100% Managed Wiki deployment using Microsoft Azure App Service (Docker-based) and Azure Database for PostgreSQL Servers.

In the ever-evolving landscape of cloud computing, the need for efficient, collaborative, and accessible document management systems is paramount. As a Cloud Engineer based in the UK, I recently undertook a project that epitomises this need — deploying a fully managed Wiki using Microsoft Azure’s App Service and Azure Database for PostgreSQL Servers. This blog post details my journey through this project, highlighting the challenges, solutions, and technologies that played a pivotal role.

Project Overview

The primary objective was transitioning from traditional, local storage of critical documents to a cloud-based solution. This shift was aimed at enhancing document accessibility, consistency, and collaboration within the team. The Wiki, designed to be 100% web-based, was a central repository for all vital documents, including Runbooks and Knowledge Bases (KBs).

Choice of Technologies

Two Azure services were instrumental in this deployment:

1. Azure Database for PostgreSQL Servers: This fully managed database service was chosen for its robustness, scalability, and compatibility with open-source PostgreSQL.
2. Azure App Service (Docker-based): Leveraging the power of Docker containers, Azure App Service provided the flexibility and ease of deploying and managing the Wiki application.

Deployment Strategy

Azure Database for PostgreSQL Servers

• Initial Setup: Configured the PostgreSQL server, ensuring optimised performance settings tailored to the Wiki’s requirements.
• Security Measures: Implemented strict firewall rules and used Azure’s built-in security features to safeguard data.
• Continuous Backups: Enabled point-in-time recovery, ensuring data integrity and minimal downtime in case of any issues.

Azure App Service

• Docker Integration: Created a custom Docker image for the Wiki application, ensuring a seamless deployment process.
• App Service Configuration: Fine-tuned the App Service plan to balance performance and cost, selecting the appropriate tier.
• Continuous Deployment: Set up CI/CD pipelines for automatic updates, leveraging Azure DevOps for streamlined operations.

Challenges and Solutions

Scalability

• Challenge: Anticipating varying loads and ensuring the Wiki remains responsive under different usage scenarios.
• Solution: Utilised Azure’s auto-scaling capabilities, allowing the service to adapt to load changes dynamically.

Security

• Challenge: Ensuring data security and compliance with organisational policies.
• Solution: Implemented Azure’s Advanced Threat Protection for proactive threat mitigation and encrypted data at rest and in transit.

Collaboration

• Challenge: Enabling real-time collaboration without compromising performance.
• Solution: Integrated Azure’s cache services to enhance performance, ensuring quick access and updates to the Wiki.

Conclusion

This project was a testament to the capabilities of Azure services in deploying a fully managed, scalable, and secure web-based Wiki. The journey from conceptualisation to implementation was filled with learning opportunities and challenges, all contributing to successfully deploying a solution that met and exceeded the team’s expectations. As I continue my path towards becoming a seasoned Cloud, Platform, or DevOps Engineer, projects like these offer invaluable experiences, cementing my skills and knowledge in the cloud domain.