Extending the Interaction Between AI Agents and Editors

This ongoing Docker Labs GenAI series explores the exciting space of AI developer tools. At Docker, we believe there is a vast scope to explore, openly and without the hype. We will share our explorations and collaborate with the developer community in real time. Although developers have adopted autocomplete tooling like GitHub Copilot and use chat, there is significant potential for AI tools to assist with more specific tasks and interfaces throughout the entire software lifecycle. Therefore, our exploration will be broad. We will be releasing software as open source so you can play, explore, and hack with us, too.

We recently met up with developers at GitHub Universe at the Docker booth. In addition to demonstrating the upcoming Docker agent extension for GitHub Copilot, we also hosted a “Hack with Docker Labs” session. 

To facilitate these sessions, we created a VSCode extension to explore the relationship between agents and tools. We encouraged attendees to think about how agents can change how we interact with tools by mixing tool definitions (anything you can package in a Docker container) with prompts using a simple Markdown-based canvas.

Many of these sessions followed a simple pattern.

Choose a tool and describe what you want it to do.

Let the agent interact with that tool.

Ask the agent to explain what it did or adjust the strategy and try again.

It was great to facilitate these discussions and learn more about how agents are challenging us to interact with tools in new ways.  

Figure 1 shows a short example of a session where we generated a QR code (qrencode). We start by defining both a tool and a prompt in the Markdown file. Then, we pass control over to the agent and let it interact with that tool (the output from the agent pops up on the right-hand side).

Figure 1: Generating a QR code.

Feel free to create an issue in our repo if you want to learn more.

Editors

This year’s trip to GitHub Universe also felt like an opportunity to reflect on how developer workflows are changing with the introduction of coding assistants. Developers may have had language services in the editor for a long time now, but coding assistants that can predict the next most likely tokens have taught us something new. We were all writing more or less the same programs (Figure 2).

Figure 2: Language service interaction.

Other agents

Tools like Cursor, GitHub Copilot Chat, and others are also teaching us new ways in which coding assistants are expanding beyond simple predictions. In this series, we’ve been highlighting tools that typically work in the background. Agents armed with these tools will track other kinds of issues, such as build problems, outdated dependencies, fixable linting violations, and security remediations.

Extending the previous diagram, we can imagine an updated picture where agents send diagnostics and propose code actions, while still offering chat interfaces for other kinds of user input (Figure 3). If the ecosystem has felt closed, get ready for it to open up to new kinds of custom agents.

Figure 3: Agent extension.

More to come

In the next few posts, we’ll take this series in a new direction and look at how agents are able to use LSPs to interact with developers in new ways. An agent that represents background tasks, such as updating dependencies, or fixing linting violations, can now start to use language services and editors as tools! We think this will be a great way for agents to start helping developers better understand the changes they’re making and open up these platforms to input from new kinds of tools.

GitHub Universe was a great opportunity to check in with developers, and we were excited to learn how many more tools developers wanted to bring to their workflows. As always, to follow along with this effort, check out the GitHub repository for this project.

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Why Testcontainers Cloud Is a Game-Changer Compared to Docker-in-Docker for Testing Scenarios

Navigating the complex world of containerized testing environments can be challenging, especially when dealing with Docker-in-Docker (DinD). As a senior DevOps engineer and Docker Captain, I’ve seen firsthand the hurdles that teams face with DinD, and here I’ll share why Testcontainers Cloud is a transformative alternative that’s reshaping the way we handle container-based testing.

Understanding Docker-in-Docker

Docker-in-Docker allows you to run Docker within a Docker container. It’s like Inception for containers — a Docker daemon running inside a Docker container, capable of building and running other containers.

How Docker-in-Docker works

Nested Docker daemons: In a typical Docker setup, the Docker daemon runs on the host machine, managing containers directly on the host’s operating system. With DinD, you start a Docker daemon inside a container. This inner Docker daemon operates independently, enabling the container to build and manage its own set of containers.

Privileged mode and access to host resources: To run Docker inside a Docker container, the container needs elevated privileges. This is achieved by running the container in privileged mode using the –privileged flag:

docker run –privileged -d docker:dind

The –privileged flag grants the container almost all the capabilities of the host machine, including access to device files and the ability to perform system administration tasks. Although this setup enables the inner Docker daemon to function, it poses significant security risks, as it can potentially allow the container to affect the host system adversely.

Filesystem considerations: The inner Docker daemon stores images and containers within the file system of the DinD container, typically under /var/lib/docker. Because Docker uses advanced file system features like copy-on-write layers, running an inner Docker daemon within a containerized file system (which may itself use such features) can lead to complex interactions and potential conflicts.

Cgroups and namespace isolation: Docker relies on Linux kernel features like cgroups and namespaces for resource isolation and management. When running Docker inside a container, these features must be correctly configured to allow nesting. This process can introduce additional complexity in ensuring that resource limits and isolation behave as expected.

Why teams use Docker-in-Docker

Isolated build environments: DinD allows each continuous integration (CI) job to run in a clean, isolated Docker environment, ensuring that builds and tests are not affected by residual state from previous jobs or other jobs running concurrently.

Consistency across environments: By encapsulating the Docker daemon within a container, teams can replicate the same Docker environment across different stages of the development pipeline, from local development to CI/CD systems.

Challenges with DinD

Although DinD provides certain benefits, it also introduces significant challenges, such as:

Security risks: Running containers in privileged mode can expose the host system to security vulnerabilities, as the container gains extensive access to host resources.

Stability issues: Nested containers can lead to storage driver conflicts and other instability issues, causing unpredictable build failures.

Complex debugging: Troubleshooting issues in a nested Docker environment can be complicated, as it involves multiple layers of abstraction and isolation.

