Adloox delivers faster, more granular ad-verification insights with Google Cloud
Adloox is an ad-verification and insights platform that helps advertisers and media agencies measure campaign delivery, transparency, and brand safety at very large data volumes. To support its growth, Adloox migrated its platform and data pipelines to Google Cloud with help from implementation partner OP-Rate, replacing dedicated servers with a cloud-based architecture that could scale with traffic and automate more of the operational work.
- Organization
- Adloox
- Industry
- Tech & Comms
- Location
- France
- Published
- January 2022
Reported outcomes
−40%
quantified impactRisk, reliability & safety
Strategic outcomes
Catalog median for risk, reliability & safety deployments: −60% across 22 reported metrics. Compare benchmarks →
Primary read
Use case focus
Showing 3 of 4
- 1Fraud detection
- 2Data analytics
- 3Cloud migration
- Adloox needed to process huge volumes of advertising data, reduce fraudulent traffic, and provide faster, more granular reporting for clients.
- The company also wanted an infrastructure that could scale during large traffic spikes while reducing the time its team spent on infrastructure management and maintenance.
- Adloox built a parallel migration to Google Cloud and moved services load by load to keep client campaigns running during the transition.
- It orchestrated data processing with Google Kubernetes Engine and Cloud Load Balancing, used Dataflow for processing pipelines, stored and analyzed data with BigQuery, and used managed Google Cloud services to improve resilience and automation.
- The company also improved its fraud-detection workflows and client reporting on top of the new cloud architecture.
- Adloox halved its overnight batch processing time, making up-to-date data available faster.
- BigQuery enabled client reports over three, six, or twelve months of data in under ten seconds.
- Managed services reduced DevOps load by about 40%, freeing the team to focus more on new features and fraud detection algorithms.
- The platform became more flexible and reliable, with automatic scaling and auto-repair supporting traffic peaks.
Architecture
Adloox migrated its data platform to Google Cloud using a parallel architecture. Data processing services were orchestrated with Google Kubernetes Engine and Cloud Load Balancing across three regions, Dataflow handled processing, BigQuery was used for storage and client reporting, and other managed Google Cloud services supported monitoring, relational database needs, and workflow automation.
Implementation partners1
Sources & evidence1
AI-generated summary. Verify important details with the linked sources before relying on this case.