Technical Proposal for Serverless Compute Platform

Introduction

In today's rapidly evolving technological landscape, businesses need to innovate swiftly and efficiently. To stay competitive, companies must leverage advanced computing platforms that provide flexibility, scalability, and ease of use. Our proposed project aims to build a next-generation backend compute platform designed to address these needs by offering a serverless architecture that insulates developers from the complexities of infrastructure management while being cloud agnostic and highly scalable.

This platform will empower developers to focus on writing and deploying their code without worrying about the underlying infrastructure. By utilizing an advanced language model (LLM), the platform will enable developers to describe functions in natural language, which the LLM will then translate into executable code. This innovative approach significantly reduces the development cycle and allows for rapid prototyping and deployment of new features.

The value propositions of this project are multifaceted:

1. Infrastructure Agnosticism: The platform's ability to run seamlessly on AWS, Azure, GCP, or on-premises environments ensures that businesses are not locked into a single cloud provider. This flexibility allows organizations to choose the best environment for their needs, optimizing costs and performance.

2. Automatic Scaling: With built-in auto-scaling capabilities, the platform adjusts resources dynamically based on demand, ensuring optimal performance and cost-efficiency. This means businesses can handle fluctuating workloads without manual intervention or over-provisioning resources.

3. Developer Empowerment: By abstracting away the complexities of web networking protocols and infrastructure management, the platform allows developers to concentrate on what they do best—writing code. The provision of SDKs and a developer-friendly interface further enhances productivity and reduces time-to-market.

4. Enhanced Monitoring and Management: The inclusion of a web-based portal provides real-time insights into the platform's performance and resource usage. Additionally, APIs and hooks facilitate seamless integration with third-party tools for logging, alerts, and other essential functions, ensuring comprehensive monitoring and management capabilities.

5. Innovative Code Generation: The platform's ability to generate and deploy code from natural language descriptions via an LLM represents a significant leap forward in software development. This feature not only accelerates development but also democratizes coding, making it accessible to a broader range of users.

By delivering a robust, scalable, and user-friendly compute platform, this project aims to revolutionize the way businesses develop and deploy software. It aligns with the strategic goals of modern enterprises to innovate rapidly, reduce operational overhead, and maximize resource efficiency.

Project Mission Statement

The objective is to build a backend compute platform with the following attributes:

• Serverless Architecture: Completely insulates the developer from managing infrastructure.
• Cloud Agnostic: Runs equally well on AWS, Azure, GCP, or on-prem.
• Automated Code Generation: Software functions are described as text, and an LLM will write and deploy the code.
• Scalability: Automatically scales with horizontal scaling only limited by the available resources.

Secondary aspects include:

• Developer Friendly: Developers can write and deploy their own functions following the appropriate paradigm.
• Web-based Portal: For monitoring and managing resources.
• API and Hooks: Provides APIs and hooks for integrating with third-party tools for logging, alerts, etc.

Scope of Work

Use Cases

1. Function Deployment:

   • Developers describe functions in natural language.
   • LLM generates and deploys the functions.
   • Developers can also manually deploy their own functions.

2. Function Execution:

   • Functions are called with 0 to n parameters and return values or objects.
   • Functions are organized into namespaces.

3. Resource Management:

   • Controller service manages function availability.
   • Automatic scaling and load balancing.

4. Monitoring and Management:

   • Web-based portal for real-time monitoring.
   • APIs and hooks for integration with logging and alerting tools.

5. Developer Interaction:

   • SDKs for handling function calls and responses.
   • Unit tests with mock data for function verification.

Technical Requirements

Core Components

1. Function Handling:

   • Functions written as code and called with parameters.
   • Stateless execution for scalability.

2. Controller Service:

   • Tracks available functions.
   • Manages spinning up and shutting down function instances.
   • Routes all function calls.
   • Scalable by spinning up additional controller instances as needed.

3. SDKs:

   • Abstracts web networking protocols.
   • Handles calling functions, receiving calls, returning values, and receiving results.

4. Web-based Portal:

   • Interface for monitoring and managing platform resources.
   • Displays real-time metrics and logs.

5. APIs and Hooks:

   • Integrates with third-party tools for logging and alerts.
   • Provides interfaces for external systems to interact with the platform.

Infrastructure

1. Containerization:

   • Platform runs in containers.
   • Initial container acts as the hub, starting the controller and loading "always on" functions.

2. Catalog Service:

   • Tracks running containers and deployed functions.
   • Possible implementation using Redis or a private blockchain.

Deployment and Scaling

1. Initial Startup:

   • Starts with a single container running the controller.
   • Loads initial functions and scales up as needed.

2. Function Scaling:

   • New containers are spun up as functions are needed.
   • Controller manages resource allocation and de-allocation.

3. Horizontal Scaling:

   • Controller can scale horizontally by spinning up additional instances.
   • Ensures high availability and load balancing.

Description of the Work

1. Platform Design

   • Define architecture and core components.
   • Design SDKs and controller service.

2. Core Development

   • Implement the controller service.
   • Develop SDKs for function interaction.
   • Create the initial set of APIs and hooks.

3. Containerization and Deployment

   • Containerize the platform.
   • Develop the catalog service for tracking containers and functions.

4. Automated Code Generation

   • Integrate LLM for generating and deploying functions.
   • Develop natural language interface for function descriptions.