Real-world challenges

Although Docker-in-Docker might sound appealing, it often introduces more problems than it solves. Before diving into those challenges, let’s briefly discuss Testcontainers and its role in modern testing practices.

What is Testcontainers?

Testcontainers is a popular open source library designed to support integration testing by providing lightweight, disposable instances of common databases, web browsers, or any service that can run in a Docker container. It allows developers to write tests that interact with real instances of external resources, rather than relying on mocks or stubs.

Key features of Testcontainers

Realistic testing environment: By using actual services in containers, tests are more reliable and closer to real-world scenarios.

Isolation: Each test session, or even each test can run in a clean environment, reducing flakiness due to shared state.

Easy cleanup: Containers are ephemeral and are automatically cleaned up after tests, preventing resource leaks.

Dependency on the Docker daemon

A core component of Testcontainers’ functionality lies in its interaction with the Docker daemon. Testcontainers orchestrates Docker resources by starting and stopping containers as needed for tests. This tight integration means that access to a Docker environment is essential wherever the tests are run.

The DinD challenge with Testcontainers in CI

When teams try to include Testcontainers-based integration testing in their CI/CD pipelines, they often face the challenge of providing Docker access within the CI environment. Because Testcontainers requires communication with the Docker daemon, many teams resort to using Docker-in-Docker to emulate a Docker environment inside the CI job.

However, this approach introduces significant challenges, especially when trying to scale Testcontainers usage across the organization.

Case study: The CI pipeline nightmare

We had a Jenkins CI pipeline that utilized Testcontainers for integration tests. To provide the necessary Docker environment, we implemented DinD. Initially, it seemed to work fine, but soon we encountered:

Unstable builds: Random failures due to storage driver conflicts and issues with nested container layers. The nested Docker environment sometimes clashed with the host, causing unpredictable behavior.

Security concerns: Running containers in privileged mode raised red flags during security audits. Because DinD requires privileged mode to function correctly, it posed significant security risks, potentially allowing containers to access the host system.

Performance bottlenecks: Builds were slow, and resource consumption was high. The overhead of running Docker within Docker led to longer feedback loops, hindering developer productivity.

Complex debugging: Troubleshooting nested containers became time-consuming. Logs and errors were difficult to trace through the multiple layers of containers, making issue resolution challenging.

We spent countless hours trying to patch these issues, but it felt like playing a game of whack-a-mole.

Why Testcontainers Cloud is a better choice

Testcontainers Cloud is a cloud-based service designed to simplify and enhance your container-based testing. By offloading container execution to the cloud, it provides a secure, scalable, and efficient environment for your integration tests.

How TestContainers Cloud addresses DinD’s shortcomings

Enhanced security

No more privileged mode: Eliminates the need for running containers in privileged mode, reducing the attack surface.

Isolation: Tests run in isolated cloud environments, minimizing risks to the host system.

Compliance-friendly: Easier to pass security audits without exposing the Docker socket or granting elevated permissions.

Improved performance

Scalability: Leverage cloud resources to run tests faster and handle higher loads.

Resource efficiency: Offloading execution frees up local and CI/CD resources.

Simplified configuration

Plug-and-play integration: Minimal changes are required to switch from local Docker to Testcontainers Cloud.

No nested complexity: Avoid the intricacies and pitfalls of nested Docker daemons.

Better observability and debugging

Detailed logs: Access comprehensive logs through the Testcontainers Cloud dashboard.

Real-time monitoring: Monitor containers and resources in real time with enhanced visibility.

Getting started with Testcontainers Cloud

Let’s dive into how you can get the most out of Testcontainers Cloud.

Switching to Testcontainers Cloud allows you to run tests without needing a local Docker daemon:

No local Docker required: Testcontainers Cloud handles container execution in the cloud.

Consistent environment: Ensures that your tests run in the same environment across different machines.

Additionally, you can easily integrate Testcontainers Cloud into your CI pipeline to run the same tests without scaling your CI infrastructure.

Using Testcontainers Cloud with GitHub Actions

Here’s how you can set up Testcontainers Cloud in your GitHub Actions workflow.

1. Create a new service account

Log in to Testcontainers Cloud dashboard.

Navigate to Service Accounts:

Create a new service account dedicated to your CI environment.

Generate an access token:

Copy the access token. Remember, you can only view it once, so store it securely.

2. Set the TC_CLOUD_TOKEN environment variable

In GitHub Actions:

Go to your repository’s Settings > Secrets and variables > Actions.

Add a new Repository Secret named TC_CLOUD_TOKEN and paste the access token.

3. Add Testcontainers Cloud to your workflow

Update your GitHub Actions workflow (.github/workflows/ci.yml) to include the Testcontainers Cloud setup.

Example workflow:

name: CI Pipeline

on:
push:
branches: [ main ]
pull_request:
branches: [ main ]

jobs:
build:
runs-on: ubuntu-latest
steps:
– uses: actions/checkout@v3

# … other preparation steps (dependencies, compilation, etc.) …

– name: Set up Java
uses: actions/setup-java@v3
with:
distribution: 'temurin'
java-version: '17'

– name: Setup Testcontainers Cloud Client
uses: atomicjar/testcontainers-cloud-setup-action@v1
with:
token: ${{ secrets.TC_CLOUD_TOKEN }}

# … steps to execute your tests …
– name: Run Tests
run: ./mvnw test

Notes:

The atomicjar/testcontainers-cloud-setup-action GitHub Action automates the installation and authentication of the Testcontainers Cloud Agent in your CI environment.

Ensure that your TC_CLOUD_TOKEN is kept secure using GitHub’s encrypted secrets.

