Generative AI in Banking

 

Cyber Threat - Infographic

 

A Snapshot of Generative AI Tools

 

5 must-ask questions for evaluating new product opportunities:

 5 must-ask questions for evaluating new product opportunities:

1. Who is the customer? (Segment) 2. How do we know their problems? (Discovery) 3. How do we reach out to them? (Go To Market) 4. How do we iterate/ scale? (Roadmap) 5. How do we know we are succeeding? (Metrics)

Evolution of the Netflix API architecture

 

Monolith. The application is packaged and deployed as a monolith, such as a single Java WAR file, Rails app, etc. Most startups begin with a monolith architecture.

Direct access. In this architecture, a client app can make requests directly to the microservices. With hundreds or even thousands of microservices, exposing all of them to clients is not ideal.

Gateway aggregation layer. Some use cases may span multiple services, we need a gateway aggregation layer. Imagine the Netflix app needs 3 APIs  (movie, production, talent) to render the frontend. The gateway aggregation layer makes it possible.

Federated gateway. As the number of developers grew and domain complexity increased, developing the API aggregation layer became increasingly harder. GraphQL federation allows Netflix to set up a single GraphQL gateway that fetches data from all the other APIs.

References: 

[1] How Netflix Scales its API with GraphQL Federation (Part 1): https://netflixtechblog.com/how-netflix-scales-its-api-with-graphql-federation-part-1-ae3557c187e2 (image source)

[2] Why You Can't Talk About Microservices Without Mentioning Netflix: https://smartbear.com/blog/why-you-cant-talk-about-microservices-without-ment/

How to Scale website? Its also applicable to all the products

 

Suppose we have two services: inventory service (handles product descriptions and inventory management) and user service (handles user information, registration, login, etc.).

Step 1 - With the growth of the user base, one single application server cannot handle the traffic anymore. We put the application server and the database server into two separate servers.

Step 2 - The business continues to grow, and a single application server is no longer enough. So we deploy a cluster of application servers.

Step 3 - Now the incoming requests have to be routed to multiple application servers, how can we ensure each application server gets an even load? The load balancer handles this nicely.

Step 4 - With the business continuing to grow, the database might become the bottleneck. To mitigate this, we separate reads and writes in a way that frequent read queries go to read replicas. With this setup,

the throughput for the database writes can be greatly increased.

Step 5 - Suppose the business continues to grow. One single database cannot handle the load on both the inventory table and user table. We have a few options:

1. Vertical partition. Adding more power (CPU, RAM, etc.) to the database server. It has a hard limit.

2. Horizontal partition by adding more database servers.

3. Adding a caching layer to offload read requests.

Step 6 - Now we can modularize the functions into different services. The architecture becomes service-oriented / microservice.

How does CDC (Change Data Capture) work?

 Data stored in the database could be interesting to many other data systems, such as analytics, AI, etc. If we have thousands of data systems, do we have to write thousands of converters?

The answer is NO. Change data capture (CDC) is a process that can solve the problem. This is how CDC works:

1. Data is written to the database normally.

2. Database uses the transaction log to record the modifications. 

3. CDC software uses the source connector to connect to the database and reads the transaction log.

4. The source connector publishes the log to the message queue.

5. CDC software uses its sink connector to consume the log.

6. The sink connector writes the log content to the destination.

All these operations except step 1 are transparent to the user. Popular CDC solutions, such as  Debezium, have connectors for most databases, such as MySQL, PostgreSQL, DB2, Oracle, etc. We only need to set up the CDC link between two databases and the data will automatically flow to the destination.