Spring RestClient Connection Leak With Invalid Status

by Henrik Larsen 54 views

Hey everyone! Let's dive into a tricky issue I've been wrestling with in my Spring Boot application. It involves the RestClient, connection management, and some unexpected behavior when dealing with invalid HTTP responses. I'm excited to share my findings and hopefully get some insights from you guys.

The Problem: RestClient Connection Leak

So, here's the deal. I've got this scenario where my Spring Boot app (using Spring Boot 3.5.4 and OpenJDK 22) needs to make HTTP calls to two different servers, let's call them Server A and Server B. Both expose a POST /readyz endpoint, which my application uses for health checks. I'm leveraging the RestClient along with the JDK's HttpClient and JdkClientHttpRequestFactory for these calls. I've set up a simple thread that pings these servers every 10 seconds.

Here’s the snippet of the code that sets up the RestClient:

public static RestClient client(String url) {
    HttpClient.Builder httpBuilder = HttpClient.newBuilder()
            .connectTimeout(Duration.ofSeconds(3))
            .version(HttpClient.Version.HTTP_1_1);

    JdkClientHttpRequestFactory factory = new JdkClientHttpRequestFactory(httpBuilder.build());
    factory.setReadTimeout(Duration.ofSeconds(3));
    return RestClient.builder()
            .baseUrl(url)
            .defaultHeader(HttpHeaders.CONNECTION, "closed")
            .defaultHeader(HttpHeaders.CONTENT_TYPE, "application/json; charset=utf-8")
            .requestFactory(factory)
            .build();
}

public static void main(String[] args) throws InterruptedException {
    String url = "server.url";
    RestClient client = client(url);

    final ScheduledExecutorService executor = Executors.newSingleThreadScheduledExecutor(r -> {
        Thread thread = new Thread(r, "node-health-issuer");
        thread.setDaemon(true);
        return thread;
    });

    executor.scheduleWithFixedDelay(() -> {
        try {
            ResponseEntity<Void> responseEntity = client.post().uri("readyz")
                    .retrieve()
                    .toBodilessEntity();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }, 0, 10, TimeUnit.SECONDS);

    Thread.sleep(60 * 1000);
}

Now, here's where things get interesting. Server A behaves perfectly, responding as expected. However, Server B, due to some version differences in its implementation, returns a slightly malformed HTTP status line: 200 OK (notice the leading space). This seemingly minor deviation triggers a java.net.ProtocolException: Invalid status line.

The crucial observation is this: while Server A maintains a single established connection as verified by netstat -an | grep <Aport>, Server B starts accumulating connections. Each error leads to a new, unclosed connection, eventually exhausting resources. This connection leak is a major concern for the application's stability and performance. Let's break down why this is happening and what the implications are.

Root Cause Analysis

Delving deeper into the exception stack trace reveals that the issue stems from the org.springframework.web.client.DefaultRestClient$DefaultRequestBodyUriSpec.exchangeInternal(DefaultRestClient.java:582) method. Within this method, there's a finally block intended to close the connection. However, the debugging shows that while the close flag is indeed set to true, the clientResponse object is null when the exception occurs with server B. This scenario prevents the connection from being properly closed, leading to the leak.

To further clarify, the malformed HTTP status line from Server B ( 200 OK) violates the HTTP/1.1 specification, which requires a specific format for the status line. The JDK's HttpClient, being strict about protocol compliance, throws a ProtocolException when it encounters this invalid format. This exception disrupts the normal flow of the RestClient, preventing it from executing the connection closure logic.

Why Connection Leaks Matter

Connection leaks are a silent killer for applications. They don't always manifest as immediate crashes, but they gradually degrade performance and stability. Here's why you should care about connection leaks:

  • Resource Exhaustion: Each open connection consumes system resources, such as file descriptors and memory. Over time, a connection leak can exhaust these resources, leading to application slowdowns and, eventually, crashes.
  • Performance Degradation: As the number of open connections increases, the server's ability to handle new requests diminishes. This results in slower response times and a poor user experience.
  • Unpredictable Behavior: Connection leaks can be difficult to diagnose because their effects are often delayed and intermittent. This makes troubleshooting challenging and time-consuming.
  • System Instability: In severe cases, a connection leak can destabilize the entire system, affecting other applications and services running on the same machine.

Therefore, addressing connection leaks is crucial for building robust and reliable applications. In our case, the RestClient's failure to close connections when encountering invalid HTTP status lines poses a significant threat to the long-term health of the application.

The Exception: Invalid Status Line

Let's take a closer look at the exception that triggers this whole mess. The java.net.ProtocolException: Invalid status line: " 200 OK" is our primary suspect. This exception is thrown by the JDK's HttpClient when it encounters an HTTP status line that doesn't conform to the HTTP/1.1 specification. In this case, the leading space in the status line is the culprit. While it might seem like a trivial formatting issue, it's enough to derail the connection management logic within the RestClient.