Clarifying the components: Testcontainers Cloud Agent and Testcontainers Cloud

To make everything clear:

Testcontainers Cloud Agent (CLI in CI environments): In CI environments like GitHub Actions, you use the Testcontainers Cloud Agent (installed via the GitHub Action or command line) to connect your CI jobs to Testcontainers Cloud.

Testcontainers Cloud: The cloud service that runs your containers, offloading execution from your CI environment.

In CI environments:

Use the Testcontainers Cloud Agent (CLI) within your CI jobs.

Authenticate using the TC_CLOUD_TOKEN.

Tests executed in the CI environment will use Testcontainers Cloud.

Monitoring and debugging

Take advantage of the Testcontainers Cloud dashboard:

Session logs: View logs for individual test sessions.

Container details: Inspect container statuses and resource usage.

Debugging: Access container logs and output for troubleshooting.

Why developers prefer Testcontainers Cloud over DinD

Real-world impact

After integrating Testcontainers Cloud, our team observed the following:

Faster build times: Tests ran significantly faster due to optimized resource utilization.

Reduced maintenance: Less time spent on debugging and fixing CI pipeline issues.

Enhanced security: Eliminated the need for privileged mode, satisfying security audits.

Better observability: Improved logging and monitoring capabilities.

Addressing common concerns

Security and compliance

Data isolation: Each test runs in an isolated environment.

Encrypted communication: Secure data transmission.

Compliance: Meets industry-standard security practices.

Cost considerations

Efficiency gains: Time saved on maintenance offsets the cost.

Resource optimization: Reduces the need for expensive CI infrastructure.

Compatibility

Multi-language support: Works with Java, Node.js, Python, Go, .NET, and more.

Seamless integration: Minimal changes required to existing test code.

Conclusion

Switching to Testcontainers Cloud, with the help of the Testcontainers Cloud Agent, has been a game-changer for our team and many others in the industry. It addresses the key pain points associated with Docker-in-Docker and offers a secure, efficient, and developer-friendly alternative.

Key takeaways

Security: Eliminates the need for privileged containers and Docker socket exposure.

Performance: Accelerates test execution with scalable cloud resources.

Simplicity: Simplifies configuration and reduces maintenance overhead.

Observability: Enhances debugging with detailed logs and monitoring tools.

As someone who has navigated these challenges, I recommend trying Testcontainers Cloud. It’s time to move beyond the complexities of DinD and adopt a solution designed for modern development workflows.

Additional resources

Testcontainers Cloud documentation:

Getting started

Testcontainers library docs:

Java

Node.js

Python

Best practices:

Testcontainers Best Practices

Community support:

Join the Testcontainers Slack

GitHub discussions

Stack Overflow

Quelle: https://blog.docker.com/feed/

Learn How to Optimize Docker Hub Costs With Our Usage Dashboards

Effective infrastructure management is crucial for organizations using Docker Hub. Without a clear understanding of resource consumption, unexpected usage can emerge and skyrocket. This is particularly true if pulls and storage needs are not budgeted and forecasted correctly. By implementing proactive post controls and monitoring usage patterns, development teams can sustain their Docker Hub usage while keeping expenses under control. 

To support these goals, we’ve introduced new Docker Hub Usage dashboards, offering organizations the ability to access and analyze their usage patterns for storage and pulls. 

Docker Hub’s Usage dashboards put you in control, giving visibility into every pull and image your Docker systems request. Each pull and cache becomes a deliberate choice — not a random event — so you can make every byte count. With clear insights into what’s happening and why, you can design more efficient, optimized systems.

Reclaim control and manage technical resources by kicking bad habits

Figure 1: Docker Hub Usage dashboards.

The Docker Hub Usage dashboards (Figure 1) provide valuable insights, allowing teams to track peaks and valleys, detect high usage periods, and identify the images and repositories driving the most consumption. This visibility not only aids in managing usage but also strengthens continuous improvement efforts across your software supply chain, helping teams build applications more efficiently and sustainably. 

This information helps development teams to stay on top of challenges, such as: 

Redundant pulls and misconfigured repositories: These can quickly and quietly drive up technical expenses while falling out of scope of the most relevant or critical use cases. Docker Hub’s Usage dashboards can help development teams identify patterns and optimize accordingly. They let you view usage trends across IPs and users as well, which helps with pinpointing high consumption areas and ensuring accountability in an organization when it comes to resource management. 

Poor caching management: Repository insights and image tagging helps customers assess internal usage patterns, such as frequently accessed images, where there might be an opportunity to improve caching. With proper governance models, organizations can also establish policies and processes that reduce the variability of resource usage as a whole. This goal goes beyond keeping track of seasonality usage patterns to help you design more predictable usage patterns so you can budget accordingly. 

Accidental automation: Accidental automated system activities can really hurt your usage. Let’s say you are using a CI/CD pipeline or automated scripts configured to pull images more often than they should. They may pull on every build instead of the actual version change, for example. 

Usage dashboards can help you identify these inefficiencies by showing detailed pull data associated with automated tooling. This information can help your teams quickly identify and adjust misconfigured systems, fine-tune automations to only pull when needed, and ultimately focus on the most relevant use cases for your organization, avoiding accidental overuse of resources:

Figure 2: Details from the Usage dashboards.

Docker Hub’s Usage dashboards offer a comprehensive view of your usage data, including downloadable CSV reports that include metrics such as pull counts, repository names, IP addresses, and version checks (Figure 2). This granular approach allows your organization to gain valuable insights and trend data to help optimize your team’s workflows and inform policies. 

Integrate robust operational principles into your development pipeline by leveraging these data-driven reports and maintain control over resource consumption and operational efficiency with Docker Hub. 

Learn more

Subscribe to the Docker Newsletter. 

View Docker Hub Usage dashboards.

Take steps to optimize and manage your usage.

