Build your Go image

Estimated reading time: 17 minutes

Prerequisites

  • Some understanding of Go and its toolchain. This is not a tutorial on Go. If you are new to the language, the Go website is a good starting point, so go (pun intended) check it out.
  • Some awareness of basic Docker concepts. If unsure, work through the orientation and setup in Get started Part 1.

Overview

Now that we have a good overview of containers and the Docker platform, let’s take a look at building our first image. An image includes everything you need to run an application – the code or binary, runtime, dependencies, and any other file system objects required.

To complete this tutorial, you need the following:

Meet the example application

To avoid losing focus on Docker’s features, the sample application is a minimal HTTP server that has only three features:

  • It responds with a text message containing a heart symbol (“<3”) on requests to /.
  • It responds with {"Status" : "OK"} JSON to the health check request on requests to /ping.
  • The port it listens on is configurable using the environment variable HTTP_PORT. The default value is 8080.

Thus, it somewhat mimics enough basic properties of a REST microservice to be useful for our learning of Docker.

The source code for the application is in the olliefr/docker-gs-ping GitHub repo. Please feel free to clone or fork it.

For our present study, we clone it to our local machine:

$ git clone https://github.com/olliefr/docker-gs-ping

The application’s main.go file is fairly straightforward, if you are familiar with Go:

package main

import (
	"net/http"
	"os"

	"github.com/labstack/echo/v4"
	"github.com/labstack/echo/v4/middleware"
)

func main() {

	e := echo.New()

	e.Use(middleware.Logger())
	e.Use(middleware.Recover())

	e.GET("/", func(c echo.Context) error {
		return c.HTML(http.StatusOK, "Hello, Docker! <3")
	})

	e.GET("/ping", func(c echo.Context) error {
		return c.JSON(http.StatusOK, struct{ Status string }{Status: "OK"})
	})

	httpPort := os.Getenv("HTTP_PORT")
	if httpPort == "" {
		httpPort = "8080"
	}

	e.Logger.Fatal(e.Start(":" + httpPort))
}

Smoke test the application

Let’s start our application and make sure it’s running properly. Open your terminal and navigate to the directory into which you cloned the project’s repo. From now on, we’ll refer to this directory as the working directory.

$ go run main.go

This should compile and start the server as a foreground application, outputting the banner, as illustrated in the next figure.

   ____    __
  / __/___/ /  ___
 / _// __/ _ \/ _ \
/___/\__/_//_/\___/ v4.2.2
High performance, minimalist Go web framework
https://echo.labstack.com
____________________________________O/_______
                                    O\
⇨ http server started on [::]:8080

Let’s run a quick smoke test on the application. In a new terminal, run a request using curl. Alternatively, you can use your favourite web browser as well.

$ curl http://localhost:8080/
Hello, Docker! <3

So, the application responds with a greeting, just as the first business requirement says it should. Great.

Having established that the server is running and is accessible, let’s proceed to “dockerizing” it.

Create a Dockerfile for the application

A Dockerfile is a text document that contains the instructions for building a Docker image. When we tell Docker to build our image by executing the docker build command, Docker reads these instructions and executes them one by one and creates a Docker image as a result.

Let’s walk through the process of creating a Dockerfile for our application. In the root of your working directory, create a file named Dockerfile and open this file in your text editor.

Note

The name of the file is not that important but the default filename for many commands is simply Dockerfile. So, we’ll use that as our filename throughout this series.

The first thing we need to do is to add a line in our Dockerfile that tells Docker what base image we would like to use for our application.

FROM golang:1.16-alpine

Docker images can be inherited from other images. Therefore, instead of creating our own base image, we’ll use the official Go image that already has all the tools and packages to compile and run a Go application. You can think of this in the same way you would think about class inheritance in object oriented programming or functional composition in functional programming.

When we have used that FROM command, we told Docker to include in our image all the functionality from the golang:1.16-alpine image. All of our consequent commands would build on top of that “base” image.

Note

If you want to learn more about creating your own base images, see creating base images section of the guide.

To make things easier when running the rest of our commands, let’s create a directory inside the image that we are building. This also instructs Docker to use this directory as the default destination for all subsequent commands. This way we do not have to type out full file paths but can use relative paths based on this directory.

WORKDIR /app

Usually the very first thing you do once you’ve downloaded a project written in Go is to install the modules necessary to compile it.

But before we can run go mod download inside our image, we need to get our go.mod and go.sum files copied into it. We use the COPY command to do this.

In its simplest form, the COPY command takes two parameters. The first parameter tells Docker what file you would like to copy into the image. The second parameter tells Docker where you want that file to be copied to.

