}

    /**
     * Set the key rotation bytes limit
     *
     * @param limit number of bytes to encrypt before rotating keys
     */
    public void setKeyRotationBytesLimit(long limit) {
        this.keyRotationBytesLimit = limit;
    }

    /**
     * Set the key rotation time limit
     *
     * @param limit time in milliseconds before rotating keys
     */

		return 0
	}
	if limit >= 100*humanize.TiByte {
		// No limit set, or unreasonably high. Ignore
		return 0
	}
	return limit
}

func availableMemory() (available uint64) {
	available = 2048 * blockSizeV2 * 2 // Default to 4 GiB when we can't find the limits.

	if runtime.GOOS == "linux" {
		// Honor cgroup limits if set.
		limit := cgroupMemLimit()
		if limit > 0 {

        // Make many attempts to trigger global rate limit
        for (int i = 1; i <= 20; i++) {
            assertTrue(rateLimiter.checkAttempt("user" + i, "192.168.1." + i), "Attempt " + i + " should be allowed");
        }

        // 21st attempt should be blocked by global rate limit
        assertFalse(rateLimiter.checkAttempt("user21", "192.168.1.21"), "Should block after global rate limit");
    }

    @Test

                return false;
            }

            // Check if we've exceeded time limits
            long totalElapsed = System.currentTimeMillis() - exception.getOperationStartTime();
            if (totalElapsed > maxDelayMs * maxAttempts) {
                log.debug("Retry time limit exceeded for operation");
                return false;
            }

            return true;
        }

issues with Docker 1.9.1 can be found below.
  * CPU hardcapping will be enabled by default for containers with CPU limit set,
if supported by the kernel. You should either adjust your CPU limit, or set CPU
request only, if you want to avoid hardcapping. If the kernel does not support
CPU Quota, NodeStatus will contain a warning indicating that CPU Limits cannot
be enforced.

 * handles timeout scenarios, and ensures proper cleanup of resources.</p>
 *
 * <p>Key features:</p>
 * <ul>
 *   <li>Concurrent crawler process management with configurable limits</li>
 *   <li>Selective crawling based on configuration IDs</li>
 *   <li>Document expiration handling</li>
 *   <li>Hot thread monitoring for performance analysis</li>
 *   <li>Process isolation with separate JVM</li>

 * This callback processes file events (create, modify, delete) and manages document indexing and deletion
 * operations in the search engine. It supports recursive crawling with configurable depth and access count limits.
 *
 * <p>The implementation uses an executor service for concurrent processing of file operations and maintains
 * a cache of URLs to be deleted for batch processing. It handles redirect following and child URL discovery

         *
         * Ideally we'd have a real eviction policy, but until we see a problem in practice, I hope
         * that this will suffice. I have not even benchmarked with different size limits.
         */
        if (validClasses.size() > 1000) {
          validClasses.clear();
        }

        validClasses.add(new WeakReference<Class<? extends Exception>>(exceptionClass));
      }
    }

        }

        // Reasonable upper limit (1TB)
        long maxSize = 1099511627776L;
        if (size > maxSize) {
            failedValidations.incrementAndGet();
            log.warn("File size exceeds reasonable limit: {} > {}", size, maxSize);
            throw new SmbException("File size exceeds limit: " + size);
        }
    }

    /**

/**
 * A one-shot stream from the origin server to the client application with the raw bytes of the
 * response body. Each response body is supported by an active connection to the webserver. This
 * imposes both obligations and limits on the client application.
 *
 * ### The response body must be closed.
 *
 * Each response body is backed by a limited resource like a socket (live network responses) or