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Accelerating AI Development with the Docker AI Catalog

Developers are increasingly expected to integrate AI capabilities into their applications but they also face many challenges. Namely, the steep learning curve, coupled with an overwhelming array of tools and frameworks, makes this process too tedious. Docker aims to bridge this gap with the Docker AI Catalog, a curated experience designed to simplify AI development and empower both developers and publishers.

Why Docker for AI?

Docker and container technology has been a key technology used by developers at the forefront of AI applications for the past few years. Now, Docker is doubling down on that effort with our AI Catalog. Developers using Docker’s suite of products are often responsible for building, deploying, and managing complex applications — and, now, they must also navigate generative AI (GenAI) technologies, such as large language models (LLMs), vector databases, and GPU support.

For developers, the AI Catalog simplifies the process of integrating AI into applications by providing trusted and ready-to-use content supported by comprehensive documentation. This approach removes the hassle of evaluating numerous tools and configurations, allowing developers to focus on building innovative AI applications.

Key benefits for development teams

The Docker AI Catalog is tailored to help users overcome common hurdles in the evolving AI application development landscape, such as:

Decision overload: The GenAI ecosystem is crowded with new tools and frameworks. The Docker AI Catalog simplifies the decision-making process by offering a curated list of trusted content and container images, so developers don’t have to wade through endless options.

Steep learning curve: With the rise of new technologies like LLMs and retrieval-augmented generation (RAG), the learning curve can be overwhelming. Docker provides an all-in-one resource to help developers quickly get up to speed.

Complex configurations preventing production readiness: Running AI applications often requires specialized hardware configurations, especially with GPUs. Docker’s AI stacks make this process more accessible, ensuring that developers can harness the full power of these resources without extensive setup.

The result? Shorter development cycles, improved productivity, and a more streamlined path to integrating AI into both new and existing applications.

Empowering publishers

For Docker verified publishers, the AI Catalog provides a platform to differentiate themselves in a crowded market. Independent software vendors (ISVs) and open source contributors can promote their content, gain insights into adoption, and improve visibility to a growing community of AI developers.

Key features for publishers include:

Increased discoverability: Publishers can highlight their AI content within a trusted ecosystem used by millions of developers worldwide.

Metrics and insights: Verified publishers gain valuable insights into the performance of their content, helping them optimize strategies and drive engagement.

Unified experience for AI application development

The AI Catalog is more than just a repository of AI tools. It’s a unified ecosystem designed to foster collaboration between developers and publishers, creating a path forward for more innovative approaches to building applications supported by AI capabilities. Developers get easy access to essential AI tools and content, while publishers gain the visibility and feedback they need to thrive in a competitive marketplace.

With Docker’s trusted platform, development teams can build AI applications confidently, knowing they have access to the most relevant and reliable tools available.

The road ahead: What’s next?

Docker will launch the AI Catalog in preview on November 12, 2024, alongside a joint webinar with MongoDB. This initiative will further Docker’s role as a leader in AI application development, ensuring that developers and publishers alike can take full advantage of the opportunities presented by AI tools.

Stay tuned for more updates and prepare to dive into a world of possibilities with the Docker AI Catalog. Whether you’re an AI developer seeking to streamline your workflows or a publisher looking to grow your audience, Docker has the tools and support you need to succeed.

Ready to simplify your AI development process? Explore the AI Catalog and get access to trusted content that will accelerate your development journey. Start building smarter, faster, and more efficiently.

For publishers, now is the perfect time to join the AI Catalog and gain visibility for your content. Become a trusted source in the AI development space and connect with millions of developers looking for the right tools to power their next breakthrough.

Learn more

Dive into the AI Catalog.

Join the AI Catalog.

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Better Together: Understanding the Difference Between Sign-In Enforcement and SSO

Docker Desktop’s single sign-on (SSO) and sign-in enforcement (also called login enforcement) features work together to enhance security and ease of use. SSO allows users to log in with corporate credentials, whereas login enforcement ensures every user is authenticated, giving IT tighter control over compliance. In this post, we’ll define each of these features, explain their unique benefits, and show how using them together streamlines management and improves your Docker Desktop experience.

Before diving into the benefits of login alongside SSO, let’s clarify three related terms: login, single sign-on (SSO), and enforced login.

Login: Logging in connects users to Docker’s suite of tools, enabling access to personalized settings, team resources, and features like Docker Scout and Docker Build Cloud. By default, members of an organization can use Docker Desktop without signing in. Logging in can be done through SSO or by using Docker-specific credentials.

Single sign-on (SSO): SSO allows users to access Docker using their organization’s central authentication system, letting teams streamline access across multiple platforms with one set of credentials. SSO standardizes and secures login and supports automation around provisioning but does not automatically log in users unless enforced.

Enforced login: This policy, configured by administrators, ensures users are logged in by requiring login credentials before accessing Docker Desktop and associated tools. With enforced login, teams gain consistent access to Docker’s productivity and security features, minimizing gaps in visibility and control.

With these definitions in mind, here’s why being logged in matters, how SSO simplifies login, and how login enforcement ensures your team gets the full benefit of Docker’s powerful development tools.

Why logging in matters for admins and compliance teams

Enforcing sign-in with corporate credentials ensures that all users accessing Docker Desktop are verified and utilizing the benefits of your Docker Business subscription while adding a layer of security to safeguard your software supply chain. This policy strengthens your organization’s security posture and enables Docker to provide detailed usage insights, helping compliance teams track engagement and adoption. 

Enforced login will support cloud-based control over settings, allowing admins to manage application configurations across the organization more effectively. By requiring login, your organization benefits from greater transparency, control, and alignment with compliance standards. 

When everyone in your organization signs in with proper credentials:

Access controls for shared resources become more reliable, allowing administrators to enforce policies and permissions consistently.

