The weather
example is a fully instrumented system that is composed of three
services:
- The
location
service makes requests to theip-api.com
web API to retrieve IP location information. - The
forecaster
service makes requests to theweather.gov
web API to retrieve weather forecast information. - The
front
service exposes a public HTTP API that returns weather forecast information for a given IP. It makes requests to thelocation
service followed by theforecaster
service to collect the information.
The following should get you going:
scripts/setup
scripts/server
scripts/setup
configures all the required dependencies and compiles the services.
scripts/server
runs the services using
overmind. scripts/server
also starts
docker-compose
with a configuration that runs a self-hosted deployment of
SigNoz as backend for instrumentation.
Assuming you have a running weather system, you can make a request to the front
service using the curl
command as follows:
curl http://localhost:8084/forecast/8.8.8.8
If this returns successfully start the script that generates load:
scripts/load
To analyze traces open the SigNoz dashboard running on http://localhost:3301.
The three services make use of the
log package initialized in
main
:
ctx := log.Context(context.Background(), log.WithFormat(format), log.WithFunc(log.Span))
The log.WithFormat
option enables colors when logging to a terminal while the
log.Span
option adds the trace and span IDs to each log entry.
The front
service uses the HTTP middleware to initialize the log context for
for every request:
handler = log.HTTP(ctx)(handler)
The health check HTTP endpoints also use the log HTTP middleware to log errors:
check = log.HTTP(ctx)(check).(http.HandlerFunc)
The gRPC services (locator
and forecaster
) use the gRPC interceptor returned by
log.UnaryServerInterceptor
to initialize the log context for every request:
grpcsvr := grpc.NewServer(
grpc.ChainUnaryInterceptor(
log.UnaryServerInterceptor(ctx), // <--
debug.UnaryServerInterceptor()),
grpc.StatsHandler(otelgrpc.NewServerHandler()))
The example runs a self-hosted deployment of SigNoz as backend for instrumentation. Each service sends telemetry data to the OpenTelemetry collector running in the docker-compose
configuration. The collector then forwards the data to the SigNoz backend.
The collector is configured in the main
function of each service:
spanExporter, err := otlptracegrpc.New(ctx,
otlptracegrpc.WithEndpoint(*oteladdr),
otlptracegrpc.WithTLSCredentials(insecure.NewCredentials()))
if err != nil {
log.Fatalf(ctx, err, "failed to initialize tracing")
}
defer func() {
if err := spanExporter.Shutdown(ctx); err != nil {
log.Errorf(ctx, err, "failed to shutdown tracing")
}
}()
metricExporter, err := otlpmetricgrpc.New(ctx,
otlpmetricgrpc.WithEndpoint(*oteladdr),
otlpmetricgrpc.WithTLSCredentials(insecure.NewCredentials()))
if err != nil {
log.Fatalf(ctx, err, "failed to initialize metrics")
}
defer func() {
if err := metricExporter.Shutdown(ctx); err != nil {
log.Errorf(ctx, err, "failed to shutdown metrics")
}
}()
cfg, err := clue.NewConfig(ctx,
genforecaster.ServiceName,
genforecaster.APIVersion,
metricExporter,
spanExporter,
)
if err != nil {
log.Fatalf(ctx, err, "failed to initialize instrumentation")
}
clue.ConfigureOpenTelemetry(ctx, cfg)
Clients of downstream services are also instrumented using OpenTelemetry. For
example the following code creates an instrumented gRPC connection and uses it
to create a client to the Locator
service:
lcc, err := grpc.DialContext(ctx,
*locatorAddr,
grpc.WithTransportCredentials(insecure.NewCredentials()),
grpc.WithUnaryInterceptor(log.UnaryClientInterceptor()), // Log requests
grpc.WithStatsHandler(otelgrpc.NewClientHandler())) // Collect metrics and traces
if err != nil {
log.Fatalf(ctx, err, "failed to connect to locator")
}
lc := locator.New(lcc) // Create client using instrumented connection
The example also showcases the instrumentation of clients to external services.
