Sample GRPC service prepared for embedded devices & IoT where orchestration (like k8s) is not present.

Service is using etcd implementation of Raft algorithm (https://github.com/etcd-io/raft).

Prerequisites:

• Go 1.19
• GRPC for Go (check make install)
• Goreman

Scope:

• embedded service composed of N nodes

• each service is using Raft consensus algorithm to find the leader

• leader handles basic API operations using GRPC

Goals:

• check in details how Raft works

• check performance of such service

• check how resilient such service is and what's the impact of failures on service performance

Design is borrowed from raft example which is based on REST API

and fits GRPC needs perfectly too.

The service consists of three components:

• a raft-backed key-value store,
• a GRPC server
• a raft consensus server based on etcd's raft implementation.

The raft-backed key-value store is a key-value map that holds all committed key-values. The store bridges communication between the raft server and the GRPC server. Key-value updates are issued through the store to the raft server. The store updates its map once raft reports the updates are committed.

The GRPC server exposes the current raft consensus by accessing the raft-backed key-value store.

The raft server participates in consensus with its cluster peers. When the GRPC server submits a proposal, the raft server transmits the proposal to its peers. When raft reaches a consensus, the server publishes all committed updates over a commit channel. In our case, this commit channel is consumed by the key-value store.

• Consensus algorithms in theory & practice

• Raft visualisation

• Raft visualisation step-by-step

• Swarmkit - toolkit for service orchestration