1S 6xv6LxoRyL8KtUXqWueQ
In a digital advertising platform, a robust feedback system is essential for the lifecycle and success of an ad campaign. This system comprises of diverse sub-systems designed to monitor, measure, and optimize ad campaigns. At Netflix, we embarked on a journey to build a robust event processing platform that not only meets the current demands but also scales for future needs. This blog post delves into the architectural evolution and technical decisions that underpin our Ads event processing pipeline.
Ad serving acts like the “brain” — making decisions, optimizing delivery and ensuring right Ad is shown to the right member at the right time. Meanwhile, ad events, after an Ad is rendered, function like “heartbeats”, continuously providing real-time feedback (oxygen/nutrients) that fuels better decision-making, optimizations, reporting, measurement, and billing. Expanding on this analogy:
Let’s dive into the journey of building this pipeline.
In November 2022, we launched a brand new basic ads plan, in partnership with Microsoft. The software systems extended the existing Netflix playback systems to play ads. Initially, the system was designed to be simple, secure, and efficient, with an underlying ethos of device-originated and server-proxied operations. The system consisted of three main components: the Microsoft Ad Server, Netflix Ads Manager, and Ad Event Handler. Each ad served required tracking to ensure the feedback loop functioned effectively, providing the external ad server with insights on impressions, frequency capping (advertiser policy that limits the number of times a user sees a specific ad), and monetization processes.
Key features of this system include:
There is an excellent prior blog post that explains how this systems was tested end-to-end at scale. This system design allowed us to quickly add new integrations for verification with vendors like DV, IAS and Nielsen for measurement.
As we continued to expand our third-party (3P) advertising vendors for measurement, tracking and verification, we identified a critical trend: growth in the volume of data encapsulated within opaque tokens. These tokens, which are cached on client devices, present a risk of elevated memory usage, potentially impacting device performance. We also anticipated increase in third-party tracking URLs, metadata needs, and more event types as our business added new capabilities.
To strategically address these challenges, we introduced a new persistence layer using Key-Value abstraction, between ad serving and event handling system: Ads Metadata Registry. This transient storage service stores metadata for each Ad served, and upon callback, event handler would read the tracking information to relay information to the vendors. The contract between the client device and Ads systems continues to use the opaque token per event, but now, instead of tracking information, it contains reference identifiers — Ad ID, the corresponding metadata record ID in the registry and the event name. This approach future proofed our systems to handle any growth in data that needs to pass from ad serving to event handling systems.
In January of 2024, we decided to invest in in-house advertising technology platform. This implied that the event processing pipeline had to evolve significantly — attain parity with existing offerings and continue to support new product launches with rapid iterations using in-house Netflix Ad Server. This required re-evaluation of the entire architecture across all of Ads engineering teams.
First, we made an inventory of the use-cases that would need to be supported through ad events.
Next, we examined upcoming launches, such as Pause/Display ads, to gain deeper insights into our strategic initiatives. We recognized that Display Ads would utilize a distinct logging framework, suggesting that different upstream pipelines might deliver ad telemetry. However, the downstream use-cases were expected to remain largely consistent. Additionally, by reviewing the goals of our telemetry teams, we saw large initiatives aimed at upgrading the platform, indicating potential future migrations.
Keeping the above insights & challenges in mind,
Putting together all the components in our vision –
Key components on event processing pipeline –
Ads Event Publisher: This centralized system is responsible for collecting ads telemetry and providing unified ad events to the ads engineering teams. It supports various functions such as measurement, finance/billing, reporting, frequency capping, and maintaining an essential feedback loop back to the ad server.
Realtime Consumers
Billing/Revenue: These are offline workflows designed to curate impressions, supporting billing and revenue recognition processes.
Ads Reporting & Metrics: This service powers reporting module for our account managers and provides a centralized metrics API that help assess the delivery of a campaign.
This was a massive multi-quarter effort across different engineering teams. With extensive planning (kudos to our TPM team!) and coordination, we were able to iterate fast, build several services and execute the vision above, to power our in-house ads technology platform.
These systems have significantly accelerated our ability to launch new capabilities for the business.
Key Takeways
We have an exciting list of projects on the horizon. These include managing ad events from ads on Netflix live streams, de-duplication processes, and enriching data signals to deliver enhanced reporting and insights. Additionally, we are advancing our Native Ads strategy, integrating Conversion API for improved conversion tracking, among many others.
This is definitely not a season finale; it’s just the beginning of our journey to create a best-in-class ads technology platform. We warmly invite you to share your thoughts and comments with us. If you’re interested in learning more or becoming a part of this innovative journey, Ads Engineering is hiring!
A special thanks to our amazing colleagues and teams who helped build our foundational post-impression system: Simon Spencer, Priyankaa Vijayakumar, Indrajit Roy Choudhury; Ads TPM team — Sonya Bellamy; the Ad Serving Team — Andrew Sweeney, Tim Zheng, Haidong Tang and Ed Barker; the Ads Data Engineering Team — Sonali Sharma, Harsha Arepalli, and Wini Tran; Product Data Systems — David Klosowski; and the entire Ads Reporting and Measurement team!
Behind the Scenes: Building a Robust Ads Event Processing Pipeline was originally published in Netflix TechBlog on Medium, where people are continuing the conversation by highlighting and responding to this story.
I know there are models available that can fill in or edit parts, but I'm…
As we look ahead, the relationship between engineers and AI systems will likely evolve from…
Lightweight, powerful, and generally inexpensive, the handheld vacuum is the perfect household helper.
Discover how latent bridge matching, pioneered by the Jasper research team, transforms image-to-image translation with…
Machine learning models have become increasingly sophisticated, but this complexity often comes at the cost…