Skip to content

🎈 lightweight message broker for learning purposes

Notifications You must be signed in to change notification settings

momtr/schnedale

Folders and files

NameName
Last commit message
Last commit date

Latest commit

Β 

History

1 Commit
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 

Repository files navigation

🎈 schnedale

the lightweight message broker

Connection

  • port: 2227

Protocol

The SCHNEDALE application-layer protocol is stateless and works on top of a TCP connection. It is designed to work with commands rather than heavyweight requests and responses.

Basic terms:

  • pipeline: a channel/queue where data is transfered from source to destination
  • subscribe: clients can subscribe to pipelines to receive all notifications published to this pipeline

Client calls

  • SUBS <pipeline>:<pipeline_tag> - subscribes to a pipeline (so that the client receives all notifications on that pipeline)
  • PUSH <pipeline>:<pipeline_tag> <base64_encoded_data> [<storage_flag>] - push a message to a pipeline (if the pipeline does not exist, it will be created)
  • HEALTH - do a health check (the server will respond with ACK)

Server calls

  • ACK - sent to the client when the server acknowledges a message
  • ERR <error_code> <error_message>[:<indicator>] - if an error occurs, the server will send an error message which has an unique error_code
  • NOTI Message(source=<source-ip>:<source-port>,pipeline=<pipeline>,data=<base64_encoded_data>) - the message that is received when data is published to a pipeline

Message:

  • source: the unique identifier of the client who sent the message
  • pipeline: the name of the message's pipeline
  • data: base64 encoded data where '=' is replaced by '*'

Client-SDK

Functionality

Message broker

Schnedale can act as a message broker, distributing messages between individual services.

Raw & structured data store

Schnedale stores data:

  • if the data_flag is set to 1 in the PUSH call
  • if it is uploaded via the DATAcall

Data is organized, so that it is accessible to analytics applications utilizing the Schnedale Sandbox. Machine learning models can be created in the Schnedale Sandbox and they have access to all stored data.

Data organization:

  • in pipelines
  • pipeline tags
  • data format (TEXT, JSON, XML, CSV, XLSX, PHOTO, FILE)

About

🎈 lightweight message broker for learning purposes

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published