SIG Scheduling development efforts have been primarily focused on improving performance and reliability of the scheduler.
- Performance of the inter-pod affinity/anti-affinity feature is improved over 100X via algorithmic optimization.
- DaemonSet pods, which used to be scheduled by the DaemonSet controller, will be scheduled by the default scheduler in 1.12. This change allows DaemonSet pods to enjoy all the scheduling features of the default scheduler.

    return getBooleanProperty(DIRECTORY_NOTIFICATIONS_ENABLED, true);
}

public int getMaxDirectoryCacheEntries() {
    return getIntProperty(MAX_DIRECTORY_CACHE_ENTRIES, 1000);
}
```

## 7. Performance Optimizations

### 7.1 Batch Directory Operations
```java
public class BatchDirectoryOperations {
    private final DirectoryLeaseManager leaseManager;
    
    public List<SmbFile> batchExists(List<String> paths) {

import static org.mockito.Mockito.mock;
import static org.mockito.Mockito.when;

/**
 * Unit tests for the {@link InferenceStrategy} class.
 * Tests Maven 4.1.0+ inference optimizations including dependency and parent inference.
 */
@DisplayName("InferenceStrategy")
class InferenceStrategyTest {

    private InferenceStrategy strategy;

    @BeforeEach
    void setUp() {

### Bug or Regression

- cloud.google.com/go/networkconnectivity: v1.11.0
- cloud.google.com/go/networkmanagement: v1.6.0
- cloud.google.com/go/networksecurity: v0.8.0
- cloud.google.com/go/notebooks: v1.8.0
- cloud.google.com/go/optimization: v1.3.1
- cloud.google.com/go/orchestration: v1.6.0
- cloud.google.com/go/orgpolicy: v1.10.0
- cloud.google.com/go/osconfig: v1.11.0
- cloud.google.com/go/oslogin: v1.9.0

Anyway, in any of the cases above, FastAPI will still work asynchronously and be extremely fast.

But by following the steps above, it will be able to do some performance optimizations.

## Technical Details { #technical-details }

Modern versions of Python have support for **"asynchronous code"** using something called **"coroutines"**, with **`async` and `await`** syntax.

Au final, peu importe le cas parmi ceux ci-dessus, **FastAPI** fonctionnera de manière asynchrone et sera extrêmement rapide.

Mais si vous suivez bien les instructions ci-dessus, alors **FastAPI** pourra effectuer quelques optimisations et ainsi améliorer les performances.

## Détails techniques

Les versions modernes de Python supportent le **code asynchrone** grâce aux **"coroutines"** avec les syntaxes **`async` et `await`**.

// --------------------------------------------------------------------------
TF_SessionOptions* TF_NewSessionOptions() {
  TF_SessionOptions* out = new TF_SessionOptions;
  // Disable optimizations for static graph to allow calls to Session::Extend.
  out->options.config.mutable_experimental()
      ->set_disable_optimize_for_static_graph(true);
  return out;
}

common:linux --experimental_guard_against_concurrent_changes

# Configure short or long logs
common:short_logs --output_filter=DONT_MATCH_ANYTHING
common:verbose_logs --output_filter=

# Instruction set optimizations
# TODO(gunan): Create a feature in toolchains for avx/avx2 to
#   avoid having to define linux/win separately.
common:avx_linux --copt=-mavx
common:avx_linux --host_copt=-mavx
common:avx_linux --copt="-mf16c"

     * system defaults will be used.
     *
     * Most applications should not call this method, and instead use the system defaults. Those
     * classes include special optimizations that can be lost if the implementations are decorated.
     *
     * If necessary, you can create and configure the defaults yourself with the following code:
     *
     * ```java