Transforming an Elasticsearch Solution to OpenSearch Service for Streamlined Business Operations

Project Summary

PXL is an open source social network platform for content creators. It enables users to create public or private spaces for any use such as any particular task base space or any other. Furthermore, users can take advantage of social features such as building connections, posting projects that pique the interest of other users, adding team members, notifications, project participation, and more. They can also manage their profiles and conduct a global search. This social network tool offers an online version where anyone can experience this free tool. PXL’s user interface is very logical, and users can easily navigate through various elements.

Problem Statement

The client’s requirement was to build a full-fledged backend application that can easily integrate with their prebuilt front-end application, and he later asked us to integrate the backend with the front-end.

We had to design and create a social platform where users can showcase their inventions and gain exposure. One can post any software project, categorize them, invite team members, and also participate in other projects.

Additionally, to meet the need for significant content uploads, a solution had to be developed that could easily handle the upload of media files while still being affordable and effective.

We also had to create a real-time notification system that monitors all network activity such as accepting requests, declining requests, and being removed from one’s network.

Our Solution

1. With thorough testing, responsive design, and increased efficiency and performance, we concentrated on completing each task as effectively as we could.
2. Based on the client’s requirements, we used S3 bucket, RDS, EC2, and flask microservice for media files and SES for emails.
   - Amazon S3 was used for file hosting and data persistence.
   – Amazon Relational Database Service (RDS) was used for database deployment as it simplifies the creation, operation, management, and scaling of relational databases.
   – Amazon EC2 was used for code deployment because it offers a simple web service interface for scalable application deployment.
3. We sent emails using Amazon SES because it is a simple and cost-effective way to send and receive emails using your own email addresses and domains.
4. Django-graphQL was used for the backend, and Next.js was used for the front end. Django includes a built-in object-relational mapping layer (ORM) for interacting with application data from various relational databases.
   – GraphQL aims to automate backend APIs by providing type-strict query language and a single API Endpoint where you can query all information that you need and trigger mutations to send data to the backend.
   – Next.js offers the best server-side rendering and static website development solutions. We utilized the flask microservice to help with high content uploads since flask upload files give your application the flexibility and efficiency to manage file uploading and serving.
5. Using Github’s automated CI/CD pipeline we have triggers for code lookup and deployment.

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Technologies

Django-GraphQL, Next.js, PostgreSQL, AWS S3, EC2, SES and RDS

Success Metrics

• All deliverables were completed on time and exceeded expectations.
• Met all the expectations of the client and with positive feedback.
• The client was constantly updated on the status of the project.

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About

A non-profit healthcare insurance provider that encountered difficulties in managing the high volume of data on their on-premises system, which impeded their capacity to analyze that data efficiently to make informed business decisions. To address these issues, they chose to migrate their data to Amazon Redshift.

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Business Challenge

As their business grew, the insurance provider faced several challenges with their legacy system. Most importantly, their on-prem data warehouse, Oracle Exadata, required significant time and resources to administer, especially for large datasets. Additionally, the financial costs associated with building, maintaining, and growing self-managed, on premises data warehouses are very high.

In order to manage costs, keep ETL complexity low, and deliver acceptable performance, the customer had to constantly trade-off what data to load into the data warehouse and what data to archive in storage. 

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Technical Challenge

The customer’s data pipeline followed a collect, store, process/analyze, and consume model, leveraging multiple AWS services. Their data lake was created in an Amazon S3 bucket, and the data lake's stored data can be queried using dbt, utilizing AWS Glue Data Catalog Databases and Crawlers.We recommended Amazon Redshift and Redshift Spectrum to build their data warehouse. After mapping the data with Redshift Spectrum, Amazon Redshift processes the data to Redshift tables. Data is then visualized and consumed by users through Amazon QuickSight.

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AWS Services Adopted for this Solution

• Amazon S3, for data lakes
• AWS Glue, as a data datalog
• Amazon Redshift, as a data warehouse
• Amazon Quicksight, for data visualization

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Data Processing Solution for Healthcare Organization

Amazon Redshift's scalability and flexibility make it easy to manage expanding data volumes effortlessly. With Redshift, customers can reduce their total cost of ownership (TCO) associated with database environments. Redshift also provides a centralized and secure data storage solution, that also automatically patches and backs up the data warehouse, storing backups for a user-defined retention period. This replication and continuous backups enhance availability and improve data durability, and can automatically recover from component and node failures.

Amazon Redshift’s parallel processing and compression capabilities accelerate command execution, enabling it to operate on billions of rows simultaneously. Redshift Spectrum integrates seamlessly with other AWS services (such as Glue), making it easy to build end-to-end data pipelines. This ensures that data is always up-to-date, accurate, and secure.

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“Before moving to Amazon Redshift, our engineering team was spending too much time managing our on-prem data warehouse. Now, we are saving so much time on data management, and our data analysis has improved significantly.”

‍- CIO, Healthcare Insurance Provider

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Data Processing Results

With Amazon Redshift and additional AWS services, the customer gained a centralized and secure data storage solution, and a streamlined data analysis process. The scalability and flexibility of Redshift empowered the customer to handle expanding data volumes seamlessly.

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Get started with Healthcare Data Processing

Take the first steps to improve your healthcare data processing to see increases in data security, analysis, and scalability. Contact Cloudtech today.

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Project Summary

Creating a Marketing website using ReactJS and AWS for the client to showcase what they do and how they do.
Feature enhancement in an existing web application where people with disabilities can request a communication facilitator or a support service provider and providers can accept a request and receive payment.

Problem Statement

The client divided the project into several MVPs.

As part of MVP-1, the client wanted to create a marketing website that is fast, secure, and allows people to understand what Mizaru is and how it can benefit them. They wanted a website that performs operations faster, is secure from the bots, and is cheaper to maintain.

MVP-2 involved enhancing the client’s existing web application, which was previously very basic. They wanted to implement features like admin dashboard management, QR code-based check-in and check-out of providers to provide service, etc.

In MVP-3 they wanted us to create a mobile application to perform the same functionality.

Our Solutions

1) We created a marketing website for the users using ReactJS. This provides us with a faster way to create and serve the application.
2) For deployment and maintenance, we used AWS. It reduced our cost and maintenance efforts.
3) For enhanced security from bots, we’ve implemented google ReCaptcha v3.
4) Once the user has a clear understanding, they are moved to a web app or a mobile App.
5) Through the web app customers (People with disability) can create a request based on their requirements (e.g. Need a communication facilitator or support service provider). Our application provides a way for people with disabilities to connect with service providers. This request will be visible to multiple service providers in the network and they can choose to accept or reject the request.
6) We integrated a payment gateway for processing the payment. Also, both customers and providers get notified of the multiple events. We created a dashboard for Admins to see the track of various requests and generate reports as per their needs.

Technologies

Express JS, React JS, Redux, AWS, GIT, Hubspot, Google Recaptcha v3

Success Metrics

1. Created and delivered marketing website within the given timeframe.
2. Created report generation feature for admin.
3. Implementation of QR code based check-in and check-out of provider.
4. Email reminders for customer and providers before service.

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