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+---
+title: How to guarantee allocated values for next reconciliation
+date: 2025-05-22
+author: >-
+  [Attila Mészáros](https://github.com/csviri)
+---
+
+We recently released v5.1 of Java Operator SDK (JOSDK). One of the highlights of this release is related to a topic of
+so-called
+[allocated values](https://github.com/kubernetes/community/blob/master/contributors/devel/sig-architecture/api-conventions.md#representing-allocated-values
+).
+
+To describe the problem, let's say that our controller needs to create a resource that has a generated identifier, i.e.
+a resource which identifier cannot be directely derived from the custom resource's desired state as specified in its
+`spec` field. In order to record the fact that the resource was successfully created, and to avoid attempting to
+recreate the resource again in subsequent reconciliations, it is typical for this type of controller to store the
+generated identifier in the custom resource's `status` field.
+
+The Java Operator SDK relies on the informers' cache to retrieve resources. These caches, however, are only guaranteed
+to be eventually consistent. It could happen, then, that, if some other event occurs, that would result in a new
+reconciliation, **before** the update that's been made to our resource status has the chance to be propagated first to
+the cluster and then back to the informer cache, that the resource in the informer cache does **not** contain the latest
+version as modified by the reconciler. This would result in a new reconciliation where the generated identifier would be
+missing from the resource status and, therefore, another attempt to create the resource by the reconciler, which is not
+what we'd like.
+
+Java Operator SDK now provides a utility class [
+`PrimaryUpdateAndCacheUtils`](https://github.com/operator-framework/java-operator-sdk/blob/main/operator-framework-core/src/main/java/io/javaoperatorsdk/operator/api/reconciler/PrimaryUpdateAndCacheUtils.java)
+to handle this particular use case. Using that overlay cache, your reconciler is guaranteed to see the most up-to-date
+version of the resource on the next reconciliation:
+
+```java
+
+@Override
+public UpdateControl<StatusPatchCacheCustomResource> reconcile(
+        StatusPatchCacheCustomResource resource,
+        Context<StatusPatchCacheCustomResource> context) {
+
+    // omitted code
+
+    var freshCopy = createFreshCopy(resource); // need fresh copy just because we use the SSA version of update
+    freshCopy
+            .getStatus()
+            .setValue(statusWithAllocatedValue());
+
+    // using the utility instead of update control to patch the resource status
+    var updated =
+            PrimaryUpdateAndCacheUtils.ssaPatchStatusAndCacheResource(resource, freshCopy, context);
+    return UpdateControl.noUpdate();
+}
+```
+
+How does `PrimaryUpdateAndCacheUtils` work?
+There are multiple ways to solve this problem, but ultimately, we only provide the solution described below. If you
+want to dig deep in alternatives, see
+this [PR](https://github.com/operator-framework/java-operator-sdk/pull/2800/files).
+
+The trick is to intercept the resource that the reconciler updated and cache that version in an additional cache on top
+of the informer's cache. Subsequently, if the reconciler needs to read the resource, the SDK will first check if it is
+in the overlay cache and read it from there if present, otherwise read it from the informer's cache. If the informer
+receives an event with a fresh resource, we always remove the resource from the overlay cache, since that is a more
+recent resource. But this **works only** if the reconciler updates the resource using **with optimistic locking**, which
+is handled for you by `PrimaryUpdateAndCacheUtils` provided you pass it a "fresh" (i.e. a version of the resource that
+only contains the fields you care about being updated) copy of the resource since Server-Side Apply will be used
+underneath. If the update fails on conflict, because the resource has already been updated on the cluster before we got
+the chance to get our update in, we simply wait and poll the informer cache until the new resource version from the
+server appears in the informer's cache,
+and then try to apply our updates to the resource again using the updated version from the server, again with optimistic
+locking.
+
+So why is optimistic locking required? We hinted at it above, but the gist of it, is that if another party updates the
+resource before we get a chance to, we wouldn't be able to properly handle the resulting situation correctly in all
+cases. The informer would receive that new event before our own update would get a chance to propagate. Without
+optimistic locking, there wouldn't be a fail-proof way to determine which update should prevail (i.e. which occurred
+first), in particular in the event of the informer losing the connection to the cluster or other edge cases (the joys of
+distributed computing!).
+
+Optimistic locking simplifies the situation and provides us with stronger guarantees: if the update succeeds, then we
+can be sure we have the proper resource version in our caches. The next event will contain our update in all cases.
+Because we know that, we can also be sure that we can evict the cached resource in the overlay cache whenever we receive
+a new event. The overlay cache is only used if the SDK detects that the original resource (i.e. the one before we
+applied our status update in the example above) is still in the informer's cache.
+
+The following diagram sums up the process:
+
+```mermaid
+flowchart TD
+    A["Update Resource with Lock"] --> B{"Successful?"}
+    B -- Fails on conflict --> D{"Resource updated from cluster?"}
+    D -- " No: poll until updated " --> D
+    D -- Yes --> n4["Apply desired changes on the resource again"]
+    B -- Yes --> n2{"Original resource still in informer cache?"}
+    n2 -- Yes --> C["Cache the resource in overlay cache"]
+    n2 -- No --> n3["Informer cache already contains up-to-date version, do not use overlay cache"]
+    n4 --> A
+
+```