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Log_replication.md

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Log replication & analytics

Google Cloud produces all kinds of logs that are automatically sent to Cloud Logging. However, in some situations, you may want to use a third party such as Splunk for log processing and analytics. This solution presents an architecture to replicate logs from Cloud Logging to a third-party service, using Dataflow. The solution ensures that all changes done in the upstream databases are promptly replicated in the destination analytics replica, with minimal delay (in the order of single digit seconds).

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Technical benefits

  • Serverless experience: Data volume can vary widely from logging applications or transactional databases. Dataflow obviates that need entirely. Dataflow’s service layer goes beyond auto-provisioning. Features like dynamic work rebalancing, autoscaling, and service backends like Streaming Engine are built to handle your workload at any scale without needing user intervention.
  • Easy operations: Dataflow offers several features that helps organizations ensure the uptime of their pipelines. Snapshots preserve the state of your pipeline for high availability / disaster recovery scenarios, while in-place streaming update can seamlessly migate your pipeline to a new version without any data loss or downtime.
  • Google-provided Templates: Google provides Dataflow templates make deployment as easy as filling out a web form. Send logs to Splunk, Elasticsearch, or Datadog with our partner-provided templates.
  • Low latency: Dataflow’s at-least-once delivery mode can help your pipeline achieve sub-second processing latencies, essential for your mission-critical logging applications.
  • Monitoring tools: In-line logging, job visualizers, monitoring charts, integrated error reporting and smart insights help you optimize the performance of your pipeline, and can catch any stuckness or slowness issues before they turn into outages.