc()
     val code = """
                  |from pytexera import *
@@ -198,7 +208,7 @@ class ReconfigurationIntegrationSpec
   }
 
   "Engine" should "propagate reconfiguration through a source operator in workflow" in {
-    val sourceOpDesc = TestOperators.pythonSourceOpDesc(10000)
+    val sourceOpDesc = slowSource()
     val udfOpDesc = TestOperators.pythonOpDesc()
     val code = """
                  |from pytexera import *
@@ -206,7 +216,7 @@ class ReconfigurationIntegrationSpec
                  |class ProcessTupleOperator(UDFOperatorV2):
                  |    @overrides
                  |    def process_tuple(self, tuple_: Tuple, port: int) -> Iterator[Optional[TupleLike]]:
-                 |        tuple_['field_1'] = tuple_['field_1'] + '_reconfigured'
+                 |        tuple_['Region'] = tuple_['Region'] + '_reconfigured'
                  |        yield tuple_
                  |""".stripMargin
     val result = shouldReconfigure(
@@ -223,12 +233,12 @@ class ReconfigurationIntegrationSpec
       OpExecWithCode(code, "python")
     )
     assert(result(udfOpDesc.operatorIdentifier).exists { t =>
-      t.getField("field_1").asInstanceOf[String].contains("_reconfigured")
+      t.getField("Region").asInstanceOf[String].contains("_reconfigured")
     })
   }
 
   "Engine" should "be able to modify two python UDFs in workflow" in {
-    val sourceOpDesc = TestOperators.smallCsvScanOpDesc()
+    val sourceOpDesc = slowSource()
     val udfOpDesc1 = TestOperators.pythonOpDesc()
     val udfOpDesc2 = TestOperators.pythonOpDesc()
     val code = """
diff --git a/amber/src/test/scala/org/apache/texera/amber/engine/e2e/TestUtils.scala b/amber/src/test/scala/org/apache/texera/amber/engine/e2e/TestUtils.scala
index ac71483a5d3..d001c4471c1 100644
--- a/amber/src/test/scala/org/apache/texera/amber/engine/e2e/TestUtils.scala
+++ b/amber/src/test/scala/org/apache/texera/amber/engine/e2e/TestUtils.scala
@@ -301,6 +301,8 @@ object TestUtils {
       ControllerConfig.default,
       error => {}
     )
+    // Timeout for control-command acks (start/pause/reconfigure/resume).
+    val commandTimeout = Duration.fromSeconds(30)
     val completion = Promise[Unit]()
     var result: Map[OperatorIdentity, List[Tuple]] = null
     client.registerCallback[ExecutionStateUpdate](evt => {
@@ -311,14 +313,14 @@ object TestUtils {
     })
     Await.result(
       client.controllerInterface.startWorkflow(EmptyRequest(), ()),
-      Duration.fromSeconds(5)
+      commandTimeout
     )
     val pausedReached = stateReached(client, PAUSED)
     Await.result(
       client.controllerInterface.pauseWorkflow(EmptyRequest(), ()),
-      Duration.fromSeconds(5)
+      commandTimeout
     )
-    Await.result(pausedReached, Duration.fromSeconds(10))
+    Await.result(pausedReached, commandTimeout)
     val physicalOps = targetOps.flatMap(op =>
       workflow.physicalPlan.getPhysicalOpsOfLogicalOp(op.operatorIdentifier)
     )
@@ -330,11 +332,11 @@ object TestUtils {
         ),
         ()
       ),
-      Duration.fromSeconds(5)
+      commandTimeout
     )
     Await.result(
       client.controllerInterface.resumeWorkflow(EmptyRequest(), ()),
-      Duration.fromSeconds(5)
+      commandTimeout
     )
     Await.result(completion, Duration.fromMinutes(1))
     result
diff --git a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/TestOperators.scala b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/TestOperators.scala
index b3c38735957..69783b5e1fb 100644
--- a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/TestOperators.scala
+++ b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/TestOperators.scala
@@ -181,4 +181,24 @@ object TestOperators {
     udf
   }
 
+  // Emits `numTuple` rows with a "Region" column, sleeping `delaySeconds`
+  // between rows.
+  def slowRegionSourceOpDesc(numTuple: Int, delaySeconds: Double): PythonUDFSourceOpDescV2 = {
+    val udf = new PythonUDFSourceOpDescV2()
+    udf.workers = 1
+    udf.columns = List(new Attribute("Region", AttributeType.STRING))
+    udf.code = s"""
+                 |from pytexera import *
+                 |import time
+                 |
+                 |class UDFSourceOperator(UDFSourceOperator):
+                 |    @overrides
+                 |    def produce(self) -> Iterator[Union[TupleLike, TableLike, None]]:
+                 |        for i in range($numTuple):
+                 |            time.sleep($delaySeconds)
+                 |            yield {'Region': 'Asia'}
+                 |""".stripMargin
+    udf
+  }
+
 }