Designing Smart Notification of Stock Price Changes

Requirements

• 3 million users
• 5000 stocks + 250 global stocks
• a user gets notified about the price change when
  1. subscribing the stock
  2. the stock has 5% or 10% changes
  3. since a) the last week or b) the last day
• extensibility. may support other kinds of notifications like breaking news, earnings call, etc.

Sketching out the Architecture

Contexts:

• What is clearing? Clearing is the procedure by which financial trades settle – that is, the correct and timely transfer of funds to the seller and securities to the buyer. Often with clearing, a specialized organization acts as an intermediary known as a clearinghouse.
• What is a stock exchange? A facility where stock brokers and traders can buy and sell securities.

Apple Push Notification service<br>(APNs)

Google Firebase Cloud Messaging

(FCM)

Google Firebase Cloud Messaging<br>(FCM)

Email Services

AWS SES /sendgrid/etc

Email Services<br>AWS SES /sendgrid/etc

notifier

notifier

External Vendors

Market Prices

[Not supported by viewer]

Robinhood App

Robinhood App

API Gateway

API Gateway

Reverse Proxy

Reverse Proxy

batch write

batch write

price

ticker

[Not supported by viewer]

Time-series DB

influx or prometheus

Time-series DB<br>influx or prometheus

Tick every 5 mins

[Not supported by viewer]

periorical read

periorical read

price

watcher

price<br>watcher

User Settings

User Settings

Notification Queue

Notification Queue

throttler cache

throttler cache

cronjob

cronjob

What are those components and how do they interact with each other?

• Price ticker
  • data fetching policies
    • option 1 preliminary: fetches data every 5 mins and flush into the time-series database in batches.
    • option 2 advanced: nowadays external systems usually push data directly so that we do not have to pull all the time.
  • ~6000 points per request or per price change.
  • data retention of 1 week, because this is just the speeding layer of the lambda architecture.
• Price watcher
  • read the data ranging from last week or last 24 hours for each stock.
  • calculate if the fluctuation exceeds 5% or 10% in those two time spans. we get tuples like (stock, up 5%, 1 week).
    • corner case: should we normalize the price data? for example, some abnormal price like someone sold UBER mistakenly for $1 USD.
  • ratelimit (because 5% or 10% delta may occur many times within one day), and then emit an event PRICE_CHANGE(STOCK_CODE, timeSpan, percentage) to the notification queue.
• Periodical triggers are cron jobs, e.g. Airflow, Cadence.
• notification queue
  • may not necessarily be introduced in the first place when users and stocks are small.
  • may accept generic messaging event, like PRICE_CHANGE, EARNINGS_CALL, BREAKING_NEWS, etc.
• Notifier
  • subscribe the notification queue to get the event
  • and then fetch who to notify from the user settings service
  • finally based on user settings, send out messages through APNs, FCM or AWS SES.