Here, I will discuss the common problems faced by the Developer while integrating Spring Boot with Google Cloud Pub-Sub
Q-1). How to resolve the Authentication problem?
A-1). To resolve the authentication problem, use the proper credentials, as it can be a challenge. You are using Google Cloud SDK, there you are running one command
gcloud auth application-default login
Once you run the above command, it will opt to authorize your Google account, which you have used to install the components in Google Cloud Console. Use the proper account and to authenticate and authorize, and it will store the credentials in your local machine and use that json file in your Spring Boot application.
Q-2). What if proper access control is not associated with the account?
A-2). If proper access control is not associated with your account that you are using from your Spring Boot application to connect to Google Cloud Components, here it is Google Cloud Pub-Sub, then it will throw an exception regarding accessibility. To access, Google Cloud Pub-Sub and to read and write operations in Pub-Sub your service account requires 2 access options Pub/Sub Admin and Pub/Sub Editor. You can enable these 2 options from the IAM menu of Google Cloud Console.
Q-3). What will happen if we use the wrong configurations?
A-3). If you use the wrong configuration errors, then your Spring Boot application will not be able to communicate properly with Google Cloud Pub-Sub. Different configuration properties are Pub/Sub Project ID, Topic Name, and Subscription Name. Wrong values can lead to issues in connecting to Pub/Sub.
Q-4). What will happen if the message is not ordered?
A-4). Pub/Sub doesn’t guarantee any message delivery. So, if your application is not stringent that I will first acknowledge this message and then that message, then it is not a problem, But if your application expects a proper message ordering as defined by you then it will be a problem. To resolve this, there are certain steps as mentioned below:
- Message Grouping → You can create messages that need to be processed in order to be grouped together. When you are publishing messages in Pub/Sub, you can include a message attribute `
groupId
` that represents the group to which the message belongs.
import com.google.cloud.pubsub.v1.Publisher;
import com.google.pubsub.v1.PubsubMessage;
import com.google.protobuf.ByteString;
// Autowire the Publisher instance
@Autowired
private Publisher publisher;
public void publishOrderedMessage(String topicName, String message, String groupId) {
PubsubMessage pubsubMessage =
PubsubMessage.newBuilder()
.setData(ByteString.copyFromUtf8(message))
.putAttributes("groupId", groupId) // Add the groupId as an attribute
.build();
ApiFuture<String> messageIdFuture = publisher.publish(pubsubMessage);
}
- Create Ordered Queues → In your consumer application, create multiple separate subscription-based message listeners (workers) to process messages from each group (queue). Each worker will listen to a specific subscription representing a message group.
import org.springframework.cloud.gcp.pubsub.core.subscriber.MessageReceiver;
import org.springframework.messaging.Message;
import org.springframework.stereotype.Component;
import com.google.cloud.pubsub.v1.AckReplyConsumer;
@Component
public class PubSubMessageReceiver implements MessageReceiver {
@Override
public void receiveMessage(Message<?> message) {
// Process the received message here
String payload = (String) message.getPayload();
LOGGER.info("Received message: {}", payload);
// Acknowledge the message
AckReplyConsumer consumer = (AckReplyConsumer) message.getHeaders().get(GcpPubSubHeaders.ACKNOWLEDGEMENT);
consumer.ack();
}
}
- Use a partition key → You can use a partitioning key to create Pub/Sub Topic. The partitioning key will ensure that the message with the same key is sent to the same partition, and thus they are received in order by a simple worker. You can use the `
groupId
` as the partitioning key for creating the Pub/Sub Topic by using the `gcloud
` command-line tool or Google Cloud Console.
Q-5). What is the usefulness of using a dead-letter queue?
A-5). Dead-Letter Queues are the types of queues that will handle those messages which get repeatedly fail to be processed. The usefulness of these queues is for application robustness. The steps to create a Dead-Letter Queue are as follows:
- Create a Dead-Letter Topic → Create a new Pub/Sub Topic that will store the problematic messages that fail to be processed after a certain no. of retries.
- Create a Dead-Letter Subscription → Create a Dead-Letter Subscription for the Pub/Sub Topic. Configure the Dead-Letter Subscription to have an acknowledgment deadline and retry policy suitable for handling problematic messages.
- Acknowledgment Deadline → It is the time given to the subscriber to acknowledge a message before it is considered unacknowledged and retired.
