Hey there! I'm thrilled to share my recent adventure in backend development with you. As someone who loves diving into complex problems, I decided to take on the task of building a distributed task scheduler app. This project pushed me to my limits but taught me so much along the way.
The Problem
So, what was the big idea? I wanted to create a distributed task scheduler that could handle both one-time and recurring tasks, making sure each task was executed within 10 seconds of its scheduled time. Sounds simple enough, right? Well, as I soon discovered, it was anything but straightforward.
The Journey
Step 1: Designing the Architecture
The first hurdle was designing the system's architecture. I opted for a microservices approach to keep things flexible and scalable. The key components were:
- Task API Service: This would handle all the task-related CRUD operations.
- Scheduler Service: Responsible for scheduling tasks accurately.
- Worker Nodes: These would actually execute the tasks.
- Database: For storing task data and logs.
- Message Queue: To keep communication flowing smoothly between services.
Step 2: Picking the Right Tools on GCP
I chose Google Cloud Platform (GCP) for this project and selected these services:
- Google Cloud Pub/Sub: To manage messaging between the different services.
- Google Cloud Firestore: As our database.
- Google Cloud Functions: For executing tasks.
- Google Cloud Scheduler: To manage the scheduling of recurring tasks.
Step 3: Building the Task API
With the architecture set, I dived into coding the Task API using TypeScript and Express.js. This service offered endpoints to create, update, and delete tasks, and it published task info to a Pub/Sub topic.
Step 4: Creating the Scheduler Service
This part was a real brain-teaser. The Scheduler Service needed to listen for new tasks, calculate when to run them, and schedule them precisely. For recurring tasks, I used Google Cloud Scheduler, which made managing and triggering recurring tasks straightforward and reliable.
Step 5: Setting Up the Worker Nodes
The Worker Nodes were essentially Google Cloud Functions that subscribed to Pub/Sub topics and executed the tasks when their time came. This setup ensured tasks were executed on time.
Step 6: Developing the GUI
Finally, I integrated a user-friendly GUI using React. This allowed users to manage tasks easily and see their status and execution logs in real-time.
The Hiccups
This journey wasn't without its challenges:
- Timely Execution: Getting tasks to run within that 10-second window was tricky. I had to fine-tune everything to minimize delays.
- Error Handling: Making the system resilient to failures involved implementing robust error handling and retry mechanisms.
- Scalability: Ensuring the system could handle a growing number of tasks required careful optimization.
Wrapping Up
Building this distributed task scheduler was a rollercoaster ride, but it was incredibly rewarding. I learned a ton about distributed systems and cloud services, and it reinforced the importance of planning and testing.
As I gear up for the HNG Internship, I'm excited to continue growing and learning. This program is an amazing opportunity to work on real-world projects and learn from experienced mentors. I can't wait to see where this journey takes me!
If you're curious about the HNG Internship, check out their website. And if you're looking to hire talented developers, head over to HNG Hire.
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