*   Added APIs for switching between interactive logging and absl logging.
        By default, Keras always writes the logs to stdout. However, this is not
        optimal in a non-interactive environment, where you don't have access to
        stdout, but can only view the logs. You can use
        `tf.keras.utils.disable_interactive_logging()` to write the logs to ABSL
        logging. You can also use `tf.keras.utils.enable_interactive_logging()`

	logger.LogIf(ctx, "tier", err, errKind...)
}

func kmsLogIf(ctx context.Context, err error, errKind ...any) {
	logger.LogIf(ctx, "kms", err, errKind...)
}

// KMSLogger permits access to kms module specific logging
type KMSLogger struct{}

// LogOnceIf is the implementation of LogOnceIf, accessible using the Logger interface
func (l KMSLogger) LogOnceIf(ctx context.Context, err error, id string, errKind ...any) {

  "durations" : [ {
    "testProject" : "excludeRuleMergingBuild",
    "linux" : 232
  } ]
}, {
  "scenario" : "org.gradle.performance.regression.corefeature.LargeDependencyGraphPerformanceTest.resolve large dependency graph (parallel = false, locking = true)",
  "durations" : [ {
    "testProject" : "excludeRuleMergingBuild",

## 🔧 Configuration

### Logging Configuration
CoreLib supports multiple logging frameworks. Configure your preferred logger:

```java
// Use with SLF4J (add slf4j-api dependency)
Logger logger = Logger.getLogger(MyClass.class);

// Use with Commons Logging (add commons-logging dependency)  
Logger logger = Logger.getLogger(MyClass.class);

// Use with Java Util Logging (built-in)

/**
 * Security audit logger for SMB operations.
 * Provides structured logging of security-relevant events with sensitive data masking.
 *
 * Features:
 * - Structured JSON logging
 * - Sensitive data masking
 * - Event categorization
 * - Performance metrics
 * - Compliance-ready audit trail
 * - Asynchronous logging with bounded queue
 * - Object pooling to reduce GC pressure
 */
public class SecurityAuditLogger {

   * segments, each governed by its own write lock. The segment lock is taken once for each explicit
   * write, and twice for each cache loading computation (once prior to loading the new value, and
   * once after loading completes). Much internal cache management is performed at the segment
   * granularity. For example, access queues and write queues are kept per segment when they are

platforms/core-configuration/kotlin-dsl-plugins/            @gradle/bt-tide
platforms/core-configuration/kotlin-dsl-provider-plugins/   @gradle/bt-tide
platforms/core-configuration/kotlin-dsl-tooling-builders/   @gradle/bt-tide
platforms/core-configuration/kotlin-dsl-tooling-models/     @gradle/bt-tide

# Core automation platform (Declarative DSL)
platforms/core-configuration/declarative-dsl-api/                   @gradle/bt-declarative-gradle-project

import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Locale;
import java.util.Map;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.codelibs.core.lang.StringUtil;
import org.codelibs.core.misc.Tuple3;
import org.codelibs.fess.Constants;
import org.codelibs.fess.entity.SearchRequestParams.SearchRequestType;

import java.util.Map;
import java.util.Queue;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ConcurrentLinkedQueue;
import java.util.stream.Collectors;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.codelibs.core.lang.StringUtil;
import org.codelibs.fess.crawler.Constants;
import org.codelibs.fess.crawler.entity.AccessResult;

    }
    try {
      return fromEntryArrayCheckingBucketOverflow(n, entryArray, throwIfDuplicateKeys);
    } catch (BucketOverflowException e) {
      // probable hash flooding attack, fall back to j.u.HM based implementation and use its
      // implementation of hash flooding protection
      return JdkBackedImmutableMap.create(n, entryArray, throwIfDuplicateKeys);
    }
  }