Improving Fintech System Reliability with Load Shedding

Introduction

Load shedding is a technique used to improve the reliability of systems by intentionally dropping or shedding non-essential traffic during periods of high load. In the context of Fintech systems, this can be particularly useful for maintaining system stability and preventing cascading failures. In this post, we'll explore how to implement load shedding in Fintech systems using TypeScript and Next.js.

Understanding Load Shedding

Load shedding is a proactive approach to managing system load. By dropping non-essential traffic, the system can conserve resources and maintain stability. This is particularly important in Fintech systems, where a single point of failure can have significant consequences. Rate limiting and circuit breakers are related concepts, but load shedding is distinct in that it involves intentionally dropping traffic rather than simply limiting it.

Implementing Load Shedding

To implement load shedding in a Fintech system, you'll need to identify the non-essential traffic that can be safely dropped. This might include requests from external services, background jobs, or other non-critical components. Once you've identified the traffic to be shed, you can use a library like Redis to implement a load shedding mechanism. Here's an example of how you might implement load shedding using Redis and TypeScript:

import { RedisClient } from 'redis';

const redisClient = new RedisClient();

const shedLoad = async () => {
  const currentLoad = await redisClient.get('current_load');
  if (currentLoad > 1000) {
    // Drop non-essential traffic
    await redisClient.set('drop_traffic', 'true');
  } else {
    await redisClient.set('drop_traffic', 'false');
  }
};

setInterval(shedLoad, 1000);

Integrating with Next.js

To integrate load shedding with Next.js, you can use the getServerSideProps method to check the load shedding status before rendering a page. If the load shedding status is true, you can return a simplified version of the page or a error message. Here's an example:

import { GetServerSideProps } from 'next';

const HomePage = () => {
  return <div>Welcome to the home page</div>;
};

export const getServerSideProps: GetServerSideProps = async () => {
  const redisClient = new RedisClient();
  const dropTraffic = await redisClient.get('drop_traffic');
  if (dropTraffic === 'true') {
    return {
      props: {},
      redirect: {
        destination: '/error',
        permanent: false,
      },
    };
  } else {
    return {
      props: {},
    };
  }
};

Best Practices

When implementing load shedding, it's essential to follow best practices to ensure that the system remains stable and reliable. Here are some key considerations:

• Monitor system load: Use metrics like CPU usage, memory usage, and request latency to monitor system load.
• Identify non-essential traffic: Clearly identify the traffic that can be safely dropped during periods of high load.
• Test load shedding: Test the load shedding mechanism to ensure that it works as expected.
• Implement feedback mechanisms: Implement feedback mechanisms to ensure that the system can recover from load shedding.

Conclusion

Load shedding is a powerful technique for improving the reliability of Fintech systems. By intentionally dropping non-essential traffic during periods of high load, you can conserve resources and maintain system stability. By following the best practices outlined in this post and using tools like Redis and Next.js, you can implement load shedding in your Fintech system and improve its overall reliability. If you're interested in learning more about how Fulcra can help you improve the reliability of your Fintech system, get in touch with us today.