Developers stay connected to their workspaces and resources, minimizing disruptions.

Desktop Insights Dashboard provides admins actionable insights into usage, from feature adoption to image usage trends and login activity, helping administrators optimize team performance and security.

Teams gain full visibility and access to Docker Scout’s security insights, which only function with logged-in accounts.

Read more about the benefits of login on our blog post, Maximizing Docker Desktop: How Signing In Unlocks Advanced Features.

Options for enforcing sign-in

Docker provides three options to help administrators enforce sign-in. 

Registry key method (Windows Only): Integrates seamlessly with Windows, letting IT enforce login policies within familiar registry settings, saving time on configuration. 

Plist or config profiles method (Mac): Provides an easy way for IT to manage access on macOS, ensuring policy consistency across Apple devices without additional tools. 

Registry.json method (all platforms): Works across Windows, macOS, and Linux, allowing IT to enforce login on all platforms with a single, flexible configuration file, streamlining policy management for diverse environments.

Each method helps IT secure access, restrict to authorized users, and maintain compliance across all systems. You can enforce login without setting up SSO. Read the documentation to learn more about Docker’s sign-in enforcement methods.  

Single sign-on (SSO) 

Docker Desktop’s SSO capabilities allow organizations to streamline access by integrating with corporate identity providers, ensuring that only authorized team members can access Docker resources using their work credentials. This integration enhances security by eliminating the need for separate Docker-specific passwords, reducing the risk of unauthorized access to critical development tools. With SSO, admins can enforce consistent login policies across teams, simplify user management, and gain greater control over who accesses Docker Desktop. Additionally, SSO enables compliance teams to track access and usage better, aligning with organizational security standards and improving overall security posture.

Docker Desktop supports SSO integrations with a variety of idPs, including Okta, OneLogin, Auth0, and Microsoft Entra ID. By integrating with these IdPs, organizations can streamline user authentication, enhance security, and maintain centralized access control across their Docker environments.

Differences between SSO enforcement and SSO enablement

SSO and SCIM give your company more control over how users log in and attach themselves to your organization and Docker subscription but do not require your users to sign in to your organization when using Docker Desktop. Without sign-in enforcement, users can continue to utilize Docker Desktop without logging in or using their personal Docker IDs or subscriptions, preventing Docker from providing you with insights into their usage and control over the application. 

SSO enforcement usually applies to identity management across multiple applications, enforcing a single, centralized login for a suite of apps or services. However, a registry key or other local login enforcement mechanism typically applies only to that specific application (e.g., Docker Desktop) and doesn’t control access across different services.

Better together: Sign-in enforcement and SSO 

While SSO enables seamless access to Docker for those who choose to log in, enforcing login ensures that users fully benefit from Docker’s productivity and security features.

Docker’s SSO integration is designed to simplify enterprise user management, allowing teams to access Docker with their organization’s centralized credentials. This streamlines onboarding and minimizes password management overhead, enhancing security across the board. However, SSO alone doesn’t require users to log in — it simply makes it more convenient and secure. Without enforced login, users might bypass the sign-in process, missing out on Docker’s full benefits, particularly in areas of security and control.

By coupling SSO with login enforcement, organizations strengthen their Registry Access Management (RAM), ensuring access is restricted to approved registries, boosting image compliance, and centralizing control. Encouraging login alongside SSO ensures teams enjoy a seamless experience while unlocking Docker’s complete suite of features.

Learn more

Learn how to enforce sign-in for Docker Desktop.

Find out about single sign-on.

Read Maximizing Docker Desktop: How Signing In Unlocks Advanced Features.

Authenticate and update to receive your subscription level’s newest Docker Desktop features.

New to Docker? Create an account.

Subscribe to the Docker Newsletter.

Quelle: https://blog.docker.com/feed/

Dockerize WordPress: Simplify Your Site’s Setup and Deployment

If you’ve ever been tangled in the complexities of setting up a WordPress environment, you’re not alone. WordPress powers more than 40% of all websites, making it the world’s most popular content management system (CMS). Its versatility is unmatched, but traditional local development setups like MAMP, WAMP, or XAMPP can lead to inconsistencies and the infamous “it works on my machine” problem.

As projects scale and teams grow, the need for a consistent, scalable, and efficient development environment becomes critical. That’s where Docker comes into play, revolutionizing how we develop and deploy WordPress sites. To make things even smoother, we’ll integrate Traefik, a modern reverse proxy that automatically obtains TLS certificates, ensuring that your site runs securely over HTTPS. Traefik is available as a Docker Official Image from Docker Hub.

In this comprehensive guide, I’ll show how to Dockerize your WordPress site using real-world examples. We’ll dive into creating Dockerfiles, containerizing existing WordPress instances — including migrating your data — and setting up Traefik for automatic TLS certificates. Whether you’re starting fresh or migrating an existing site, this tutorial has you covered.

Let’s dive in!

Why should you containerize your WordPress site?

Containerizing your WordPress site offers a multitude of benefits that can significantly enhance your development workflow and overall site performance.

Increased page load speed

Docker containers are lightweight and efficient. By packaging your application and its dependencies into containers, you reduce overhead and optimize resource usage. This can lead to faster page load times, improving user experience and SEO rankings.

Efficient collaboration and version control

With Docker, your entire environment is defined as code. This ensures that every team member works with the same setup, eliminating environment-related discrepancies. Version control systems like Git can track changes to your Dockerfiles and to wordpress-traefik-letsencrypt-compose.yml, making collaboration seamless.

Easy scalability

Scaling your WordPress site to handle increased traffic becomes straightforward with Docker and Traefik. You can spin up multiple Docker containers of your application, and Traefik will manage load balancing and routing, all while automatically handling TLS certificates.

