Publisher Subscriber Model (Pub/Sub Model)

What is Pub/Sub Messaging ? Related Terminology

Sub

Publisher —> Input(Channel) —> Output(Channel) —> Sub

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Sub

Here The Publisher is produces the Message , through the help of the Input Channel The Message can be Sends to the Output Channel and the message receives Needed Consumers/ All The Consumers / Different Consumers

There should be a multiple Output Channel for Multiple Consumers

Every Message which is produced by Publisher its not All the Consumers is has to React , Just who else have to React they Can React the Message

There should be an need for Message Broker between Input & Output Channel

Its takes care of the Multiple Responsibilities

One of the Responsibilities is , When The Publisher Publishing the Event(Message) in some format , the format could have to be modified / Its enriched with other data then its passes to the Output Channel

Message Broker can divide the Message into different topics , then consumers listen to particular topic then they can react accordingly

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Publisher —> Input(Channel) —> Message Broker —> Output(Channel) —> Sub

Sub

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Pub/Sub Use Cases

Async Workflow : Business Workflow , If any of the order has been placed the customer will get the Notification Through the Email or Message (Send Notification) and The Communication has to be send to the Warehouse (Process item for packing) , The finance department has to send the Invoice about the Order , Initiating seller workflow for delivery of the product.

Here some responses has to been happen ASAP , like if customer click any of the product in Add to Cart instantly the product could be added in cart here we can’t able to use Asynchronous Communication.

Decoupling : Every users activity to be recorded for analytic purpose , the each activity has to be store in database , so User actions and Data processing at backend cannot be synchronous

Load Balancing : Increased load can be balanced either by increasing the number of subscribers and even if subscribers are limited , then too messages would be retained in the queue.

Deferred Processing : Its similar to Asynchronous workflow Data Streaming

Performance Metrics :

Throughput : Some amount of work done in particular time , in system design Throughput can be considered as Number of API calls served per unit time.

Bandwidth : Its comes into to picture when the data getting delivered / Transferred over the connected networks on multiple location

Ex : Netflix , the streaming can be happing in every different location around the globe so the data can be get it in the real time.

1.Not enough Resources —> High Bandwidth —> Less Throughput(Performance)

2.High Resources —> Less Bandwidth —> Less Throughput(Performance)

3.High Resources —> High Bandwidth —> High Throughput(Performance)

Response Time : When our System will serve 1000 requests per second , and the Response also will be in One second

High Resource —> High Bandwidth —> Time Takes (More Time for an Each Request ) —> Throughput (Performance )

In this above case The Performance will be low ,because the time taken for each request is more.

Performance of Components

Performance Metrics of an Application :

API Response Time —> Throughput of APIs —> Error Occurrences —> Bug / Defect in the Code

Performance Metrics of an Databases :

Time Taken by various database queries —> Number of queries executed per unit time (or throughput)

Performance Metrics of an Cache :

Latency of Writing to Cache —> Number of Cache Eviction and Invalidation —> Memory of Cache Instance

Performance Metrics of an Message Queues :

Rate of Production and Consumption —> Fraction of Stale or Unprocessed Messages —> Number of Consumers affects Bandwidth and Throughput

Performance Metrics of an Workers :

Time taken for Job Completion —> Resources used in Processing

Performance Metrics of an Server Instances :

Every Components would be run on some Hardware Machines/Some Instance in Cloud ex: Application , Databases ,Workers , Message Queues etc.. all of them need some Infrastructure support running on the Instances , on every Component its self would have some requirement , Those requirements are

Memory

CPU

Performance Metrics Tools :

PM Tools – Performance Management Tools

There are different many tools to measure the performance of the Application , Cache , Message Queues , Databases , etc..