WPP Leverages Google Cloud for AI Marketing Data and Platform Engineering
WPP partnered with Google Cloud to build a unified data backbone and custom platform engineering path, powering its AI marketing system, WPP Open. This infrastructure overcomes data fragmentation across global agencies, enabling efficient and secure deployment of AI tools. By standardizing serverless compute patterns and data processing workflows, WPP can now deploy targeted marketing campaigns in days instead of months. Key components include a service-based data foundation, Managed Service for Apache Spark, Kubeflow, and GitLab CI/CD for traceable, immutable deployments.
- →Centralized Data Foundation for AI Marketing
- →Standardized Data Ingestion and Transformation
- →Standardized Enterprise CI/CD and Immutable Deployments
- →Automated Security and Intelligent Networking
- →Deep Observability for Operational Health
Notes (5) ›
- Centralized Data Foundation for AI Marketing
WPP constructed a unified data backbone on Google Cloud, centralizing Google Cloud Storage and BigQuery into dedicated, shared data projects while segregating compute workloads. This service-based structure simplifies user experience, ensures a unified source of truth, and applies granular IAM controls for data security.
- Standardized Data Ingestion and Transformation
Raw marketing data is ingested into dedicated GCS buckets, then Managed Service for Apache Spark executes custom jobs to cleanse, normalize, and canonicalize it into standardized cohort definitions. This serverless architecture, combined with Kubeflow for pipeline orchestration, avoids infrastructure overhead and ensures full source traceability.
- Standardized Enterprise CI/CD and Immutable Deployments
WPP developed reusable GitLab CI/CD templates for various enterprise workloads, including Cloud Run applications and pipelines. They adopted a "build once, deploy many" methodology using Artifact Registry and cross-project IAM logic to promote immutable container images directly to production environments, ensuring parity and reducing risk.
- Automated Security and Intelligent Networking
WPP integrated Wiz security scanning into the CI/CD pipeline and enforced zero-trust access across internal applications using Google Cloud Identity-Aware Proxy. Additionally, intelligent Virtual Private Cloud (VPC) logic automatically identifies and resolves networking conflicts, preventing deployment failures and accelerating release cycles.
- Deep Observability for Operational Health
To ensure a resilient platform foundation, WPP's engineering team monitors strict operational metrics beyond just deployment frequency. Key metrics include request latency (p50, p95, p99), 4xx and 5xx error rates, container startup times to mitigate cold starts, and overall CPU and memory utilization.
https://cloud.google.com/blog/products/media-entertainment/how-wpp-operationalizes-platform-and-data-engineering-for-ai-marketing/
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