We’ll copy the go.mod and go.sum file into our working directory /app which, owing to our use of WORKDIR, is the current directory (.) inside the image.

COPY go.mod ./
COPY go.sum ./

Now that we have the module files inside the Docker image that we are building, we can use the RUN command to execute the command go mod download there as well. This works exactly the same as if we were running go locally on our machine, but this time these Go modules will be installed into the a directory inside our image.

RUN go mod download

At this point, we have an image that is based on Go environment version 1.16 (or a later minor version, since we had specified 1.16 as our tag in the FROM command) and we have installed our dependencies.

The next thing we need to do is to copy our source code into the image. We’ll use the COPY command just like we did with our module files before.

COPY *.go ./

This COPY command uses a wildcard to copy all files with .go extension located in the current directory on the host (the directory where the Dockerfile is located) into the current directory inside the image.

Now, we would like to compile our application. To that end, we use the familiar RUN command:

RUN go build -o /docker-gs-ping

This should be familiar. The result of that command will be a static application binary named docker-gs-ping and located in the root of the filesystem of the image that we are building. We could have put the binary into any other place we desire inside that image, the root directory has no special meaning in this regard. It’s just convenient to use it to keep the file paths short for improved readability.

Now, all that is left to do is to tell Docker what command to execute when our image is used to start a container.

We do this with the CMD command:

CMD [ "/docker-gs-ping" ]

Here’s the complete Dockerfile:

FROM golang:1.16-alpine

WORKDIR /app

COPY go.mod ./
COPY go.sum ./
RUN go mod download

COPY *.go ./

RUN go build -o /docker-gs-ping

EXPOSE 8080

CMD [ "/docker-gs-ping" ]

The Dockerfile may also contain comments. They always begin with a # symbol and make no difference to Docker. The comments are there for the convenience of humans tasked to maintain the Dockerfile:

# Alpine is chosen for its small footprint
# compared to Ubuntu
FROM golang:1.16-alpine

WORKDIR /app

# Download necessary Go modules
COPY go.mod ./
COPY go.sum ./
RUN go mod download

# ... the rest of the Dockerfile is ...
# ...   omitted from this example   ...

Build the image

Now that we’ve created our Dockerfile, let’s build an image from it. The docker build command creates Docker images from the Dockerfile and a “context”. A build context is the set of files located in the specified path or URL. The Docker build process can access any of the files located in the context.

The build command optionally takes a --tag flag. This flag is used to label the image with a string value, which is easy for humans to read and recognise. If you do not pass a --tag, Docker will use latest as the default value.

Let’s build our first Docker image!

$ docker build --tag docker-gs-ping .
[+] Building 3.6s (12/12) FINISHED
 => [internal] load build definition from Dockerfile                                      0.1s
 => => transferring dockerfile: 38B                                                       0.0s
 => [internal] load .dockerignore                                                         0.1s
 => => transferring context: 2B                                                           0.0s
 => [internal] load metadata for docker.io/library/golang:1.16-alpine                     3.0s
 => [1/7] FROM docker.io/library/golang:1.16-alpine@sha256:49c07aa83790aca732250c2258b59  0.0s
 => => resolve docker.io/library/golang:1.16-alpine@sha256:49c07aa83790aca732250c2258b59  0.0s
 => [internal] load build context                                                         0.1s
 => => transferring context: 114B                                                         0.0s
 => CACHED [2/7] WORKDIR /app                                                             0.0s
 => CACHED [3/7] COPY go.mod .                                                            0.0s
 => CACHED [4/7] COPY go.sum .                                                            0.0s
 => CACHED [5/7] RUN go mod download                                                      0.0s
 => CACHED [6/7] COPY *.go .                                                              0.0s
 => CACHED [7/7] RUN go build -o /docker-gs-ping                                          0.0s
 => exporting to image                                                                    0.1s
 => => exporting layers                                                                   0.0s
 => => writing image sha256:336a3f164d0f079f2e42cd1d38f24ab9110d47d481f1db7f2a0b0d2859ec  0.0s
 => => naming to docker.io/library/docker-gs-ping                                         0.0s

Use 'docker scan' to run Snyk tests against images to find vulnerabilities and learn how to fix them

Your exact output will vary, but provided there aren’t any errors, you should see the FINISHED line in the build output. This means Docker has successfully built our image and assigned a docker-gs-ping tag to it.

View local images

To see the list of images we have on our local machine, we have two options. One is to use the CLI and the other is to use Docker Desktop. Since we are currently working in the terminal, let’s take a look at listing images with the CLI.

