Azure-Based Scalable Trading Platform Deployment

Sahil Patil

Completed work

DevOps Engineer

Azure

Kubernetes

Terraform

Azure-Based Scalable Trading Platform Deployment

Overview

This project involves the deployment of a scalable trading platform on Microsoft Azure. The goal is to ensure high availability, performance, and security for trading operations while optimizing costs and automating infrastructure management. The platform is deployed using Azure Kubernetes Service (AKS), with continuous integration and continuous deployment (CI/CD) pipelines, enhanced security measures, monitoring, and observability using industry-standard tools.

🚀 Key Features

📦 Infrastructure Setup

Terraform was used for automating the provisioning of Azure infrastructure, ensuring reproducibility and version control.

The application was deployed on Azure Kubernetes Service (AKS) for efficient container orchestration, scaling based on load and demand.

Kubernetes deployment strategies, such as rolling updates, were used to minimize downtime during application updates.

🔒 Security Enhancements

API Gateway: Integrated API Gateway for secure API management, rate limiting, and monitoring API calls to protect the platform from malicious actors.

SonarQube Integration: Integrated SonarQube scanning in the CI/CD pipeline to ensure continuous code quality checks. This ensures the codebase remains maintainable and secure with every deployment.

🛠 CI/CD Automation

Created robust CI/CD pipelines using GitHub Actions to automate deployments for the frontend, backend, and APIs.

Automated infrastructure provisioning and application updates for consistent and repeatable deployment processes.

Additionally, CI/CD for APK deployment was established to facilitate seamless deployment of Android app versions via the pipeline.

🔍 Monitoring & Observability

Prometheus and Grafana were configured to provide real-time monitoring and visualizations of platform metrics, ensuring rapid response to issues.

Integrated alerting mechanisms to trigger alerts based on predefined thresholds (e.g., CPU usage, memory, or disk space).

DNS routing was optimized using Azure Traffic Manager to distribute traffic efficiently across various regions and ensure low-latency access to the platform.

📢 Deployment & Cost Optimization

Weekly deployment reports are generated to track successful deployments, application performance, and any potential failures.

Cost analysis reports are generated monthly to ensure financial visibility and optimize the resources being utilized.

Cloud cost optimization resulted in a 20% reduction through proactive resource management, right-sizing of infrastructure, and choosing cost-effective Azure services.

🔧 Prerequisites

Azure Subscription: Ensure you have access to an Azure account and subscription.

Terraform: Terraform CLI must be installed to provision the infrastructure.

Docker: Docker is needed for building the container images.

Kubernetes: Familiarity with Kubernetes and Azure Kubernetes Service (AKS) for container orchestration.

SonarQube: For static code analysis and quality gates.

Prometheus & Grafana: For monitoring and observability.

GitHub: For the CI/CD pipeline automation with GitHub Actions.

📑 Architecture

Azure Kubernetes Service (AKS): The application is deployed using Kubernetes, with AKS providing the underlying infrastructure.

API Gateway: Secures the platform APIs by managing and routing incoming API requests, ensuring proper security mechanisms such as rate limiting and traffic filtering.

CI/CD Pipeline: Automates the entire deployment workflow, including building, testing, and deploying code for frontend, backend, APIs, and mobile apps.

Monitoring: Prometheus collects system and application metrics, while Grafana dashboards visualize the data, making it easy to monitor health and performance.

Cost Optimization: Azure's cost management tools analyze monthly usage and expenses to guide resource optimization efforts.

🏗️ Infrastructure Setup with Terraform

Step 1: Provisioning Resources

Use Terraform to provision the necessary Azure resources. This includes:

AKS Cluster: For containerized application deployment.

Azure Container Registry (ACR): For storing container images.

Virtual Network (VNet): For secure networking between services.

API Gateway: For secure and centralized API management.

Terraform configuration files for infrastructure setup are located in the terraform/ directory.

Step 2: Running Terraform Scripts

Clone the repository:

Initialize Terraform:

Plan and apply the configuration:

Once the infrastructure is provisioned, AKS will be available for deploying applications.

🔧 CI/CD Pipeline Setup

Frontend & Backend CI/CD Pipelines

GitHub Actions is used for CI/CD pipeline automation. The workflows are defined in .github/workflows/ for both the frontend and backend.

Frontend Pipeline: Builds, tests, and deploys the frontend code to AKS.

Backend Pipeline: Handles backend builds, tests, and deployment to AKS.

APK Deployment Pipeline

The APK pipeline automates the deployment process for the Android application. This includes:

Building the APK: Using Android Build tools integrated with GitHub Actions.

Uploading to Google Play Store: Automating the upload process of APK to Google Play Store using Fastlane.

Example Workflow for Frontend (GitHub Actions)

name: Frontend CI/CD Pipeline

on:
  push:
    branches:
      - main

jobs:
  build:
    runs-on: ubuntu-latest

    steps:
      - name: Checkout repository
        uses: actions/checkout@v2

      - name: Set up Node.js
        uses: actions/setup-node@v2
        with:
          node-version: '16'

      - name: Install dependencies
        run: npm install

      - name: Build application
        run: npm run build

      - name: Deploy to AKS
        run: kubectl apply -f kubernetes/frontend-deployment.yaml

📊 Monitoring & Alerts

Prometheus Setup

Prometheus collects metrics from the AKS cluster, such as:

CPU and memory usage

Network I/O

Disk I/O

Grafana Setup

Grafana is used to visualize metrics collected by Prometheus. Key dashboards include:

System health

Resource usage

Traffic routing performance

Alerts are configured for various thresholds, including:

High CPU/Memory usage

Deployment failure alerts

Traffic anomalies

💡 Cost Optimization Strategy

Azure cost management tools were used to track monthly resource usage and spending, with the following optimizations made:

Right-sizing resources: Scaling down unused resources and adjusting instance sizes.

Auto-scaling: Implemented auto-scaling rules for AKS based on workload demand.

Resource tags: Tagging resources to better track and manage costs per department or project.

📝 Weekly Deployment Reports

Weekly deployment reports are generated using GitHub Actions and sent to the team. These reports include:

Summary of deployments.

Failed deployments and reasons.

Rollback actions (if any).

🎯 Next Steps

Continuous improvement: Further optimization of the CI/CD pipeline and monitoring tools.

Scalability: Testing the scalability of the application by simulating increased traffic and load.

Security: Conduct regular security audits and improve security practices.

📄 Conclusion

This scalable trading platform deployment on Azure provides a robust and secure solution for trading operations. By utilizing Terraform for infrastructure provisioning, CI/CD pipelines for automation, SonarQube for code quality, and Prometheus/Grafana for monitoring, the system is optimized for high availability, performance, and security.

With ongoing cost optimization and proactive resource management, the platform is designed to scale seamlessly while minimizing cloud costs.

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Completed work

Posted Mar 16, 2025

Deploying a scalable trading platform on Azure with Kubernetes, Terraform, CI/CD, API Gateway, monitoring, and cost optimization.

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Timeline

Dec 15, 2024 - May 15, 2025