Simplified environment setup

Setting up your development environment becomes as simple as running a few Docker commands. No more manual installations or configurations — everything your application needs is defined in your Docker configuration files.

Simplified updates and maintenance

Updating WordPress or its dependencies is a breeze. Update your Docker images, rebuild your containers, and you’re good to go. Traefik ensures that your routes and certificates are managed dynamically, reducing maintenance overhead.

Getting started with WordPress, Docker, and Traefik

Before we begin, let’s briefly discuss what Docker and Traefik are and how they’ll revolutionize your WordPress development workflow.

Docker is a cloud-native development platform that simplifies the entire software development lifecycle by enabling developers to build, share, test, and run applications in containers. It streamlines the developer experience while providing built-in security, collaboration tools, and scalable solutions to improve productivity across teams.

Traefik is a modern reverse proxy and load balancer designed for microservices. It integrates seamlessly with Docker and can automatically obtain and renew TLS certificates from Let’s Encrypt.

How long will this take?

Setting up this environment might take around 45-60 minutes, especially if you’re integrating Traefik for automatic TLS certificates and migrating an existing WordPress site.

Documentation links

Docker documentation

Traefik documentation

WordPress Docker Bitnami image

Docker Compose documentation

Tools you’ll need

Docker Desktop: If you don’t already have the latest version installed, download and install Docker Desktop.

A domain name: Required for Traefik to obtain TLS certificates from Let’s Encrypt.

Access to DNS settings: To point your domain to your server’s IP address.

Code editor: Your preferred code editor for editing configuration files.

Command-line interface (CLI): Access to a terminal or command prompt.

Existing WordPress data: If you’re containerizing an existing site, ensure you have backups of your WordPress files and MySQL database.

What’s the WordPress Docker Bitnami image?

To simplify the process, we’ll use the Bitnami WordPress image from Docker Hub, which comes pre-packaged with a secure, optimized environment for WordPress. This reduces configuration time and ensures your setup is up to date with the latest security patches.

Using the Bitnami WordPress image streamlines your setup process by:

Simplifying configuration: Bitnami images come with sensible defaults and configurations that work out of the box, reducing the time spent on setup.

Enhancing security: The images are regularly updated to include the latest security patches, minimizing vulnerabilities.

Ensuring consistency: With a standardized environment, you avoid the “it works on my machine” problem and ensure consistency across development, staging, and production.

Including additional tools: Bitnami often includes helpful tools and scripts for backups, restores, and other maintenance tasks.

By choosing the Bitnami WordPress image, you can leverage a tested and optimized environment, reducing the risk of configuration errors and allowing you to focus more on developing your website.

Key features of Bitnami WordPress Docker image:

Optimized for production: Configured with performance and security in mind.

Regular updates: Maintained to include the latest WordPress version and dependencies.

Ease of use: Designed to be easy to deploy and integrate with other services, such as databases and reverse proxies.

Comprehensive documentation: Offers guides and support to help you get started quickly.

Why we use Bitnami in the examples:

In our Docker Compose configurations, we specified:

WORDPRESS_IMAGE_TAG=bitnami/wordpress:6.3.1

This indicates that we’re using the Bitnami WordPress image, version 6.3.1. The Bitnami image aligns well with our goals for a secure, efficient, and easy-to-manage WordPress environment, especially when integrating with Traefik for automatic TLS certificates.

By leveraging the Bitnami WordPress Docker image, you’re choosing a robust and reliable foundation for your WordPress projects. This approach allows you to focus on building great websites without worrying about the underlying infrastructure.

How to Dockerize an existing WordPress site with Traefik

Let’s walk through dockerizing your WordPress site using practical examples, including your .env and wordpress-traefik-letsencrypt-compose.yml configurations. We’ll also cover how to incorporate your existing data into the Docker containers.

Step 1: Preparing your environment variables

First, create a .env file in the same directory as your wordpress-traefik-letsencrypt-compose.yml file. This file will store all your environment variables.

Example .env file:

# Traefik Variables
TRAEFIK_IMAGE_TAG=traefik:2.9
TRAEFIK_LOG_LEVEL=WARN
TRAEFIK_ACME_EMAIL=your-email@example.com
TRAEFIK_HOSTNAME=traefik.yourdomain.com
# Basic Authentication for Traefik Dashboard
# Username: traefikadmin
# Passwords must be encoded using BCrypt https://hostingcanada.org/htpasswd-generator/
TRAEFIK_BASIC_AUTH=traefikadmin:$$2y$$10$$EXAMPLEENCRYPTEDPASSWORD

# WordPress Variables
WORDPRESS_MARIADB_IMAGE_TAG=mariadb:11.4
WORDPRESS_IMAGE_TAG=bitnami/wordpress:6.6.2
WORDPRESS_DB_NAME=wordpressdb
WORDPRESS_DB_USER=wordpressdbuser
WORDPRESS_DB_PASSWORD=your-db-password
WORDPRESS_DB_ADMIN_PASSWORD=your-db-admin-password
WORDPRESS_TABLE_PREFIX=wpapp_
WORDPRESS_BLOG_NAME=Your Blog Name
WORDPRESS_ADMIN_NAME=AdminFirstName
WORDPRESS_ADMIN_LASTNAME=AdminLastName
WORDPRESS_ADMIN_USERNAME=admin
WORDPRESS_ADMIN_PASSWORD=your-admin-password
WORDPRESS_ADMIN_EMAIL=admin@yourdomain.com
WORDPRESS_HOSTNAME=wordpress.yourdomain.com
WORDPRESS_SMTP_ADDRESS=smtp.your-email-provider.com
WORDPRESS_SMTP_PORT=587
WORDPRESS_SMTP_USER_NAME=your-smtp-username
WORDPRESS_SMTP_PASSWORD=your-smtp-password

Notes:

Replace placeholder values (e.g., your-email@example.com, your-db-password) with your actual credentials.