- Retry Policy → Retry policy determines how many times the Pub/Sub service should attempt to redeliver an unacknowledged message before moving them to Dead-Letter Queue.
- Handle Dead-Letter Messages → In your application, you can have a separate message receiver that will handle them separately and take necessary actions like logging, notifying administrators, or attempting to process the messages differently.
import org.springframework.cloud.gcp.pubsub.core.subscriber.MessageReceiver;
import org.springframework.messaging.Message;
import org.springframework.stereotype.Component;
import com.google.cloud.pubsub.v1.AckReplyConsumer;
@Component
public class PubSubMessageReceiver implements MessageReceiver {
@Override
public void receiveMessage(Message<?> message) {
// Handle the Dead-Letter message here
String payload = (String) message.getPayload();
LOGGER.info("Dead-LetterReceived message: {}", payload);
// Acknowledge the message to remove it from the Dead-Letter Queue
AckReplyConsumer consumer = (AckReplyConsumer) message.getHeaders().get(GcpPubSubHeaders.ACKNOWLEDGEMENT);
consumer.ack();
}
}
Q-6). What will be the impact if proper error handling and retry logic are not there?
A-6). Proper error handling and retry logic should be implemented to handle transient failures and ensure message processing reliability.
Q-7). What will be the impact if proper Message Serialization/Deserialization is not there?
A-7). If you don’t properly use the Message Serialization or Deserialization technique to handle messages between your application and Pub/Sub then it can lead to data corruption and parsing errors.
Q-8). How to handle Concurrent Message Processing?
A-8). If multiple instances of your application are processing messages concurrently, be aware of potential race conditions and data consistency issues.
There are various ways to handle concurrent message processing, as follows:
- Thread-safe Message Processing Logic → Use of local variables and synchronized block protects shared resources. And avoid a global mutable state in your message processing code.
- Limit the no. of Concurrent messages → By default, Spring Cloud GCP sets up a single message listener container for a subscription, which means messages are processed one by one. But if you need to process the messages concurrently, then you can increase the no. of containers by configuring the
concurrency
property. - Throttle Processing Rate → Implement a throttling mechanism to control the rate at which the messages are processed. This will prevent overloading your application when there’s a sudden surge in message traffic.
- Idempotent Processing → It means that your message processing logic is idempotent, which means processing the same message multiple times will not have any side effects. As there is no guarantee in the delivery of messages in Pub/Sub to be exactly once.
- Use Spring’s Asynchronous Processing → By annotating your message processing logic with
@Asynch
annotation, Spring will automatically execute the logic on a separate thread from a pool of threads managed by Spring. - Sharding and Partitioning → It will process the messages concurrently without contention. This approach can be beneficial to process large volumes of data.
- Monitor and Adjust → Monitor the performance and resource usage of your application as it will increase concurrency.
import org.springframework.scheduling.annotation.Async;
import org.springframework.stereotype.Component;
@Component
public class PubSubMessageProcessor {
@Async
public void processMessage(String message) {
// Message processing logic here
LOGGER.info("Processing message: {}", message);
// Simulate processing time
try {
Thread.sleep(1000);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
Q-9). Is it a good practice to acknowledge the messages?
A-9). Yes, it is a good practice to acknowledge the messages only after successful processing to avoid duplication of messages.
Q-10). Is the testing environment Pub/Sub can behave differently from the Production environment?
A-10). There is a high possibility that the Pub/Sub in both environments can behave differently. So need to be cautious about that.
Q-11). What are Resource Limitations? Will we have to be aware of that?
A-11). Resource Limitations of Pub/Sub are, such as message size limits, rate limits, and quotas. Be aware of the limitations imposed by Pub/Sub.
Q-12). Don’t make long polling and idle connections to entertain.
A-12). It is advisable that appropriately configured the connection and session timeouts for long-polling operations to prevent idle connections from being terminated.
Q-13). Do proper scaling and load balancing.
A-13). Plan for scaling your application to handle a large number of messages and make sure your load balancer works well with long-lived connections.
Q-14). Implement proper monitoring and logging.
A-14). Implement proper monitoring and logging to track message processing, identify errors, and monitor Pub/Sub quotas and usage.
Q-15). Is Synchronous communication possible using Google Pub/Sub?
A-15). Pub/Sub is an asynchronous messaging service. If you need synchronous communication, you’ll have to consider alternative solutions like Cloud Functions or Cloud Run for HTTP Endpoints.