adtech

A simple implementation of an AdTech web service that tracks the ads that are being delivered through their lifecycle and generates some simple statistics.

The web service’s endpoints and request / response formats are described below.

Ingestion

POST /ads/delivery that is triggered whenever one of our ads is loaded on a page and follows the spec below: Request format:

    {
        "advertisementId": 4483,
        "deliveryId": "244cf0db-ba28-4c5f-8c9c-2bf11ee42988",
        "time": "2018-01-07T18:32:23.602300+0000",
        "browser": "Chrome",
        "os": "iOS",
        "site": "http://super-dooper-news.com"
    }

Response format:

• HTTP response code 200 if all went fine
• HTTP response code 500 if any error occurred

POST /ads/click that is triggered whenever an user clicks on one of the ads we delivered. It follows the spec below: Request format:

    {
        "deliveryId": "244cf0db-ba28-4c5f-8c9c-2bf11ee42988",
        "clickId" : "fff54b83-49ff-476f-8bfb-2ec22b252c32",
        "time": "2018-01-07T18:32:34.201100+0000",
    }

Response format:

• HTTP response code 200 if everything went fine
• HTTP response code 404 if we never received the given delivery
• HTTP response 500 if something went wrong

POST /ads/install that follows the spec below: Request format:

    {
        "installId": "144cf0db-ba28-4c5f-8c9c-2bf11ee42988",
        "clickId" : "fff54b83-49ff-476f-8bfb-2ec22b252c32",
        "time": "2018-01-07T18:32:34.201100+0000",
    }

Response format:

• HTTP response code 200 if everything went fine
• HTTP response code 404 if we never received the given click HTTP response 500 if something went wrong

Statistics

GET /ads/statistics?start={start}&end={end} Description: Returns the number of views, clicks and installs in the given period Example: /ads/statistics?start=2018-01- 07T14:30:00+0000&end=2018-01-07T18:20:00+0000

Response format:

    {
        "interval" : {
            "start" : "2018-01-07T14:30:00+0000",
            "end" : "2018-01-07T18:20:00+0000"
        },
        "stats": {
            "deliveries": 10,
            "clicks": 4,
            "installs": 1
        }
    }

GET /ads/statistics?start={start}&end={end}&group_by={category1}...&group_by={categoryN} Description returns the number of views, clicks and installs in the given period grouped by the given categories Example: /ads/statistics?start=2018-01-07T14:30:00+0000&end=2018-01-07T18:20:00+0000&group_by=browser

Response format:

    {
        "interval": {
            "start": "2018-01-07T14:30:00+0000",
            "end": "2018-01-07T18:20:00+0000"
        },
        "data": [
            {
                "fields": {
                    "browser": "Chrome"
                },
                "stats": {
                    "deliveries": 10,
                    "clicks": 4,
                    "installs": 1
                }
            },
            {
                "fields": {
                    "browser": "Safari"
                },
                "stats": {
                    "deliveries": 2,
                    "clicks": 1,
                    "installs": 1
                }
            }
        ]
    }

SCALABLE DESIGN -

1. In order to cater to load of requests we should create a dedicated ingest micro-service to receive the delivery requests and ingest into the cache ( elastic search, Redis, etc. ) so that it is readily available for click service to identify the delivery ID, as click and install ingestion depends on delivery ID.
2. Once the delivery, click and install are captured using ingest service then we can publish the message ( delivery, click, and install ) on message queue and there will be another micro-service to actually persist the data in a data store - and sends acknowledgement to the publisher.
3. We should create different topics for delivery, click and install messages.
4. Finally there will be a separate micro-service to cater to statistics request(query-service).