Microservice for Video Processing:
Video Processing.
Create a docker image/container for video processing.
We were thinking of using this software below and modify to achieve results.
singhkays/ffmpeg-av1-libaom
We need a microservice for video processing to handle tasks like optimization, watermarking, transcoding, resolution adjustments, frame rate adjustment, color correction and enhancement, thumbnails generation, content moderation, aspect ratio.
encoding in H.264 High Profile and VP9 (profile 0) AV1 encoding. Thanks.
More Details:
Technical Specification for Developing a Microservice for File Upload and Processing via REST API
Project Description
The microservice is designed for scalable processing of files (photos and videos). It should handle requests, distribute tasks among processing instances, and ensure the execution of task chains to achieve the desired result. The output should be a Docker file with the complete instance configuration and a description for deployment. Each instance must be configurable and extensible through configuration files.
Key Requirements
1. Architecture
Scalability: Achieved through container replication and load distribution. Each container must be independent. Shared dependencies like KeyDB or databases (e.g., MySQL, PostgreSQL) are allowed, but instances should not interfere with one another.
Task Distribution: A central service should efficiently allocate tasks among active instances using a load balancer. The service must include endpoints to determine the current load and readiness of instances.
Extensibility: Adding new processors should be as simple as defining new classes in the configuration. The sequence of task execution should also be adjustable through configuration files.
2. API
2.1 Endpoints
File Upload: POST /upload
Task Status: GET /status/{task_id}
Supported Presets: GET /presets
3. File Processing
General Requirements:
File processing must be executed as a chain of tasks.
Each processing step must be logged.
Presets and Configurations: Examples include limiting the file size to 100 MB, converting to the MP4 format, and more.
Processor Configuration: New processing steps can be added by updating the configuration files.
4. Integration with Wasabi
Upload processed files to the specified bucket.
Generate and provide a link to access the results.
5. Logging and Monitoring
Log task statuses and processing steps.
Monitor instance states (activity, load).
Send notifications in case of errors.
6. Security
API token-based authorization.
Validation of all input data.
Non-Functional Requirements
1. Fault Tolerance
Implement task restarts in case of a processing instance failure.
2. Technology Stack
Programming language: Any, with criteria focused on simplicity, processing speed, and resource efficiency.
Task Queue: Open-source solutions like RabbitMQ or Kafka.
Configuration Storage: JSON, .env files, or ENV definitions via YAML.
3. Documentation
Provide a Swagger/OpenAPI specification for all endpoints.
4. Testing
Include unit tests for key components.
Conduct load testing to evaluate scalability.
Development Stages
1. Design the architecture.
2. Develop the API and task distribution system.
3. Implement processors and configurations.
4. Integrate with Wasabi.
5. Set up logging and monitoring.
6. Conduct testing and optimization.
7. Deploy the system and deliver documentation.
Thanks. The Presser Team.
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10 days1000 USD
103 10 days1000 USDHello. Ready to start the project. All requirements are clear
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30 days1000 USD
8867 60 0 1 30 days1000 USDHello,
I am ready to take on this project.
I have experience in implementing similar projects and write in Python. I currently hold 3rd place on the platform.
I will implement all the required features: video processing using FFmpeg (H.264, VP9, AV1), thumbnail generation, resolution adjustment, Wasabi integration, and creating a scalable architecture. I guarantee secure authorization, stable task processing, and comprehensive documentation (including Swagger).
Here is my portfolio:
Freelancehunt
Feel free to reach out to discuss the details, and I’ll get started right away.
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10 days1000 USD
1341 23 0 10 days1000 USDGood afternoon,
I will use the Go programming language to implement the microservice. I have previous experience creating microservices, so I will complete the task quickly and efficiently. Let’s get in touch to discuss the details.
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10 days1000 USD
166 10 days1000 USDHi, Jean Claude Jc Cournoyer.
My name is William Martin, and I am a full-stack developer with experience across a range of technologies, including DevOps, React, Next.js, Express, Python, Artificial Intelligence (AI), and Computer Vision (CV). I’ve worked on projects that required building scalable architectures, efficient APIs, and seamless integrations. I am confident in delivering an efficient solution tailored to your needs.
For the backend, I propose using Python, combined with either FastAPI or Flask. Python’s extensive ecosystem provides powerful libraries for video processing (such as FFmpeg, OpenCV, and MoviePy) and AI tools (TensorFlow, PyTorch), making it ideal for this microservice.
To boost efficiency, we can integrate AI solutions for tasks like content moderation, video enhancement, and intelligent automation. Leveraging OpenAI APIs or custom AI models will bring advanced capabilities to the system.
Based on my experience, this technology stack is reliable, scalable, and well-suited for building a microservice with complex processing tasks.
I think we can use Docker, Nginx, Consul and Kubernetes for building microservice architecture.
… For logging and monitoring, I suggest two potential options:
ELK Stack (Elasticsearch, Logstash, Kibana)
Prometheus + Grafana or Loki + Promtail + Grafana
The database can be managed using Supabase, a scalable platform offering simple integration and real-time features. For authentication, JWT (JSON Web Tokens) is ideal for ensuring secure and stateless user sessions.
The frontend, if required, can be developed with React, providing a responsive and user-friendly interface for interacting with the microservice.
In terms of deadline, I can develop the entire system at most 5~6 days, but after that, I have to fix bugs and improve the performance based on your feedback. Also, I would make a documentation for future updating. So in total, it can take 10 days.
With my experience in Python, containerized architectures, video processing, and AI-driven solutions, I am confident in my ability to deliver a high-quality product.
I hope you can make it.
I am looking forward to hearing from you.
Best Regards.
William.
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