Introduction
Hi, fellow engineers! Paul here, I have a solid intrigued in backend advancement, and I fair ran into a few issue while overseeing databases in a microservices architecture and also I'm energized to be a portion of the HNG Internship program. I'll clarify the issue, the activities I took to resolve it, and the reasons I'm excited to begin this internship with HNG in this post.
The Problem
I was working on a project, a number of weeks back that called for efficient database administration management among a few microservices. Guaranteeing data consistency, high accessibility, and scalability without presenting a single point of disappointment was a difficulty. The prerequisite to viably oversee and manage heavy traffic and server requests at once made this issue more awful.
Step-by-Step Solution
Step 1: Choosing the Proper Database Technique
The primary step was to choose a fitting database technique. Few of the strategies, was to choose either between:
Database per Service: Where each microservice has its own implemented database.
Shared Database: One database is utilized by all available microservices.
In arrange to ensure loose coupling and free microservice scalability, I opt-in the "Database per Service" approach.
Step 2: High Availability
I configured database replication and utilized a low memory database framework (redis) to form beyond any doubt that resources that are cached are gotten more rapidly in order to ensure high accessibility. Redundancy was offered by this implementation, which too decreased downtime within the event of hardware breakdowns or maintenance.
Step 3: Data Consistency
It is essential to keep data consistent across all services. I read an article on microservices.io that inspired me to handle transactions using the SAGA pattern. This helps my case with respect to the inconsistent data.
Step 4: Optimizing Database Performance
Optimizing performance was very crucial for overseeing heavy traffic. I utilized a number of strategies:
- Indexing: Utilizing the right index help to improve the query performance. O boy the query was faster with indexing.
- Caching: To minimize database hits, Redis was used to cache regularly accessed data.
The Outcome
The result was a strong and proficient database administration framework that ensured data consistency, high accessibility, and scalability. The "Database per Service", combined with the SAGA pattern and performance optimization methods, given a strong arrangement for overseeing databases in a microservices architecture.
HNG Internship
The HNG Internship could be an incredible opportunity to memorize, develop, and collaborate with gifted people. I am enthusiastic to require on unused challenges, construct inventive arrangements, and contribute to energizing ventures. The organized learning environment and mentorship at HNG will without a doubt quicken my development as a backend engineer.
Are you interested in learning more about the HNG 11 Bootcamp and what HNG offers, check out their official pages, internship page and premium services.
Conclusion
Solving complex backend issue is continuously compensate.
I'm thrilled to set out on this journey with the HNG 11 Internship and see forward to the challenges and learning openings ahead. Thank you for reading, and happy coding !.
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