Do not commit this file to version control if it contains sensitive information.

Use a password encryption tool to generate the encrypted password for TRAEFIK_BASIC_AUTH. For example, you can use the htpasswd generator.

Step 2: Creating the Docker Compose file

Create a wordpress-traefik-letsencrypt-compose.yml file that defines your services, networks, and volumes. This YAML file is crucial for configuring your WordPress installation through Docker.

Example wordpress-traefik-letsencrypt-compose.yml.

networks:
wordpress-network:
external: true
traefik-network:
external: true

volumes:
mariadb-data:
wordpress-data:
traefik-certificates:

services:
mariadb:
image: ${WORDPRESS_MARIADB_IMAGE_TAG}
volumes:
– mariadb-data:/var/lib/mysql
environment:
MARIADB_DATABASE: ${WORDPRESS_DB_NAME}
MARIADB_USER: ${WORDPRESS_DB_USER}
MARIADB_PASSWORD: ${WORDPRESS_DB_PASSWORD}
MARIADB_ROOT_PASSWORD: ${WORDPRESS_DB_ADMIN_PASSWORD}
networks:
– wordpress-network
healthcheck:
test: ["CMD", "healthcheck.sh", "–connect", "–innodb_initialized"]
interval: 10s
timeout: 5s
retries: 3
start_period: 60s
restart: unless-stopped

wordpress:
image: ${WORDPRESS_IMAGE_TAG}
volumes:
– wordpress-data:/bitnami/wordpress
environment:
WORDPRESS_DATABASE_HOST: mariadb
WORDPRESS_DATABASE_PORT_NUMBER: 3306
WORDPRESS_DATABASE_NAME: ${WORDPRESS_DB_NAME}
WORDPRESS_DATABASE_USER: ${WORDPRESS_DB_USER}
WORDPRESS_DATABASE_PASSWORD: ${WORDPRESS_DB_PASSWORD}
WORDPRESS_TABLE_PREFIX: ${WORDPRESS_TABLE_PREFIX}
WORDPRESS_BLOG_NAME: ${WORDPRESS_BLOG_NAME}
WORDPRESS_FIRST_NAME: ${WORDPRESS_ADMIN_NAME}
WORDPRESS_LAST_NAME: ${WORDPRESS_ADMIN_LASTNAME}
WORDPRESS_USERNAME: ${WORDPRESS_ADMIN_USERNAME}
WORDPRESS_PASSWORD: ${WORDPRESS_ADMIN_PASSWORD}
WORDPRESS_EMAIL: ${WORDPRESS_ADMIN_EMAIL}
WORDPRESS_SMTP_HOST: ${WORDPRESS_SMTP_ADDRESS}
WORDPRESS_SMTP_PORT: ${WORDPRESS_SMTP_PORT}
WORDPRESS_SMTP_USER: ${WORDPRESS_SMTP_USER_NAME}
WORDPRESS_SMTP_PASSWORD: ${WORDPRESS_SMTP_PASSWORD}
networks:
– wordpress-network
– traefik-network
healthcheck:
test: timeout 10s bash -c ':> /dev/tcp/127.0.0.1/8080' || exit 1
interval: 10s
timeout: 5s
retries: 3
start_period: 90s
labels:
– "traefik.enable=true"
– "traefik.http.routers.wordpress.rule=Host(`${WORDPRESS_HOSTNAME}`)"
– "traefik.http.routers.wordpress.service=wordpress"
– "traefik.http.routers.wordpress.entrypoints=websecure"
– "traefik.http.services.wordpress.loadbalancer.server.port=8080"
– "traefik.http.routers.wordpress.tls=true"
– "traefik.http.routers.wordpress.tls.certresolver=letsencrypt"
– "traefik.http.services.wordpress.loadbalancer.passhostheader=true"
– "traefik.http.routers.wordpress.middlewares=compresstraefik"
– "traefik.http.middlewares.compresstraefik.compress=true"
– "traefik.docker.network=traefik-network"
restart: unless-stopped
depends_on:
mariadb:
condition: service_healthy
traefik:
condition: service_healthy

traefik:
image: ${TRAEFIK_IMAGE_TAG}
command:
– "–log.level=${TRAEFIK_LOG_LEVEL}"
– "–accesslog=true"
– "–api.dashboard=true"
– "–api.insecure=true"
– "–ping=true"
– "–ping.entrypoint=ping"
– "–entryPoints.ping.address=:8082"
– "–entryPoints.web.address=:80"
– "–entryPoints.websecure.address=:443"
– "–providers.docker=true"
– "–providers.docker.endpoint=unix:///var/run/docker.sock"
– "–providers.docker.exposedByDefault=false"
– "–certificatesresolvers.letsencrypt.acme.tlschallenge=true"
– "–certificatesresolvers.letsencrypt.acme.email=${TRAEFIK_ACME_EMAIL}"
– "–certificatesresolvers.letsencrypt.acme.storage=/etc/traefik/acme/acme.json"
– "–metrics.prometheus=true"
– "–metrics.prometheus.buckets=0.1,0.3,1.2,5.0"
– "–global.checkNewVersion=true"
– "–global.sendAnonymousUsage=false"
volumes:
– /var/run/docker.sock:/var/run/docker.sock
– traefik-certificates:/etc/traefik/acme
networks:
– traefik-network
ports:
– "80:80"
– "443:443"
healthcheck:
test: ["CMD", "wget", "http://localhost:8082/ping","–spider"]
interval: 10s
timeout: 5s
retries: 3
start_period: 5s
labels:
– "traefik.enable=true"
– "traefik.http.routers.dashboard.rule=Host(`${TRAEFIK_HOSTNAME}`)"
– "traefik.http.routers.dashboard.service=api@internal"
– "traefik.http.routers.dashboard.entrypoints=websecure"
– "traefik.http.services.dashboard.loadbalancer.server.port=8080"
– "traefik.http.routers.dashboard.tls=true"
– "traefik.http.routers.dashboard.tls.certresolver=letsencrypt"
– "traefik.http.services.dashboard.loadbalancer.passhostheader=true"
– "traefik.http.routers.dashboard.middlewares=authtraefik"
– "traefik.http.middlewares.authtraefik.basicauth.users=${TRAEFIK_BASIC_AUTH}"
– "traefik.http.routers.http-catchall.rule=HostRegexp(`{host:.+}`)"
– "traefik.http.routers.http-catchall.entrypoints=web"
– "traefik.http.routers.http-catchall.middlewares=redirect-to-https"
– "traefik.http.middlewares.redirect-to-https.redirectscheme.scheme=https"
restart: unless-stopped