The stack trace provides valuable clues about the exception's origin:

org.springframework.web.client.ResourceAccessException: I/O error on POST request for "http://192.1.1.1:11111/readyz": Invalid status line: " 200 OK"
        at org.springframework.web.client.DefaultRestClient$DefaultRequestBodyUriSpec.createResourceAccessException(DefaultRestClient.java:697)
        at org.springframework.web.client.DefaultRestClient$DefaultRequestBodyUriSpec.exchangeInternal(DefaultRestClient.java:582)
        ...
Caused by: java.net.ProtocolException: Invalid status line: " 200 OK"
        at java.net.http/jdk.internal.net.http.Http1HeaderParser.protocolException(Unknown Source)
        at java.net.http/jdk.internal.net.http.Http1HeaderParser.readStatusLineFeed(Unknown Source)
        ...

As you can see, the ProtocolException is caught and wrapped in a ResourceAccessException by the RestClient. This is a standard practice for handling exceptions during HTTP communication. However, the key point is that this exception disrupts the normal execution flow, preventing the finally block in exchangeInternal from properly closing the connection.

Diving into the Stack Trace

The stack trace provides a roadmap of how the exception propagates through the system. Let's break it down:

  1. The ProtocolException originates from the jdk.internal.net.http package, specifically within the Http1HeaderParser class. This indicates that the JDK's HTTP/1.1 parser is the first to detect the malformed status line.
  2. The exception bubbles up through the internal classes of the java.net.http module, eventually reaching the Http1Response$HeadersReader.
  3. The RestClient's exchangeInternal method catches this exception and wraps it in a ResourceAccessException. This wrapping is important because it provides a more Spring-specific exception type for handling HTTP communication errors.
  4. The exception then propagates up the call stack, eventually reaching the executor.scheduleWithFixedDelay block in the main method. This is where the exception is caught and printed to the console.

The crucial part of the stack trace is the exchangeInternal method in DefaultRestClient. This method is responsible for executing the HTTP request and handling the response. The finally block within this method is intended to ensure that the connection is closed, regardless of whether the request was successful or not. However, in the case of the ProtocolException, the clientResponse is null, preventing the connection from being closed.

The Role of the finally Block

The finally block in the exchangeInternal method is a critical piece of the puzzle. It's designed to guarantee that resources are released, even if an exception occurs. Here's the relevant snippet of code (for illustrative purposes, as the exact implementation might vary slightly across Spring Boot versions):

try {
    // Execute the HTTP request and process the response
} catch (Exception ex) {
    // Handle exceptions
} finally {
    if (close) {
        // Close the connection
        if (clientResponse != null) {
            clientResponse.close();
        } else {
            // Connection closure logic if clientResponse is null
        }
    }
}

The problem arises because the clientResponse is null when the ProtocolException is thrown. This prevents the clientResponse.close() method from being called, which is responsible for releasing the connection back to the pool (or closing it if connection pooling is not enabled). The else block, which should handle the case where clientResponse is null, might not be present or might not contain the necessary logic to properly close the connection in this specific scenario.

This highlights a potential gap in the RestClient's error handling. While it correctly catches and wraps the ProtocolException, it doesn't adequately address the connection closure when the exception occurs during the initial response parsing phase, before a clientResponse object is created. This is the core reason behind the connection leak we're observing.

Connection Accumulation: A Ticking Time Bomb

The most concerning symptom of this issue is the accumulation of connections. As the application runs, each failed attempt to communicate with Server B results in a new, unclosed connection. This relentless accumulation acts like a ticking time bomb, gradually depleting system resources and threatening the application's stability.

Using the netstat -an | grep <Bport> command, I observed a steady increase in the number of established connections to Server B. This confirms that the connections are not being properly closed and are accumulating over time. The following output illustrates this phenomenon:

tcp6    0   0 <local-address1>   <B-address>     ESTABLISHED
tcp6    0   0 <local-address2>   <B-address>     ESTABLISHED
tcp6    0   0 <local-address3>   <B-address>     ESTABLISHED
tcp6    0   0 <local-address4>   <B-address>     ESTABLISHED
...

Each line represents an open TCP connection between the application and Server B. The ESTABLISHED status indicates that these connections are active but idle, consuming resources without performing any useful work. The continuous increase in these connections signals a serious problem that needs immediate attention.

The Impact of Unclosed Connections

The consequences of unclosed connections can be severe. Here's a breakdown of the potential impacts:

  • File Descriptor Exhaustion: Each open TCP connection consumes a file descriptor, a limited system resource. If the application creates connections faster than it closes them, it can eventually exhaust the available file descriptors. This will lead to a java.io.IOException: Too many open files error and prevent the application from establishing new connections.
  • Memory Consumption: Each connection consumes memory for buffers and other data structures. A large number of open connections can put a strain on the system's memory, leading to performance degradation and potential out-of-memory errors.
  • Performance Degradation: Maintaining a large number of open connections consumes CPU resources and network bandwidth. This can slow down the application's overall performance and increase latency for other requests.
  • Server Overload: The accumulation of connections can also overload the server that the application is connecting to. This can lead to performance issues on the server side and potentially cause it to become unresponsive.
  • Application Instability: In the worst-case scenario, the accumulation of connections can lead to application crashes and system instability. This can disrupt critical services and impact the user experience.

