Q3.
Troubleshooting Hadoop and Kafka Architectures in Azure
General Troubleshooting Steps:
- Check Logs: Logs are the primary source of information for troubleshooting issues.
- Hadoop: Use the YARN ResourceManager, NodeManager, and application logs.
- Kafka: Check the broker logs, zookeeper logs, and producer/consumer client logs.
- Monitor Resources: Ensure your clusters are not running out of memory, disk space, or other critical resources.
- Use tools like Azure Monitor, Grafana, or the Hadoop ResourceManager UI.
- Network Issues: Check for network connectivity issues between different components.
- Verify firewall settings and VNet configurations.
- Configuration Errors: Incorrect configurations can lead to various issues.
- Ensure that configuration files (e.g.,
hdfs-site.xml, core-site.xml, server.properties) are correctly set up.
- Service Health: Ensure all services are up and running.
- Use tools like
jps to check Java processes for Hadoop.
- Use
kafka-topics.sh and kafka-consumer-groups.sh to check Kafka topics and consumer groups.
- Version Compatibility: Ensure compatibility between different components and libraries.
Troubleshooting Specific Issues:
Hadoop:
- Job Failures: Check the application logs in the ResourceManager and NodeManager UI. Look for errors and exceptions.
- DataNode Issues: If a DataNode is down, check its logs for disk errors or network issues.
- HDFS Corruption: Use
hdfs fsck / to check the health of the filesystem.
- YARN Resource Issues: Check the ResourceManager UI for resource allocation problems. Increase resources if necessary.
Kafka:
- Broker Issues: Check broker logs for errors. Common issues include out-of-memory errors and disk issues.
- Zookeeper Issues: Check the Zookeeper logs for connectivity issues or leader election problems.
- Producer/Consumer Issues: Check client logs for serialization errors, network timeouts, and authentication issues.
- Topic Issues: Use
kafka-topics.sh to describe topics and check for under-replicated partitions or leader issues.