Thoughtbuzz Case Study
Thoughtbuzz is a social media intelligence platform that provides social management activities in a centralized manner. It identifies social trends and buzzwords to create content to engage the right influencers and detractors with in-depth information on their activities. Its aim is to integrate listening, management, social Customer Relationship Management (CRM), and analytics to simplify social media for business.
The centralized dashboard allows a customer to publish content on multiple social networks and analyze the responses on the published matter from various sources such as blogs, forums, and social networking sites in a unified manner. It then enables customers to manage, publish, schedule, respond, and analyze in a few clicks and helps them focus on their business instead of operational activities.
Thoughtbuzz has an illustrious clientele that includes global brands like Nestle, Toyota, and Samsung. These brands are usually in the midst of various social interactions, so we capture and analyze the data to gauge market trends and design a social media strategy for our clients. High performance, high availability, and scalability are thus imperative to support our growing customer base continuously.
We at Thoughtbuzz work with a broad technology stack that works with several backend resources working in tandem with each other. Our application captures a massive amount of user data from different platforms and stores it in databases, which ultimately decides the base performance of the application. This is why the application needs to be highly available as it interacts with various social media platforms. Managing a highly available database cluster containing massive amounts of data and simultaneously ensuring that the application runs smoothly was a big challenge for us.
Additionally, social pages undergo constant changes regarding the backend and user interface codes. We, therefore, wanted our deployment to be in an auto-scaled environment to support code changes. We also requested auto-monitoring support to recognize any form of system failure.
Why Alibaba Cloud?
We chose Alibaba Cloud because they are a leading cloud service provider with a large footprint in Asia. Since Asia is home to most of our clients, we wanted a solution provider based close to home.
The Alibaba Cloud platform enabled our team to set up an auto-scaled environment, ensuring alignment of hardware capacity and data that required processing. This allowed optimal use of hardware while lowering infrastructure costs. Our migration to the Alibaba Cloud environment improved the application performance significantly, which in turn led to a better customer experience.
Our nature of services involves a heavy exchange of social media data, so our backend application needs to process and analyze data continuously. Alibaba Cloud provides us with a flexible platform that effectively accommodates the need for resources. Their infrastructure offers us a robust cloud solution to provide maximum resource reliability.
The Alibaba Cloud architecture allows us to collect insights from multiple social media platforms onto a single dashboard. This helps in facilitating the performance of our business trends effectively on various social media.
Products used: Domain Name System (DNS), Virtual Private Cloud (VPC), Object Storage Service (OSS), Elastic Compute Service (ECS), Relational Database Service (RDS), Server Load Balancer
The deployment architecture provided by Alibaba Cloud meets two essential requirements of availability and scalability, as it interacts with various social media platforms. The DNS service derives the query from the browser and routes it to the Server Load Balancer. The Server Load Balancer routes the queries only to healthy instances, thus increasing the availability of the entire application.
The Render load balancer is set up to serve the front-end of the application with support from the Alpha and Beta load balancers. Alibaba Cloud Auto Scaling helps increase the scalability of the architecture so customers do not face issues on their live website.
We can leverage this benefit by using high-performance ECS instances. Alpha and Beta process the information and update the MongoDB, which adds to the application availability by managing large data. The Render application takes the processed data from the Mongo DB and serves it to the end user. This process helps provide zero downtime when the code changes. The entire application is placed within a VPC, which acts as an added security layer protecting our basic infrastructure.