Monitoring the performance and latency of Java 11 HTTP requests is essential when utilizing the java.net.http
package introduced with the new Java 11 HttpClient
API. It helps identify bottlenecks, optimize network calls, and ensure efficient resource usage for your application.
Here’s how you can do it:
1. Measure Latency Using Timestamps
You can manually measure the time taken to send and receive HTTP requests by recording timestamps before and after executing the HTTP call.
package org.kodejava.net.http;
import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.time.Duration;
import java.time.Instant;
public class HttpPerformanceMonitor {
public static void main(String[] args) throws Exception {
HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
.uri(new URI("https://example.com"))
.GET()
.build();
// Record start time
Instant start = Instant.now();
// Send request and get response
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
// Record end time
Instant end = Instant.now();
// Calculate latency
Duration latency = Duration.between(start, end);
System.out.println("Response time: " + latency.toMillis() + " ms");
System.out.println("Response status code: " + response.statusCode());
}
}
This approach calculates the time taken for the entire HTTP operation, including connection establishment, sending the request, and receiving the response.
2. Use a Custom Executor to Monitor Thread Usage
HttpClient allows you to set a custom Executor
for handling its asynchronous operations. You can measure how efficiently the threads are being utilized.
package org.kodejava.net.http;
import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.util.concurrent.Executors;
import java.util.concurrent.ExecutorService;
public class HttpClientWithCustomExecutor {
public static void main(String[] args) throws Exception {
ExecutorService executor = Executors.newFixedThreadPool(4); // Monitor thread usage
HttpClient client = HttpClient.newBuilder()
.executor(executor)
.build();
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://example.com"))
.GET()
.build();
long startTime = System.currentTimeMillis();
client.sendAsync(request, HttpResponse.BodyHandlers.ofString())
.thenAccept(response -> {
long endTime = System.currentTimeMillis();
System.out.println("Response time: " + (endTime - startTime) + " ms");
System.out.println("Response status code: " + response.statusCode());
})
.join(); // Wait for the async call to complete
executor.shutdown();
}
}
By setting a custom Executor
, you can track thread pool utilization and capture latency.
3. Enable Logging for HTTP Headers and Debugging
Java 11 supports configuring logging for the HTTP Client. You can enable debug-level logging to capture low-level details:
- Add the following JVM options to enable
java.net.http.HttpClient
debugging:
-Djdk.httpclient.HttpClient.log=requests,headers,frames:all
This will output detailed log information, including HTTP request/response headers and frames.
4. Monitor HTTP Client Metrics Using Libraries
Libraries that support metrics collection (like Micrometer) can be integrated with Java 11 HttpClient
to collect throughput, response times, and errors.
Example: Using Micrometer You can create custom timers and counters to record metrics manually.
package org.kodejava.net.http;
import io.micrometer.core.instrument.MeterRegistry;
import io.micrometer.core.instrument.simple.SimpleMeterRegistry;
import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.time.Duration;
import java.time.Instant;
import java.util.concurrent.TimeUnit;
public class HttpClientWithMetrics {
public static void main(String[] args) throws Exception {
MeterRegistry registry = new SimpleMeterRegistry(); // Replace with a distributed registry like Prometheus
HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
.uri(new URI("https://example.com"))
.GET()
.build();
registry.timer("http.requests").record(() -> {
try {
Instant start = Instant.now();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
Instant end = Instant.now();
System.out.println("Response time: " + Duration.between(start, end).toMillis() + " ms");
System.out.println("Response status code: " + response.statusCode());
} catch (Exception e) {
e.printStackTrace();
}
});
registry.get("http.requests").timers().forEach(timer -> {
System.out.println("Timer count: " + timer.count());
System.out.println("Total time: " + timer.totalTime(TimeUnit.MILLISECONDS) + " ms");
});
}
}
5. Use Dependency Injection Frameworks
Combine the Java 11 HttpClient
with Spring Boot’s actuator (if you’re already using it). Actuator provides built-in metrics and HTTP tracing capabilities.
6. Profiling with External Tools
You can observe Java application performance (including HTTP requests) using APM tools, such as:
- Java Flight Recorder (JFR)
- Use JFR to monitor detailed HTTP request timings and underlying JVM performance.
- Java VisualVM
- Profile application threads and network usage.
- Third-Party APMs
- Tools like New Relic, AppDynamics, or Datadog can report on HTTP client usage.
Summary of Approaches
Approach | Tools/Techniques | Notes |
---|---|---|
Manual Timing | Instant + Duration |
Tracks latency at the request level. |
Custom Executors | ExecutorService |
Measures thread usage and async execution. |
Logging | JVM Debugging (HttpClient.log ) |
Debugs detailed network activity. |
Metrics Libraries | Micrometer (manual instrumentation) | Can feed metrics into observability tools. |
Framework Integration | Spring Boot Actuator | Collects trace and performance metrics. |
External Profiling/Monitoring | JFR, APM Tools, VisualVM | Monitors JVM, HTTP, and app performance. |
Choose the approach based on your application’s complexity and monitoring needs!
Maven Dependencies
<dependency>
<groupId>io.micrometer</groupId>
<artifactId>micrometer-core</artifactId>
<version>1.15.0</version>
</dependency>