Sysadmin productivity with Go

3 minutes

Over the past 6 months, I’ve been learning Go and using it to solve various system administration tasks. One of the first useful things I wrote in Go, was a program that read the report plist, which AutoPkg outputs, and piped the output to Slack.

With the release of AutoPkg 0.5.0, the format of --report-plist had changed, which meant that I would have to rewrite my script. By this time I had a better handle on Go, especially it’s concurrency primitives.

AutoPkg lets you specify a text file with a list of recipes to check.

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Given the text file above, AutoPkg will check each recipe, sequentially. With a big enough list, the process can easily take 30 minutes or more. We can illustrate the current process by borrowing this cute picture from the Concurrency is not parallelism go talk.

An this example, the pile of books represents the recipes autopkg must process. We can speed this process a bit, by separating the work. Let’s assign one gopher(goroutine) to read each recipe from a file, and create work for other gophers.

recipes := make( chan string ) ... func readRecipeList ( recipes chan string ) { file , err := os . Open ( conf . RecipesFile ) if err != nil { log . Fatal ( err ) } defer file . Close () scanner := bufio . NewScanner ( file ) for scanner . Scan () { recipe := scanner . Text () recipes <- recipe } close( recipes ) }

Here we open a text file, read each line, and send each recipe on a channel. When we are done, we close the recipes channel.

for recipe := range recipes { go func(recipe string) { reports <- runAutopkg(recipe) }(recipe) }

Adding the go keyword before a function call, executes that function in a separate goroutine. In this case, we call

func runAutopkg(recipe string) *autopkgReport { // Exec autopkg and return report.plist }

for each recipe, and pass the report that the function returns to a new channel, called reports. We can take the reports channel, and pass it to different interpreter functions, that can do something based on the report(also concurrently).

We can wrap all of the above into a new function called process() , that looks like this:

var wg sync.WaitGroup recipes := make(chan string) reports := make(chan *autopkgReport) go readRecipeList(recipes) go notifySlack(reports) for recipe := range recipes { wg.Add(1) go func(recipe string) { reports <- runAutopkg(recipe) wg.Done() }(recipe) } wg.Wait() close(reports) done <- true

The code has two new additions. The first is a WaitGroup variable. The WaitGroup allows us to synchronize all the concurrent processes and wait until they complete. We also added the line

done <- true

Somewhere else in our code, we created done := make(chan bool) , a boolean channel and by sending <-true on the channel, we are signaling that the our process() function has completed. The process can be roughly illustrated by the picture below.

We can now repeat the whole process at a specified interval by creating a ticker.

func main() { done := make(chan bool) ticker := time.NewTicker(time.Minute * 5).C for { go process(done) <-done <-ticker } }

The process will now repeat every 5 minutes, except that we’re also blocking the loop by listening on the <-done channel, so if the previous process is still executing, the program will wait.

The full program, including an OS X binary is available on github.

We can use a similar process to solve many problems we encounter in the real world. If you found the above example intriguing, here’s an entertaining talk that illustrates the same concepts more concisely.

The drawings used in this blog post were created by illustrator Renee French.