micro-os

README

Micro OS

Micro OS is a microservice operating system

Micro OS is useful where you want to build reliable globally distributed systems at scale. In a world of infinite compute and billions of devices it's still difficult to build products that are highly available and that cope with demand. Micro OS attempts to solve these problems by providing an environment for distributed applications.

Use the micro/go-os client library to simplify use of Micro OS.

Note: This is still a work in progress

Features

Repo	Description
auth	Authentication and authorization (Oauth2)
config	Dynamic configuration
db	Database proxy
discovery	Discovery read cache
event	Event aggregation
kv	Key-Value service
log	TODO: structured log aggregation
metrics	TODO: analytics aggregation
monitor	Monitoring for Status, Stats and Healthchecks
router	Global service load balancing
sync	TODO: distributed consensus
trace	Distributed tracing

How does it work?

Go OS is a client library which lets you leverage the features of Micro OS. Each package connects to a backend Micro OS service which handles that feature. Packages can be used independently or integrated using go-micro client and handler wrappers.

Auth

Auth addresses authentication and authorization of services and users. The default implementation is Oauth2 with an additional policy engine coming soon. This is the best way to authenticate users and service to service calls using a centralised authority. Security is a first class citizen in a microservice operating system.

Config

Config implements an interface for dynamic configuration. The config can be hierarchically loaded and merged from multiple sources e.g file, url, config service. It can and should also be namespaced so that environment specific config is loaded when running in dev, staging or production. The config interface is useful for business level configuration required by your services. It can be reloaded without needing to restart a service.

DB

The DB interface is an experiment CRUD interface to simplify database access and management. The amount of CRUD boilerplate written and rewritten in a microservice world is immense. By offloading this to a backend service and using RPC, we eliminate much of that and speed up development. The Micro OS implementation includes pluggable backends such as mysql, cassandra, elasticsearch and utilises the registry to lookup which nodes databases are assigned to.

Discovery

Discovery provides a high level service discovery interface on top of the go-micro registry. It utilises the watcher to locally cache service records and also heartbeats to a discovery service. It's akin to the Netflix Eureka 2.0 architecture whereby we split the read and write layers of discovery into separate services.

Event

The event package provides a way to send events and essentially create an event stream and record of all that's happening in your microservice environment. On the backend an event service aggregates the records and allows you to subscribe to a specific set of events. An event driven architecture is a powerful concept in a microservice environment and must be addressed adequately. At scale it's essential for correlating events within a distributed system e.g provisioning of new services, change of dynamic config, logouts for customers, tracking notifications, alerts.

KV

KV represents a simple distributed key-value interface. It's useful for sharing small fast access bits of data amonst instances of a service. We provide three implementations currently. Memcached, redis and a consistently hashed in distributed in memory system.

Log

Log provides a structured logging interface which allows log messages to be tagged with key-value pairs. The default output plugin is file which allows many centralised logging systems to be used such as the ELK stack.

Monitor

The monitor provides a way to publish Status, Stats and Healtchecks to a monitoring service. Healthchecks are user defined checks that may be critical to a service e.g can access database, can sync from s3, etc. Monitoring in a distributed system is fundamentally different from the classic LAMP stack. In the old ways pings and tcp checks were regarded as enough, in a distributed system we require much more fine grained metrics and a monitoring service which can make sense of what failure means in this world.

Metrics

Metrics is an interface for instrumentation. We regard metrics as a superior form of observability in a distributed system over logging. Instrumentation is a great way to graph historic and realtime data which can be correlated and immediately understood. The metrics interface provides a way to create counters, gauges and histograms. We currently implement the statsd interface and offload to telegraf which provides an augmented statsd interface with labels.

Router

The router builds on the registry and selector to provide rate limiting, circuit breaking and global service load balancing. It implements the selector interface. Stats are recorded for every request and periodically published. A centralised routing service aggregates these metrics from all services in the environment and makes decisions about how to route requests. The routing service is not a proxy. Proxies are a weak form of load balancing, we prefer smart clients which retrieve a list of nodes from the router and make direct connections, this means if the routing service dies or misbehaves, clients can continue to make request independently.

Sync

Sync is an interface for distributed synchronisation. This provides an easy way to do leadership election and locking to serialise access to a resource. We expect there to be multiple copies of a service running to provide fault tolerance and scalability but it makes it much harder to deal with transactions or serialising access. The sync package provides a way to regain some of these semantics.

Trace

Trace is a client side interface for distributed tracing e.g dapper, zipkin, appdash. In a microservice world, a single request may fan out to 20-30 services. Failure may be non deterministic and difficult to track. Distributed tracing is a way of tracking the lifetime of a request. The interface utilises client and server wrappers to simplify using tracing.