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Elastic Security and Google Cloud Integration for Security Analytics

4 posts · Feb 2023 – Jul 2026

What this trail covers

Elastic Security integrates with Google Cloud services, including Security Command Center (SCC) and Mandiant threat intelligence, to provide a comprehensive security analytics platform. This integration streamlines data ingestion from various Google Cloud sources via Elastic Agent or Dataflow, enhances threat detection and analysis, and aids in mitigating misconfigurations and compliance issues through Cloud Security Posture Management (CSPM). The solution aims to offer end-to-end security from data ingestion to incident response for hybrid workloads.

All Elastic trails
  1. Elastic and Axonius integrate to deliver unified asset intelligence for security teamsThis post details the integration of Axonius asset intelligence into Elastic Security. It describes the agentless setup for data ingestion from Axonius APIs into Elasticsearch, focusing on three key data streams: axonius.application (installed software, SaaS, licenses, extensions, audit activity), axonius.user (normalized to ECS user.* fields, surfacing orphaned identities and service accounts), and axonius.network (core asset inventory data from Source Adapters, enriched with user.* and related.ip fields).
  2. Elastic and Google Cloud: Enhancing security analytics from data ingestion to incident responseThis post details the integration of Elastic Security with Google Cloud services, specifically highlighting the ingestion of Google Cloud Security Command Center (SCC) findings and Mandiant threat intelligence into Elastic. It describes how Elastic Agent and Dataflow can be used for data ingestion from Google Cloud services, and how Elastic's CSPM complements Google Cloud's security features for posture management. The post emphasizes the unified approach to security analytics, threat intelligence, and incident response.
  3. How to build comprehensive customer financial profiles with Elastic Cloud and Google CloudThis post introduces a reference architecture for building comprehensive customer financial profiles by integrating Elastic Cloud and Google Cloud. It details the process of moving data from mainframes to Google Cloud using a Mainframe Connector, processing and enriching it in BigQuery, and then ingesting it into Elastic Cloud via Dataflow. The architecture also covers cloud orchestration from the mainframe and provides strategies for mainframe capacity planning, including remote dataset transcoding on Compute Engine VMs and data transfer via FICON and Interconnect. Specific use cases like customer experience, Customer 360, partnership management, cost optimization, and risk reduction are highlighted, with examples of Elastic's Graph feature for fraud detection.