How to build a simple HTTP server with Sogou Workflow?

Use WFHttpServer with a callback function, as shown in the README example: instantiate the server, define the response in the task, and start on a port. The tutorial covers more advanced features like proxy servers and file handling.

Sogou Workflow vs Boost.Asio for C++ async networking?

Sogou Workflow offers a higher-level, unified framework integrating networking and computing with built-in protocols and structured concurrency. Boost.Asio is lower-level and more flexible for custom implementations but requires more boilerplate. Workflow is better for end-to-end task scheduling in backend services.

Does Sogou Workflow support real-time protocols like WebSocket?

No, built-in protocols do not include WebSocket; you would need to implement it as a custom protocol using the framework's serialization/deserialization functions. The srpc project based on Workflow might offer alternatives for RPC-like use cases.

How to handle errors in asynchronous tasks?

Errors are managed through task callbacks and the framework's error handling mechanisms, detailed in the 'about-error' tutorial. Each task provides error codes and states, allowing centralized error logging and recovery in series contexts.

Is Sogou Workflow suitable for microservices with load balancing?

Yes, it has built-in service governance and load balancing features, making it ideal for microservice architectures. The upstream management and configuration tutorials explain how to distribute requests across multiple service instances.

Can I use it for compute-intensive parallel tasks without networking?

Yes, computing tasks are first-class citizens; you can create parallel workflows using the algorithm factory (e.g., sort, merge) or custom compute tasks, and integrate them with networking or file IO as needed.

Sogou Workflow — C++ Parallel Computing Framework

What is Sogou Workflow?

Sogou C++ Workflow is a C++ parallel computing and asynchronous networking framework used to build high-performance backend services. It handles networking, computation, and file IO tasks within unified workflows, supporting protocols like HTTP, Redis, MySQL, and Kafka. The framework is designed to manage complex asynchronous operations and concurrency structures efficiently.

Target Audience

C++ backend developers building high-concurrency online services, microservice architectures, or custom RPC systems. It is particularly suited for teams requiring enterprise-grade performance and structured asynchronous programming.

Value Proposition

Developers choose Sogou C++ Workflow for its proven scalability in production (handling over 10 billion daily requests), its integrated approach to networking and computing tasks, and its lightweight design without dependencies on boost or asio. The framework's structured concurrency model and simplified memory management reduce the complexity of asynchronous C++ development.

C++ Parallel Computing and Asynchronous Networking Framework

Use Cases

Best For

Building HTTP servers and asynchronous clients for multiple protocols
Implementing custom network protocols and RPC systems
Creating parallel computing workflows with DAG structures
Developing high-concurrency backend services with complex networking and computing interactions
Constructing microservice architectures with built-in service governance
Performing asynchronous file IO operations on Linux systems

Not Ideal For

Projects prioritizing rapid prototyping in higher-level languages like Python or Go over C++ performance
Teams preferring synchronous I/O models or simpler concurrency without explicit callback mechanisms
Environments requiring seamless cross-platform development, as Windows support is maintained in a separate branch
Applications needing out-of-the-box support for protocols like WebSocket or gRPC without custom implementation

Pros & Cons

Pros

Enterprise-Proven Scalability

Powers Sogou's core services handling over 10 billion daily requests, demonstrating reliability in high-concurrency production environments as stated in the README.

Unified Async Framework

Integrates networking, computation, and file IO tasks into a single workflow with support for series, parallel, and DAG structures, simplifying complex asynchronous programming.

Lightweight No-Dependency Design

Uses C++11 standard without relying on boost or asio, making it self-contained and easier to integrate, as highlighted in the compiling requirements.

Structured Concurrency Model

Abstracts tasks into five types with factory generation and explicit lifecycle management, reducing callback depth and memory leaks without std::shared_ptr.

Cons

Protocol Coverage Gaps

Built-in protocols are limited to HTTP, Redis, MySQL, and Kafka; common protocols like WebSocket or gRPC require custom implementation or external projects like srpc.

Windows Branch Fragmentation

Windows support is in a separate branch using iocp, which may lead to inconsistent updates, maintenance overhead, and potential feature lag compared to the main Linux/macOS branch.

Additional Dependency Hassles

Kafka protocol requires installing compression libraries like lz4, zstd, and snappy, adding setup complexity beyond the core framework.

Frequently Asked Questions

What is Sogou Workflow?

Target Audience

Value Proposition

Use Cases

Best For

Building HTTP servers and asynchronous clients for multiple protocols
Implementing custom network protocols and RPC systems
Creating parallel computing workflows with DAG structures
Developing high-concurrency backend services with complex networking and computing interactions
Constructing microservice architectures with built-in service governance
Performing asynchronous file IO operations on Linux systems

Not Ideal For

Projects prioritizing rapid prototyping in higher-level languages like Python or Go over C++ performance
Teams preferring synchronous I/O models or simpler concurrency without explicit callback mechanisms
Environments requiring seamless cross-platform development, as Windows support is maintained in a separate branch
Applications needing out-of-the-box support for protocols like WebSocket or gRPC without custom implementation

Pros & Cons

Pros

Enterprise-Proven Scalability

Powers Sogou's core services handling over 10 billion daily requests, demonstrating reliability in high-concurrency production environments as stated in the README.

Unified Async Framework

Integrates networking, computation, and file IO tasks into a single workflow with support for series, parallel, and DAG structures, simplifying complex asynchronous programming.

Lightweight No-Dependency Design

Uses C++11 standard without relying on boost or asio, making it self-contained and easier to integrate, as highlighted in the compiling requirements.

Structured Concurrency Model

Abstracts tasks into five types with factory generation and explicit lifecycle management, reducing callback depth and memory leaks without std::shared_ptr.

Cons

Protocol Coverage Gaps

Built-in protocols are limited to HTTP, Redis, MySQL, and Kafka; common protocols like WebSocket or gRPC require custom implementation or external projects like srpc.

Windows Branch Fragmentation

Windows support is in a separate branch using iocp, which may lead to inconsistent updates, maintenance overhead, and potential feature lag compared to the main Linux/macOS branch.

Additional Dependency Hassles

Kafka protocol requires installing compression libraries like lz4, zstd, and snappy, adding setup complexity beyond the core framework.

Frequently Asked Questions

Sogou Workflow

What is Sogou Workflow?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

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Sogou Workflow

What is Sogou Workflow?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

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