Kafka Logs & Metrics Monitoring

Kafka logs are the recorded events of data transactions within a Kafka cluster. They serve as a crucial record of all activity, enabling users to track data flow, troubleshoot errors, and ensure data integrity.

Key metrics to monitor in Kafka include message throughput, latency, consumer lag, broker health, disk utilization, and network throughput. Monitoring these metrics helps ensure optimal performance and timely data processing.

Atatus provides comprehensive monitoring for Kafka through its agent-based approach. The Atatus Kafka integration collects metrics from Kafka brokers, producers, consumers, and ZooKeeper ensemble, offering real-time insights into the performance and health of your Kafka clusters.

Kafka lag refers to the delay between the production and consumption of messages within Kafka. High consumer lag can indicate processing bottlenecks or slow consumer performance, leading to data backlog and degraded system performance.

By closely monitoring Kafka metrics such as throughput, latency, and consumer lag, you can identify areas for optimization. Adjusting configurations, scaling resources, and optimizing consumer groups based on metric insights can help improve overall Kafka performance.

ZooKeeper serves as a centralized repository for maintaining Kafka cluster metadata and configuration settings. Monitoring ZooKeeper metrics, such as connection counts and request latency, is essential for ensuring the stability and reliability of Kafka clusters.

Regular monitoring of Kafka logs and metrics is recommended, with frequency varying based on the size and complexity of the Kafka deployment. Daily reviews are typically sufficient for most environments, with additional checks during peak usage periods or after system updates.

Yes, Atatus allows for flexible alerting configurations based on Kafka metrics thresholds. Users can define custom alert policies to trigger notifications via email, Slack, or other channels when specific Kafka metrics exceed predefined thresholds, enabling proactive issue resolution and performance optimization.

Atatus employs robust security measures to protect Kafka log data within its platform, including data encryption in transit and at rest, role-based access controls (RBAC), and compliance with industry security standards such as SOC 2 and GDPR. Additionally, Atatus provides audit logs and monitoring features to track and monitor access to Kafka log data, ensuring data integrity and confidentiality.

If you exceed your log ingestion limits, we would contact you to discuss on stopping further processing new log data or upgrade your subscription.

You can choose to store logs in Atatus for a limited time (e.g., 7 days) or export them to external storage solutions like Amazon S3 for long-term retention.

To access historical log data beyond the retention period, you can rely on log data exports from Amazon S3, where you can push the logs into Atatus for further analysis.

Yes, Atatus provides users with the flexibility to customize log retention settings. Users can adjust retention periods based on their specific needs, aligning with compliance standards or internal data management policies.