To list images, simply run the images command:

$ docker images
REPOSITORY       TAG       IMAGE ID       CREATED          SIZE
docker-gs-ping   latest    336a3f164d0f   39 minutes ago   540MB
postgres         13.2      c5ec7353d87d   7 weeks ago      314MB

Your exact output may vary, but you should see docker-gs-ping image with the latest tag.

Tag images

An image name is made up of slash-separated name components. Name components may contain lowercase letters, digits and separators. A separator is defined as a period, one or two underscores, or one or more dashes. A name component may not start or end with a separator.

An image is made up of a manifest and a list of layers. In simple terms, a “tag” points to a combination of these artifacts. You can have multiple tags for the image and, in fact, most images have multiple tags. Let’s create a second tag for the image we had built and take a look at its layers.

To create a new tag for our image, run the following command.

$ docker tag docker-gs-ping:latest docker-gs-ping:v1.0

The Docker tag command creates a new tag for the image. It does not create a new image. The tag points to the same image and is just another way to reference the image.

Now run the docker images command to see the updated list of local images:

$ docker images
REPOSITORY       TAG       IMAGE ID       CREATED          SIZE
docker-gs-ping   latest    336a3f164d0f   43 minutes ago   540MB
docker-gs-ping   v1.0      336a3f164d0f   43 minutes ago   540MB
postgres         13.2      c5ec7353d87d   7 weeks ago      314MB

You can see that we have two images that start with docker-gs-ping. We know they are the same image because if you look at the IMAGE ID column, you can see that the values are the same for the two images. This value is a unique identifier Docker uses internally to identify the image.

Let’s remove the tag that we had just created. To do this, we’ll use the rmi command, which stands for “remove image”:

$ docker rmi docker-gs-ping:v1.0
Untagged: docker-gs-ping:v1.0

Notice that the response from Docker tells us that the image has not been removed but only “untagged”. Verify this by running the images command:

$ docker images
REPOSITORY       TAG       IMAGE ID       CREATED          SIZE
docker-gs-ping   latest    336a3f164d0f   45 minutes ago   540MB
postgres         13.2      c5ec7353d87d   7 weeks ago      314MB

The tag v1.0 has been removed but we still have the docker-gs-ping:latest tag available on our machine, so the image is there.

Multi-stage builds

You may have noticed that our docker-gs-ping image stands at 540MB, which you may think is a lot. You may also be wondering whether our dockerized application still needs the full suite of Go tools, including the compiler, after the application binary had been compiled.

These are legit concerns. Both can be solved by using multi-stage builds. The following example is provided with little explanation because this would derail us from our current concerns, but please feel free to explore on your own later. The main idea is that we use one image to produce some artefacts, which are then placed into another, much smaller image, containing only the parts necessary for running the artefacts that we’d built.

The Dockerfile.multistage in the sample application’s repo has the following content:

##
## Build
##

FROM golang:1.16-buster AS build

WORKDIR /app

COPY go.mod ./
COPY go.sum ./
RUN go mod download

COPY *.go ./

RUN go build -o /docker-gs-ping

##
## Deploy
##

FROM gcr.io/distroless/base-debian10

WORKDIR /

COPY --from=build /docker-gs-ping /docker-gs-ping

EXPOSE 8080

USER nonroot:nonroot

ENTRYPOINT ["/docker-gs-ping"]

Since we have two dockerfiles now, we have to tell Docker that we want to build using our new Dockerfile. We also tag the new image with multistage but this word has no special meaning, we only do so that we could compare this new image to the one we’ve built previously, that is the one we tagged with latest:

docker build -t docker-gs-ping:multistage -f Dockerfile.multistage .

Comparing the sizes of docker-gs-ping:multistage and docker-gs-ping:latest we see an order-of-magnitude difference!

REPOSITORY       TAG          IMAGE ID       CREATED              SIZE
docker-gs-ping   multistage   e3fdde09f172   About a minute ago   27.1MB
docker-gs-ping   latest       336a3f164d0f   About an hour ago    540MB

This is due to the fact that the “distroless” base image that we have used to deploy our Go application is very barebones and is meant for lean deployments of static binaries.

For more information on multi-stage builds, please feel free to check out other parts of Docker documentation. This is, however, not essential for our progress here, so we’ll leave it at that.

Next steps

In this module, we took a look at setting up our example Go application that we will use for much of the rest of the tutorial. We also created a Dockerfile that we used to build our Docker image. Then, we took a look at tagging our images and removing images and tags. In the next module, we’ll take a look at how to:

Run your image as a container

Feedback

Help us improve this topic by providing your feedback. Let us know what you think by creating an issue in the Docker Docs GitHub repository. Alternatively, create a PR to suggest updates.


containers, images, go, golang, dockerfiles, coding, build, push, run