diff --git a/core/src/main/java/google/registry/beam/billing/ExpandRecurringBillingEventsPipeline.java b/core/src/main/java/google/registry/beam/billing/ExpandRecurringBillingEventsPipeline.java
index 7066583d2..8a4fabfea 100644
--- a/core/src/main/java/google/registry/beam/billing/ExpandRecurringBillingEventsPipeline.java
+++ b/core/src/main/java/google/registry/beam/billing/ExpandRecurringBillingEventsPipeline.java
@@ -138,9 +138,15 @@ public class ExpandRecurringBillingEventsPipeline implements Serializable {
   private final boolean isDryRun;
   private final boolean advanceCursor;
   private final Counter recurringsInScopeCounter =
-      Metrics.counter("ExpandBilling", "RecurringsInScope");
-  private final Counter expandedOneTimeCounter =
-      Metrics.counter("ExpandBilling", "ExpandedOneTime");
+      Metrics.counter("ExpandBilling", "Recurrings in scope for expansion");
+  // Note that this counter is only accurate when running in dry run mode. Because SQL persistence
+  // is a side effect and not idempotent, a transaction to save OneTimes could be successful but the
+  // transform that contains it could be still be retried, rolling back the counter increment. The
+  // same transform, when retried, would skip the already expanded OneTime, causing this counter to
+  // be lower than it should be when not in dry run mode.
+  // See: https://beam.apache.org/documentation/programming-guide/#user-code-idempotence
+  private final Counter oneTimesToExpandCounter =
+      Metrics.counter("ExpandBilling", "OneTimes that would be expanded");
 
   ExpandRecurringBillingEventsPipeline(
       ExpandRecurringBillingEventsPipelineOptions options, Clock clock) {
@@ -195,6 +201,7 @@ public class ExpandRecurringBillingEventsPipeline implements Serializable {
                     endTime.minusYears(1)),
                 true,
                 (BigInteger id) -> {
+                  recurringsInScopeCounter.inc();
                   // Note that because all elements are mapped to the same dummy key, the next
                   // batching transform will effectively be serial. This however does not matter for
                   // our use case because the elements were obtained from a SQL read query, which
@@ -271,13 +278,9 @@ public class ExpandRecurringBillingEventsPipeline implements Serializable {
     } catch (IllegalArgumentException e) {
       return;
     }
-
-    recurringsInScopeCounter.inc();
     Domain domain = tm().loadByKey(Domain.createVKey(recurring.getDomainRepoId()));
     Registry tld = Registry.get(domain.getTld());
 
-
-
     // Find the times for which the OneTime billing event are already created, making this expansion
     // idempotent. There is no need to match to the domain repo ID as the cancellation matching
     // billing event itself can only be for a single domain.
@@ -301,7 +304,7 @@ public class ExpandRecurringBillingEventsPipeline implements Serializable {
     // Create new OneTime and DomainHistory for EventTimes that needs to be expanded.
     for (DateTime eventTime : eventTimesToExpand) {
       recurrenceLastExpansionTime = latestOf(recurrenceLastExpansionTime, eventTime);
-      expandedOneTimeCounter.inc();
+      oneTimesToExpandCounter.inc();
       DateTime billingTime = eventTime.plus(tld.getAutoRenewGracePeriodLength());
       // Note that the DomainHistory is created as of transaction time, as opposed to event time.
       // This might be counterintuitive because other DomainHistories are created at the time
diff --git a/core/src/main/java/google/registry/config/files/default-config.yaml b/core/src/main/java/google/registry/config/files/default-config.yaml
index ae41e6e5c..cb6951fa1 100644
--- a/core/src/main/java/google/registry/config/files/default-config.yaml
+++ b/core/src/main/java/google/registry/config/files/default-config.yaml
@@ -427,7 +427,7 @@ misc:
 
 beam:
   # The default region to run Apache Beam (Cloud Dataflow) jobs in.
-  defaultJobRegion: us-east1
+  defaultJobRegion: us-central1
   # The GCE machine type to use when a job is CPU-intensive (e. g. RDE). Be sure
   # to check the VM CPU quota for the job region. In a massively parallel
   # pipeline this quota can be easily reached and needs to be raised, otherwise
diff --git a/core/src/main/resources/google/registry/beam/expand_recurring_billing_events_pipeline_metadata.json b/core/src/main/resources/google/registry/beam/expand_recurring_billing_events_pipeline_metadata.json
index 7519abd3b..d34e4acb0 100644
--- a/core/src/main/resources/google/registry/beam/expand_recurring_billing_events_pipeline_metadata.json
+++ b/core/src/main/resources/google/registry/beam/expand_recurring_billing_events_pipeline_metadata.json
@@ -23,12 +23,6 @@
       "helpText": "The exclusive upper bound of the operation window, in ISO 8601 format.",
       "is_optional": false
     },
-    {
-      "name": "shard",
-      "label": "The exclusive upper bound of the operation window.",
-      "helpText": "The exclusive upper bound of the operation window, in ISO 8601 format.",
-      "is_optional": true
-    },
     {
       "name": "isDryRun",
       "label": "Whether this job is a dry run.",