diff --git a/python/ray/autoscaler/autoscaler.py b/python/ray/autoscaler/autoscaler.py
index 2e2f9593c892..b2f9a2adbb08 100644
--- a/python/ray/autoscaler/autoscaler.py
+++ b/python/ray/autoscaler/autoscaler.py
@@ -142,6 +142,7 @@ def prune_active_ips(self, active_ips):
         def prune(mapping):
             unwanted = set(mapping) - active_ips
             for unwanted_key in unwanted:
+                print("Removed mapping", unwanted_key, mapping[unwanted_key])
                 del mapping[unwanted_key]
             if unwanted:
                 print("Removed {} stale ip mappings: {} not in {}".format(
@@ -454,9 +455,8 @@ def launch_new_node(self, count):
                 TAG_RAY_NODE_STATUS: "Uninitialized",
                 TAG_RAY_LAUNCH_CONFIG: self.launch_hash,
             }, count)
-        # TODO(ekl) be less conservative in this check
-        assert len(self.workers()) > num_before, \
-            "Num nodes failed to increase after creating a new node"
+        if len(self.workers()) <= num_before:
+            print("Warning: Num nodes failed to increase after node creation")
 
     def workers(self):
         return self.provider.nodes(tag_filters={
diff --git a/python/ray/ray_constants.py b/python/ray/ray_constants.py
index 4f337ad41e60..7e5df96500e5 100644
--- a/python/ray/ray_constants.py
+++ b/python/ray/ray_constants.py
@@ -3,19 +3,30 @@
 from __future__ import print_function
 """Ray constants used in the Python code."""
 
+import os
+
+
+def env_integer(key, default):
+    if key in os.environ:
+        return int(os.environ(key))
+    return default
+
+
 # Abort autoscaling if more than this number of errors are encountered. This
 # is a safety feature to prevent e.g. runaway node launches.
-AUTOSCALER_MAX_NUM_FAILURES = 5
+AUTOSCALER_MAX_NUM_FAILURES = env_integer("AUTOSCALER_MAX_NUM_FAILURES", 5)
 
 # Max number of nodes to launch at a time.
-AUTOSCALER_MAX_CONCURRENT_LAUNCHES = 10
+AUTOSCALER_MAX_CONCURRENT_LAUNCHES = env_integer(
+    "AUTOSCALER_MAX_CONCURRENT_LAUNCHES", 10)
 
 # Interval at which to perform autoscaling updates.
-AUTOSCALER_UPDATE_INTERVAL_S = 5
+AUTOSCALER_UPDATE_INTERVAL_S = env_integer("AUTOSCALER_UPDATE_INTERVAL_S", 5)
 
 # The autoscaler will attempt to restart Ray on nodes it hasn't heard from
 # in more than this interval.
-AUTOSCALER_HEARTBEAT_TIMEOUT_S = 30
+AUTOSCALER_HEARTBEAT_TIMEOUT_S = env_integer("AUTOSCALER_HEARTBEAT_TIMEOUT_S",
+                                             30)
 
 # Max number of retries to AWS (default is 5, time increases exponentially)
-BOTO_MAX_RETRIES = 12
+BOTO_MAX_RETRIES = env_integer("BOTO_MAX_RETRIES", 12)
diff --git a/test/autoscaler_test.py b/test/autoscaler_test.py
index c3b84ca968f1..c56bd3ce55aa 100644
--- a/test/autoscaler_test.py
+++ b/test/autoscaler_test.py
@@ -365,14 +365,6 @@ def testMaxFailures(self):
         autoscaler.update()
         self.assertRaises(Exception, autoscaler.update)
 
-    def testAbortOnCreationFailures(self):
-        config_path = self.write_config(SMALL_CLUSTER)
-        self.provider = MockProvider()
-        self.provider.fail_creates = True
-        autoscaler = StandardAutoscaler(
-            config_path, LoadMetrics(), max_failures=0, update_interval_s=0)
-        self.assertRaises(AssertionError, autoscaler.update)
-
     def testLaunchNewNodeOnOutOfBandTerminate(self):
         config_path = self.write_config(SMALL_CLUSTER)
         self.provider = MockProvider()