For example, the Locator
service demonstrates how the HTTP client used to
create the IP Location service client is instrumented:
httpc := &http.Client{
Transport: log.Client( // Log requests
otelhttp.NewTransport(
http.DefaultTransport,
otelhttp.WithClientTrace(func(ctx context.Context) *httptrace.ClientTrace {
return otelhttptrace.NewClientTrace(ctx)
}), // Propagate traces
))}
ipc := ipapi.New(httpc)
Health checks are implemented using the health
package, for example:
check := health.Handler(health.NewChecker(wc))
The front service also uses the health.NewPinger
function to create a health
checker for the forecaster
and location
services which both expose a
/livez
HTTP endpoint:
check := health.Handler(health.NewChecker(
health.NewPinger("locator", "http", *locatorHealthAddr),
health.NewPinger("forecaster", "http", *forecasterHealthAddr)))
The health check and metric handlers are mounted on a separate HTTP handler (the
global http
standard library handler) to avoid logging, tracing and otherwise
instrumenting the corresponding requests.
http.Handle("/livez", check)
http.Handle("/metrics", instrument.Handler(ctx))
The service HTTP handler created by Goa - if any - is mounted onto the global handler under the root path so that all HTTP requests other than heath checks and metrics are passed to it:
http.Handle("/", handler)
The front
service define clients for both the locator
and forecaster
services under the clients
directory. Each client is defined via a
Client
interface, for example:
// Client is a client for the forecast service.
Client interface {
// GetForecast gets the forecast for the given location.
GetForecast(ctx context.Context, lat, long float64) (*Forecast, error)
}
The interface is implemented by both a real and a mock client. The real client
is instantiated via the New
function in the client.go
file:
// New instantiates a new forecast service client.
func New(cc *grpc.ClientConn) Client {
c := genclient.NewClient(cc, grpc.WaitForReady(true))
return &client{c.Forecast()}
}
The mock is instantiated via the NewClient
function located in the
mocks/client.go
file that is generated using the cmg
tool:
// NewMock returns a new mock client.
func NewClient(t *testing.T) *Client {
var (
m = &Client{mock.New(), t}
_ = forecaster.Client = m
)
return m
}
The mock implementations make use of the mock
package to make it possible to
create call sequences and validate them:
type (
// Mock implementation of the forecast client.
Client struct {
m *mock.Mock
t *testing.T
}
ClientGetForecastFunc func(ctx context.Context, lat, long float64) (*forecaster.Forecast, error)
)
// AddGetForecastFunc adds f to the mocked call sequence.
func (m *Client) AddGetForecast(f ClientGetForecastFunc) {
m.m.Add("GetForecast", f)
}
// SetGetForecastFunc sets f for all calls to the mocked method.
func (m *Client) SetGetForecast(f ClientGetForecastFunc) {
m.m.Set("GetForecast", f)
}
// GetForecast implements the Client interface.
func (m *Client) GetForecast(ctx context.Context, lat, long float64) (*forecaster.Forecast, error) {
if f := m.m.Next("GetForecast"); f != nil {
return f.(ClientGetForecastFunc)(ctx, lat, long)
}
m.t.Helper()
m.t.Error("unexpected GetForecast call")
return nil, nil
}
Tests leverage the AddGetForecast
and SetGetForecast
methods to configure
the mock client:
lmock := mocklocator.NewClient(t)
lmock.AddGetLocation(c.locationFunc) // Mock the locator service.
fmock := mockforecaster.NewClient(t)
fmock.AddGetForecast(c.forecastFunc) // Mock the forecast service.
s := New(fmock, lmock) // Create front service instance for testing
The mock
package is also used to create mocks for web services (ip-api.com
and weather.gov
) in the location
and forecaster
services.
A bug was intentionally left in the code to demonstrate how useful instrumentation can be, can you find it? If you do let us know on the Gophers slack Goa channel!