Docker images are fundamental building blocks in the Docker ecosystem that allow you to package up applications and their dependencies so they can be ported easily between different environments. When you build an image, Docker reads instructions from a Dockerfile and executes them in order to create the filesystem and populate it.
In this comprehensive 2600+ word guide for full-stack engineers, we will walk through how to build a Docker image by specifying the Dockerfile location, analyze key build considerations, and provide expert tips for creating optimized and secure images suited for CI/CD deployments.
Prerequisites
Before you can build an image, you need:
- Docker installed on your machine
- Basic understanding of Docker concepts like images, containers, Dockerfile
- Dockerfile written with instructions to assemble the image
Step 1 – Best Practices for Dockerfiles
Since the Dockerfile provides the instructions for building our images, it is crucially important to optimize and secure it properly. Some key best practices include:
Choosing the Right Base Image
The base image provides the foundational filesystem for building upon and influences security, file size, and efficiency. Some popular choices include:
| Base Image | Description |
|---|---|
| Ubuntu | Popular Linux distro, strikes balance of size and capability |
| Debian | Stable and minimal Linux distro good for containers |
| Alpine | Extremely small security focused Linux distro (5MB) |
| Red Hat UBI | Commercial Linux distro focused on security |
According to industry reports [1], Alpine and Red Hat UBI lead for security given their "just enough OS (JeOS)" approach with smaller surface area for attacks. However, minimal distros limit what software can be installed. Ubuntu presents a solid middle ground.
Utilize Multi-Stage Builds
Multi-stage Docker builds allow you to use multiple FROM statements. By splitting your Dockerfile into stages, early stages can contain build dependencies like compilers that are not needed in final image [2]. This optimized for minimal production images.
As an example, building a Go application:
# Builder
FROM golang:1.19 AS builder
WORKDIR /app
COPY main.go .
RUN CGO_ENABLED=0 GOOS=linux go build -a -installsuffix cgo -o main .
# Production Image
FROM alpine:3
WORKDIR /app
COPY --from=builder /app/main .
CMD ["./main"] This method can reduce final image sizes substantially (in some cases over 100MB smaller) by removing unneeded toolchain artifacts [3].
Use Semantic Version Tags
Proper container image tagging is essential for identification and version management. Some guidelines:
- Use namespace/imagename:version-variant format
- Increment version according to semantic version MAJOR.MINOR.PATCH
- Note variant like os or arch differences
Example: yourcontainer/web:1.3.5-alpine
This provides easy visual recognition and ensures compatibility when pulling images.
Reproducible Builds
To enable reproducible image builds over time, Dockerfiles should be self contained with no dependencies on external state. Some tips:
- Always commit generated files rather than pulling them in during build
- Fully qualify RUN commands paths like WORKDIR/script instead of script
- Don‘t pull packages from HEAD tip versions
Testing regularly from scratch ensures you generate bit-for-bit identical images.
reduce attack surface area
It is critical to run services in containers as non-root users wherever possible and avoid installing unnecessary packages that increase potential vulnerabilities.
Some key techniques:
- Create and switch to non-root user in Dockerfile
- Set USER declaration to use non-root user
- Only include essential apt packages needed for app runtime
- Scan images regularly for CVEs using tools like Trivy
Step 2 – Specify Build Context
When building an image, we need to specify the build context – this is the set of files located in the specified PATH or URL containing our Dockerfile, files to copy into image, etc.
For our example app, let‘s create a folder structure:
/docker-image
|__ Dockerfile
|__ index.html
|__ package.json
|__ server.js Here our build context includes all files Docker needs access to in order to build image per our Dockerfile instructions.
Step 3 – Build Image with docker build
With our build context ready, we can now use the docker build command to construct the image by specifying the Dockerfile path:
docker build -t my-app:v1.0.2 -f docker-image/Dockerfile docker-imageLet‘s examine each part:
-t– Name and optionally tag image-f– Specify location of Dockerfiledocker-image– Build context path
This will run the instructions in our Dockerfile using the files in our context and generate the my-app:1.0.2 image.
Comparison: docker build vs docker-compose
Docker Compose allows you to define services including their build configuration and dependencies in a YAML file, and build multiple images:
services:
web:
build:
context: .
dockerfile: Dockerfile
image: my-app
db:
image: mysqlThen run docker-compose build to construct images.
Compose simplifies building multiple services simultaneously but docker build allows more granular control over a single image. We recommend Compose for local dev/test and docker build for CI/CD pipeline use cases.
