Distributed Job Scheduler Using Redisson

Job Scheduling is one of the main components required for every kind of business unit.Supporting Job scheduling in a distributed and scalable environment is one of the challenging problems to solve. Redis provides multiple solutions for distributed and scalable systems with the help of unique data structures implementation. In this blog we will discuss how to implement a distributed Job Scheduler using Redis via Redisson with a working spring boot project example.

Design and Implement Rate Limiter

Rate limiter is one of the most important aspects when designing a microservice system. It is used to limit the usage of an api upto a particular threshold. When an api exceeds its TPS (Transactions Per Second) threshold limit, it should ignore those extra requests to save all downstream services and should send proper http status to its client.

Let's take an example to understand this. Let's say there is an api whose maximum TPS it can handle is 500 requests per second. If we apply a rate limiter on this api upto 500 request per second and we experience 700 request per second in a particular time window, then 200 extra requests will be ignored with an http status 429 i.e. TOO_MANY_REQUEST. Before going into detail of how to implement a Rate limiter in a distributed environment, let's understand various advantages of using it.