Therefore, it's crucial to address connection leaks proactively to prevent these issues from occurring. In our case, the RestClient's failure to close connections when encountering invalid HTTP status lines creates a significant risk of connection accumulation and its associated problems.

Seeking a Solution: How to Prevent RestClient Connection Leaks?

Okay, so we've established that there's a problem. The RestClient isn't closing connections properly when it encounters a malformed HTTP status line, leading to a connection leak. The million-dollar question is: how do we fix it? I've got a few ideas, but I'd love to hear your thoughts and suggestions as well. Let's brainstorm some potential solutions.

1. Server-Side Fix (Ideal but Not Always Possible)

The most straightforward solution is to fix the root cause: the malformed HTTP status line from Server B. If we can convince Server B to respond with a valid HTTP status line (e.g., 200 OK without the leading space), the ProtocolException will disappear, and the RestClient should function correctly. However, this isn't always feasible. We might not have control over Server B, or the fix might require significant changes that can't be implemented immediately. So, we need to explore client-side solutions as well.

2. Custom Error Handling with ClientHttpResponse

One approach is to implement custom error handling within the RestClient to explicitly close the connection when a ProtocolException is encountered. We can achieve this by using a ClientHttpResponse interceptor. This interceptor would inspect the response and, if a ProtocolException is detected, manually close the connection. This ensures that the connection is released, even if the RestClient's default error handling fails.

Here's a conceptual example of how this might look:

import org.springframework.http.client.ClientHttpResponse;
import org.springframework.web.client.ResponseErrorHandler;
import org.springframework.web.client.RestClient;

public class CustomResponseErrorHandler implements ResponseErrorHandler {

    @Override
    public boolean hasError(ClientHttpResponse response) throws IOException {
        // Check for ProtocolException or other relevant errors
        return false; // Implement your error checking logic here
    }

    @Override
    public void handleError(ClientHttpResponse response) throws IOException {
        try {
            // Close the connection explicitly
            response.close();
        } catch (Exception e) {
            // Log the error
        }
        throw new CustomException("Error during HTTP communication");
    }
}

// Configure RestClient with the custom error handler
RestClient restClient = RestClient.builder()
        .errorHandler(new CustomResponseErrorHandler())
        .build();

This approach gives us fine-grained control over the error handling process and allows us to explicitly close the connection when necessary. However, it requires us to implement custom error handling logic and potentially duplicate some of the RestClient's built-in error handling.

3. Connection Pooling Configuration

Another strategy is to fine-tune the connection pooling configuration of the underlying HttpClient. By setting appropriate connection timeout and maximum connections per route, we can mitigate the impact of connection leaks. For example, we can set a shorter connection timeout to ensure that idle connections are closed more quickly. We can also limit the maximum number of connections per route to prevent the application from exhausting resources.

Here's an example of how to configure connection pooling with the JDK's HttpClient:

HttpClient httpClient = HttpClient.newBuilder()
        .connectTimeout(Duration.ofSeconds(3))
        .version(HttpClient.Version.HTTP_1_1)
        .executor(Executors.newFixedThreadPool(10)) // Use a thread pool for connection management
        .build();

JdkClientHttpRequestFactory factory = new JdkClientHttpRequestFactory(httpClient);

RestClient restClient = RestClient.builder()
        .requestFactory(factory)
        .build();

This approach doesn't directly fix the connection leak, but it helps to contain its impact by limiting the number of connections that can be created and ensuring that idle connections are closed in a timely manner. However, it's more of a workaround than a true solution.

4. Upgrade Spring Boot Version

It's possible that the issue has been addressed in a later version of Spring Boot or the underlying Spring Framework. Upgrading to the latest version might resolve the problem. Spring Boot and Spring Framework often include bug fixes and performance improvements that can address connection management issues. Before upgrading, carefully review the release notes and migration guides to ensure compatibility with your application.

5. Implement a Retry Mechanism with Connection Closure

We can implement a retry mechanism that attempts to re-establish the connection after an exception. This involves catching the ProtocolException, explicitly closing the connection (if possible), and then retrying the request. However, this approach should be used cautiously to avoid infinite retry loops and potential resource exhaustion.

6. Monitor and Alert on Connection Leaks

Regardless of the solution we choose, it's crucial to implement monitoring and alerting to detect connection leaks. We can use metrics tools to track the number of open connections and set up alerts if the number exceeds a threshold. This allows us to proactively identify and address connection leaks before they cause significant problems.

Conclusion: Addressing RestClient Connection Leaks

In conclusion, the RestClient's failure to close connections when encountering invalid HTTP status lines is a serious issue that can lead to connection leaks and application instability. We've explored several potential solutions, ranging from server-side fixes to client-side workarounds. The best approach depends on the specific circumstances and the level of control we have over the server-side and client-side environments.

I'm curious to hear your experiences and insights on this issue. Have you encountered similar problems with the RestClient or other HTTP clients? What solutions have you found effective? Let's discuss in the comments below!

I hope this deep dive into RestClient connection leaks has been helpful. Remember, proactive connection management is essential for building robust and reliable applications. Stay tuned for more troubleshooting adventures!