Golang - Scaling a websocket client for multiple connections to different servers - sockets

Question

I have a websocket client. In reality, it is far more complex than the basic code shown below.
I now need to scale this client code to open connections to multiple servers. Ultimately, the tasks that need to be performed when a message is received from the servers is identical.
What would be the best approach to handle this?
As I said above the actual code performed when receiving the message is far more complex than shown in the example.
package main
import (
"flag"
"log"
"net/url"
"os"
"os/signal"
"time"
"github.com/gorilla/websocket"
)
var addr = flag.String("addr", "localhost:1234", "http service address")
func main() {
flag.Parse()
log.SetFlags(0)
interrupt := make(chan os.Signal, 1)
signal.Notify(interrupt, os.Interrupt)
// u := url.URL{Scheme: "ws", Host: *addr, Path: "/echo"}
u := url.URL{Scheme: "ws", Host: *addr, Path: "/"}
log.Printf("connecting to %s", u.String())
c, _, err := websocket.DefaultDialer.Dial(u.String(), nil)
if err != nil {
log.Fatal("dial:", err)
}
defer c.Close()
done := make(chan struct{})
go func() {
defer close(done)
for {
_, message, err := c.ReadMessage()
if err != nil {
log.Println("read:", err)
return
}
log.Printf("recv: %s", message)
}
}()
ticker := time.NewTicker(time.Second)
defer ticker.Stop()
for {
select {
case <-done:
return
case t := <-ticker.C:
err := c.WriteMessage(websocket.TextMessage, []byte(t.String()))
if err != nil {
log.Println("write:", err)
return
}
case <-interrupt:
log.Println("interrupt")
// Cleanly close the connection by sending a close message and then
// waiting (with timeout) for the server to close the connection.
err := c.WriteMessage(websocket.CloseMessage, websocket.FormatCloseMessage(websocket.CloseNormalClosure, ""))
if err != nil {
log.Println("write close:", err)
return
}
select {
case <-done:
case <-time.After(time.Second):
}
return
}
}
}

Answer 1

Modify the interrupt handling to close a channel on interrupt. This allows multiple goroutines to wait on the event by waiting for the channel to close.
shutdown := make(chan struct{})
interrupt := make(chan os.Signal, 1)
signal.Notify(interrupt, os.Interrupt)
go func() {
<-interrupt
log.Println("interrupt")
close(shutdown)
}()
Move the per-connection code to a function. This code is a copy and paste from the question with two changes: the interrupt channel is replaced with the shutdown channel; the function notifies a sync.WaitGroup when the function is done.
func connect(u string, shutdown chan struct{}, wg *sync.WaitGroup) {
defer wg.Done()
log.Printf("connecting to %s", u)
c, _, err := websocket.DefaultDialer.Dial(u, nil)
if err != nil {
log.Fatal("dial:", err)
}
defer c.Close()
done := make(chan struct{})
go func() {
defer close(done)
for {
_, message, err := c.ReadMessage()
if err != nil {
log.Println("read:", err)
return
}
log.Printf("recv: %s", message)
}
}()
ticker := time.NewTicker(time.Second)
defer ticker.Stop()
for {
select {
case <-done:
return
case t := <-ticker.C:
err := c.WriteMessage(websocket.TextMessage, []byte(t.String()))
if err != nil {
log.Println("write:", err)
return
}
case <-shutdown:
// Cleanly close the connection by sending a close message and then
// waiting (with timeout) for the server to close the connection.
err := c.WriteMessage(websocket.CloseMessage, websocket.FormatCloseMessage(websocket.CloseNormalClosure, ""))
if err != nil {
log.Println("write close:", err)
return
}
select {
case <-done:
case <-time.After(time.Second):
}
return
}
}
}
Declare a sync.WaitGroup in main(). For each websocket endpoint that you want to connect to, increment the WaitGroup and start a goroutine to connect that endpoint. After starting the goroutines, wait on the WaitGroup for the goroutines to complete.
var wg sync.WaitGroup
for _, u := range endpoints { // endpoints is []string
// where elements are URLs
// of endpoints to connect to.
wg.Add(1)
go connect(u, shutdown, &wg)
}
wg.Wait()
The code above with an edit to make it run against Gorilla's echo example server is posted on the playground.

Answer 2

is the communication with every different server completely independendant of the other servers? if yes i would go around in a fashion like:
in main create a context with a cancellation function
create a waitgroup in main to track fired up goroutines
for every server, add to the waitgroup, fire up a new goroutine from the main function passing the context and the waitgroup references
main goes in a for/select loop listening to for signals and if one arrives calls the cancelfunc and waits on the waitgroup.
main can also listen on a result chan from the goroutines and maybe print the results itself it the goroutines shouldn't do it directly.
every goroutine has as we said has references for the wg, the context and possibly a chan to return results. now the approach splits on if the goroutine must do one and one thing only, or if it needs to do a sequence of things. for the first approach
if only one thing is to be done we follow an approach like the one descripbed here (observe that to be asyncronous he would in turn fire up a new goroutine to perform the DoSomething() step that would return the result on the channel)
That allows it to be able to accept the cancellation signal at any time. it is up to you to determine how non-blocking you want to be and how prompt you want to be to respond to cancellation signals.Also the benefit of having the a context associated being passed to the goroutines is that you can call the Context enabled versions of most library functions. For example if you want your dials to have a timeout of let's say 1 minute, you would create a new context with timeout from the one passed and then DialContext with that. This allows the dial to stop both from a timeout or the parent (the one you created in main) context's cancelfunc being called.
if more things need to be done ,i usually prefer to do one thing with the goroutine, have it invoke a new one with the next step to be performed (passing all the references down the pipeline) and exit.
this approach scales well with cancellations and being able to stop the pipeline at any step as well as support contexts with dealines easily for steps that can take too long.