5. Web Portal Development

   • Implement the web-based portal for monitoring and management.
   • Integrate real-time metrics and logging.

6. Testing and Optimization

   • Conduct unit tests with mock data.
   • Optimize performance and scalability.

7. Documentation and Training

   • Create comprehensive documentation for developers.
   • Provide training and support for using the platform.

Repository Structure

Given the team structure and projects they are working on, it's important to organize the repositories to minimize the risk of merge conflicts while maintaining logical groupings and clear boundaries between different components. Here's an updated proposal for a hybrid repository structure that balances these concerns:

1. Monorepo for Core Components

Repository: osiris-core Structure:

osiris-core/
│
├── controller/
│   ├── core/ (Team 1)
│   │   ├── src/
│   │   ├── tests/
│   │   └── Dockerfile
│   ├── scalability/ (Team 2)
│   │   ├── src/
│   │   ├── tests/
│   │   └── Dockerfile
│   └── README.md
│
├── cli/
│   ├── core/ (Team 3)
│   │   ├── src/
│   │   ├── tests/
│   │   └── Dockerfile
│   ├── user-management/ (Team 4)
│   │   ├── src/
│   │   ├── tests/
│   │   └── Dockerfile
│   └── README.md
│
├── client-sdk/
│   ├── core/ (Team 5)
│   │   ├── src/
│   │   ├── tests/
│   │   └── Dockerfile
│   ├── advanced-features/ (Team 6)
│   │   ├── src/
│   │   ├── tests/
│   │   └── Dockerfile
│   └── README.md
│
├── function-sdk/ (Team 7)
│   ├── core/
│   │   ├── src/
│   │   ├── tests/
│   │   └── Dockerfile
│   ├── performance-optimization/
│   │   ├── src/
│   │   ├── tests/
│   │   └── Dockerfile
│   └── README.md
│
└── README.md

2. Separate Repositories for Infrastructure and Additional Scope Components

Repository: osiris-infrastructure Structure:

osiris-infrastructure/
│
├── docker/ (Team 8)
│   ├── core/
│   ├── management/
│   └── README.md
│
├── terraform/ (Team 9)
│   ├── scripts/
│   └── README.md
│
└── README.md

Repository: osiris-function-library Structure:

osiris-function-library/
│
├── core-management/ (Team 10)
│   ├── src/
│   ├── tests/
│   └── Dockerfile
│
├── versioning-rollback/ (Team 11)
│   ├── src/
│   ├── tests/
│   └── Dockerfile
│
└── README.md

Repository: osiris-index-ledger Structure:

osiris-index-ledger/
│
├── core-implementation/ (Team 12)
│   ├── src/
│   ├── tests/
│   └── Dockerfile
│
├── synchronization-consistency/ (Team 13)
│   ├── src/
│   ├── tests/
│   └── Dockerfile
│
└── README.md

Repository: osiris-admin-portal Structure:

osiris-admin-portal/
│
├── core-features/ (Team 14)
│   ├── src/
│   ├── tests/
│   └── Dockerfile
│
├── advanced-features/
│   ├── src/
│   ├── tests/
│   └── Dockerfile
│
└── README.md

Repository: osiris-code-generation Structure:

osiris-code-generation/ (Team 15)
├── core/
│   ├── src/
│   ├── tests/
│   └── Dockerfile
├── advanced/
│   ├── src/
│   ├── tests/
│   └── Dockerfile
└── README.md

Repository: osiris-logging-monitoring Structure:

osiris-logging-monitoring/
│
├── logging-service/
│   ├── src/
│   ├── tests/
│   └── Dockerfile
│
├── monitoring-alerts/
│   ├── src/
│   ├── tests/
│   └── Dockerfile
│
└── README.md

Repository: osiris-security-compliance Structure:

osiris-security-compliance/
│
├── auth-authorization/
│   ├── src/
│   ├── tests/
│   └── Dockerfile
│
├── compliance-auditing/
│   ├── src/
│   ├── tests/
│   └── Dockerfile
│
└── README.md

Repository: osiris-integration-testing Structure:

osiris-integration-testing/
│
├── testing-framework/
│   ├── src/
│   ├── tests/
│   └── Dockerfile
│
├── automated-ci-cd/
│   ├── src/
│   ├── tests/
│   └── Dockerfile
│
└── README.md

Repository: osiris-documentation-support Structure:

osiris-documentation-support/
│
├── documentation-guides/
│   ├── src/
│   ├── tests/
│   └── Dockerfile
│
├── support-tools/
│   ├── src/
│   ├── tests/
│   └── Dockerfile
│
└── README.md

Summary

By adopting this hybrid repository structure, we can minimize merge conflicts and ensure that each team has clear boundaries and responsibilities:

• Monorepo for Core Components: This allows for efficient management of interdependent components, ensuring consistency and simplifying cross-cutting concerns.
• Separate Repositories for Additional Scope Components: These repositories allow for focused development and testing of specific subsystems, reducing the risk of conflicts and enabling independent progress.
• Modular Structure within Repositories: Dividing each repository into smaller, focused sub-projects allows for clear separation of responsibilities and minimizes the risk of merge conflicts even within larger repositories.

This approach should help streamline development, improve collaboration, and ensure that the Osiris platform is built efficiently and effectively within the eight-week timeframe.

Further Reading

How functions work.

Authenticating developers.

Managing hardware.

Command Line Interface.

Network Communication

Architecture

Interfaces

Tasks for Teams