Enhanced BuildKit and LLB
Docker BuildKit provides advanced capabilities for building container images [4] including:
- Better caching for faster rebuilds
- Running builders in parallel
- Dynamic dependency graphs
- Support for other file formats like Buildah‘s Low-Level Builders
To enable, set environment variable DOCKER_BUILDKIT=1 or export DOCKER_BUILDKIT=1.
Alternative Build Tools
While docker build is the standard way to construct images, alternatives do exist:
- Buildah – Provides CLI tool for building OCI images
- Kaniko – Build images directly from Dockerfile without needing daemon
- Img – Standalone, daemon-less tool for building images
These options can be useful for restricted environments that disallow or limit Docker daemon access.
Step 4 – Push and Distribution
Once our image is built, we need to make it accessible for deployment. Best practice is to store images in a central registry rather than distributing docker host artifacts.
Registries options:
| Option | Description |
|---|---|
| DockerHub | Public registry to host public/private images |
| AWS ECR | Managed registry integrated with AWS services |
| Google GCR | Private container registry on Google Cloud |
| Azure ACR | Managed private Docker registry service |
For maximum security and privacy, use managed private registries like AWS ECR or GCR versus public repositories.
To push our recently built image:
docker tag my-app acct123.dkr.ecr.us-east-1.amazonaws.com/my-app:v1.0.2
docker push acct123.dkr.ecr.us-east-1.amazonaws.com/my-app:v1.0.2We retag with our registry endpoint, then push.
Troubleshooting Registry Access
If encountering errors like access denied, authentication required, or TLS handshake failure, some things to validate:
- Registry network ACLs or firewalls allowing connection
- docker login executed against registry for auth
- Certs/CA bundles properly configured
Running docker login or docker logout can often resolve registry access problems.
Content Addressability with Image Digests
To provide immutable identifiers for images independent of tags, Docker supports content addressable image digests.
A digest references a specific image manifest that is hashed, for example:
acct123.dkr.ecr.us-east-1.amazonaws.com/my-app@sha256:9460f7a04684887e307ad29ec53f28d70c9341f6a05655dd35d66a7d60d270218Using digests ensures you always redeploy the exact same image.
Garbage Collection and Storage
As engineers rebuild images during development, abandoned intermediate containers, logs, and unused images will pile up on disk overtime.
Be sure to implement garbage collection processes using docker system prune and docker image prune to clean out this cruft periodically.
Without concerted pruning efforts, redundant layers and orphaned files can claim substantial amounts of storage causing resource pressure:
Accumulated image waste before garbage collection
CI/CD Integration
For maximum productivity, image build pipelines should integrate into overall Continuous Integration / Continuous Delivery workflows. This enables automated building for rapid, consistent updates.
Caching for Faster Builds
Docker caching during image builds is enabled by default but proper use of cache directives like --cache-from and --no-cache in your CI scripts allow even faster repeat builds.
Some leading practices for optimized caching:
- Cache vendor package steps separately from app code
- Tag build cache sources with unique IDs
- Rebuild from scratch regularly to layer bust
A well-tuned cache can cut build times from 15+ minutes to under five in many cases.
Unit Test Images
Robust testing by both dynamically analyzing images for expected contents using tools like Container Structure Tests and behaviorally via product test suites is highly recommended.
Execute both unit and integration testing against your images before promoting builds to staging/production. Fail builds fast that don‘t pass quality checks.
Security Scanning
Images should undergo static and dynamic vulnerability analysis using tools such as Trivy, Snyk, or proprietary scanners available from registry providers:
Sample security scan output
Scan images routinely as part of your pipelines, fail builds on policy violations like high severity CVEs.
Canary Testing
Where possible utilize canary testing by deploying image changes incrementally to a portion of your infrastructure before broader rollout. This technique reduces risk and provides an additional round of validation for container updates.
Conclusion
In summary, we walked through full lifecycle management for Docker images – constructing optimized Dockerfiles, building images from specified locations, distributing via secure registries, and integrating into CI/CD pipelines to enable rapid, robust delivery of updates.
Leveraging docker build allows granular control over image generation instructions while supporting integration into automated workflows around continuous delivery. Keeping images small, caching effectively, testing rigorously, and scanning continuously are all central to container success. We hope these industry best practices and expert tips help you efficiently build, manage and run your containerized workloads.
Let us know if you have any other questions!
References
- CIS Benchmark for Kubernetes, Center for Internet Security
- Multi-Stage Docker Builds for Creating Tiny Go Images, Alex Ellis
- Why Multi-Stage Docker Builds Help Engineers Reduce Image Sizes, RisingStack
- Introducing Docker BuildKit, Docker Blog