patron
Patron is a framework for creating microservices.
Patron
is french for template
or pattern
, but it means also boss
which we found out later (no pun intended).
The entry point of the framework is the Service
. The Service
uses Components
to handle the processing of sync and async requests. The Service
starts by default a HTTP Component
which hosts the debug, health and metric endpoints. Any other endpoints will be added to the default HTTP Component
as Routes
. The service set's up by default logging with zerolog
, tracing and metrics with jaeger
and prometheus
.
Patron
provides abstractions for the following functionality of the framework:
- service, which orchestrates everything
- components and processors, which provide a abstraction of adding processing functionality to the service
- asynchronous message processing (RabbitMQ, Kafka)
- synchronous processing (HTTP)
- metrics and tracing
- logging
Patron
provides same defaults for making the usage as simple as possible.
Service
The Service
has the role of glueing all of the above together, which are:
- setting up logging
- setting up termination by os signal
- starting and stopping components
- handling component errors
- setting up metrics and tracing
The service has some default settings which can be changed via environment variables:
- Service HTTP port, for setting the default HTTP components port to
50000
with PATRON_HTTP_DEFAULT_PORT
- Log level, for setting zerolog with
INFO
log level with PATRON_LOG_LEVEL
- Tracing, for setting up jaeger tracing with
- agent address
0.0.0.0:6831
with PATRON_JAEGER_AGENT
- sampler type
probabilistic
with PATRON_JAEGER_SAMPLER_TYPE
- sampler param
0.1
with PATRON_JAEGER_SAMPLER_PARAM
Component
A Component
is a interface that exposes the following API:
type Component interface {
Run(ctx context.Context) error
Shutdown(ctx context.Context) error
}
The above API gives the Service
the ability to start and gracefully shutdown a component
. The framework divides the components in 2 categories:
- synchronous, which are components that follow the request/response pattern and
- asynchronous, which consume messages from a source but don't respond anything back
The following component implementations are available:
- HTTP (sync)
- RabbitMQ consumer (async)
- Kafka consumer (async)
Adding to the above list is as easy as implementing a Component
and a Processor
for that component.
Example
Setting up a new service with a HTTP Component
is as easy as the following code:
// Set up HTTP routes
routes := make([]sync_http.Route, 0)
routes = append(routes, sync_http.NewRoute("/", http.MethodGet, processor, true))
srv, err := patron.New("test", patron.Routes(routes))
if err != nil {
log.Fatalf("failed to create service %v", err)
}
err = srv.Run()
if err != nil {
log.Fatalf("failed to create service %v", err)
}
The above is pretty much self-explanatory. The processor follows the sync pattern.
Processors
Synchronous
The implementation of the processor is responsible to create a Request
by providing everything that is needed (Headers, Fields, decoder, raw io.Reader) pass it to the implementation by invoking the Process
method and handle the Response
or the error
returned by the processor.
The sync package contains only a function definition along with the models needed:
type ProcessorFunc func(context.Context, *Request) (*Response, error)
The Request
model contains the following properties (which are provided when calling the "constructor" NewRequest
)
- Fields, which may contain any fields associated with the request
- Raw, the raw request data (if any) in the form of a
io.Reader
- decode, which is a function of type
encoding.Decode
that decodes the raw reader
A exported function exists for decoding the raw io.Reader in the form of
Decode(v interface{}) error
The Response
model contains the following properties (which are provided when calling the "constructor" NewResponse
)
- Payload, which may hold a struct of type
interface{}
Asynchronous
The implementation of the async processor follows exactly the same principle as the sync processor.
The main difference is that:
- The
Request
is the Message
and contains only data as []byte
- There is no
Response
, so the processor may return a error
type ProcessorFunc func(context.Context, *Message) error
Everything else is exactly the same.
Metrics and Tracing
Tracing and metrics are provided by jaeger's implementation of the OpenTracing project.
Every component has been integrated with the above library and produces traces and metrics.
Metrics are provided with the default HTTP component at the /metrics
route for Prometheus to scrape.
Tracing will be send to a jaeger agent which can be setup though environment variables mentioned in the config section. Sane defaults are applied for making the use easy.
We have included some clients inside the trace package which are instrumented and allow propagation of tracing to
downstream systems. The tracing information is added to each implementations header. These clients are:
Logging
The log package is designed to be a leveled logger with field support.
The log package defines the logger interface and a factory function type that needs to be implemented in order to set up the logging in this framework.
// instantiate the implemented factory func type and fields (map[string]interface{})
err := log.Setup(factory, fields)
// handle error
If the setup is omitted the package will not setup any logging!
From there logging is as simple as
log.Info("Hello world!")
The implementations should support following log levels:
- Debug, which should log the message with debug level
- Info, which should log the message with info level
- Warn, which should log the message with warn level
- Error, which should log the message with error level
- Panic, which should log the message with panic level and panics
- Fatal, which should log the message with fatal level and terminates the application
The first four (Debug, Info, Warn and Error) give the opportunity to differentiate the messages by severity. The last two (Panic and Fatal) do the same and do additional actions (panic and termination).
The package supports fields, which are logged along with the message, to augment the information further to ease querying in the log management system.
The following implementations are provided as sub-package and are by default wired up in the framework:
- zerolog, which supports the excellent zerolog library and is set up by default
Logger
The logger interface defines the actual logger.
type Logger interface {
Fatal(...interface{})
Fatalf(string, ...interface{})
Panic(...interface{})
Panicf(string, ...interface{})
Error(...interface{})
Errorf(string, ...interface{})
Warn(...interface{})
Warnf(string, ...interface{})
Info(...interface{})
Infof(string, ...interface{})
Debug(...interface{})
Debugf(string, ...interface{})
}
In order to be consistent with the design the implementation of the Fatal(f)
have to terminate the application with an error and the Panic(f)
need to panic.
Factory
The factory function type defines a factory for creating a logger.
type FactoryFunc func(map[string]interface{}) Logger