Notes:

Networks: We’re using external networks (wordpress-network and traefik-network). We’ll create these networks before deploying.

Volumes: Volumes are defined for data persistence.

Services: We’ve defined mariadb, wordpress, and traefik services with the necessary configurations.

Health checks: Ensure that services are healthy before dependent services start.

Labels: Configure Traefik routing, HTTPS settings, and enable the dashboard with basic authentication.

Step 3: Creating external networks

Before deploying your Docker Compose configuration, you need to create the external networks specified in your wordpress-traefik-letsencrypt-compose.yml.

Run the following commands to create the networks:

docker network create traefik-network
docker network create wordpress-network

Step 4: Deploying your WordPress site

Deploy your WordPress site using Docker Compose with the following command (Figure 1):

docker compose -f wordpress-traefik-letsencrypt-compose.yml -p website up -d

Figure 1: Using Docker Compose to deploy your WordPress site.

Explanation:

-f wordpress-traefik-letsencrypt-compose.yml: Specifies the Docker Compose file to use.

-p website: Sets the project name to website.

up -d: Builds, (re)creates, and starts containers in detached mode.

Step 5: Verifying the deployment

Check that all services are running (Figure 2):

docker ps

Figure 2: Services running.

You should see the mariadb, wordpress, and traefik services up and running.

Step 6: Accessing your WordPress site and Traefik dashboard

WordPress site: Navigate to https://wordpress.yourdomain.com in your browser. Type in the username and password you set earlier in the .env file and click the Log In button. You should see your WordPress site running over HTTPS, with a valid TLS certificate automatically obtained by Traefik (Figure 3).

Figure 3: WordPress dashboard.

Important: To get cryptographic certificates, you need to set up A-type records in your external DNS zone that point to your server’s IP address where Traefik is installed. If you’ve just set up these records, wait a bit before starting the service installation because it can take anywhere from a few minutes to 48 hours — sometimes even longer — for these changes to fully spread across DNS servers.

Traefik dashboard: Access the Traefik dashboard at https://traefik.yourdomain.com. You’ll be prompted for authentication. Use the username and password specified in your .env file (Figure 4).

Figure 4: Traefik dashboard.

Step 7: Incorporating your existing WordPress data

If you’re migrating an existing WordPress site, you’ll need to incorporate your existing files and database into the Docker containers.

Step 7.1: Restoring WordPress files

Copy your existing WordPress files into the wordpress-data volume.

Option 1: Using Docker volume mapping

Modify your wordpress-traefik-letsencrypt-compose.yml to map your local WordPress files directly:

volumes:
– ./your-wordpress-files:/bitnami/wordpress

Option 2: Copying files into the running container

Assuming your WordPress backup is in ./wordpress-backup, run:

docker cp ./wordpress-backup/. wordpress_wordpress_1:/bitnami/wordpress/

Step 7.2: Importing your database

Export your existing WordPress database using mysqldump or phpMyAdmin.

Example:

mysqldump -u your_db_user -p your_db_name > wordpress_db_backup.sql

Copy the database backup into the MariaDB container:

docker cp wordpress_db_backup.sql wordpress_mariadb_1:/wordpress_db_backup.sql

Access the MariaDB container:

docker exec -it wordpress_mariadb_1 bash

Import the database:

mysql -u root -p${WORDPRESS_DB_ADMIN_PASSWORD} ${WORDPRESS_DB_NAME} < wordpress_db_backup.sql

Step 7.3: Update wp-config.php (if necessary)

Because we’re using environment variables, WordPress should automatically connect to the database. However, if you have custom configurations, ensure they match the settings in your .env file.

Note: The Bitnami WordPress image manages wp-config.php automatically based on environment variables. If you need to customize it further, you can create a custom Dockerfile.

Step 8: Creating a custom Dockerfile (optional)

If you need to customize the WordPress image further, such as installing additional PHP extensions or modifying configuration files, create a Dockerfile in your project directory.

Example Dockerfile:

# Use the Bitnami WordPress image as the base
FROM bitnami/wordpress:6.3.1

# Install additional PHP extensions if needed
# RUN install_packages php7.4-zip php7.4-mbstring

# Copy custom wp-content (if not using volume mapping)
# COPY ./wp-content /bitnami/wordpress/wp-content

# Set working directory
WORKDIR /bitnami/wordpress

# Expose port 8080
EXPOSE 8080

Build the custom image:

Modify your wordpress-traefik-letsencrypt-compose.yml to build from the Dockerfile:

wordpress:
build: .
# Rest of the configuration

Then, rebuild your containers:

docker compose -p wordpress up -d –build

Step 9: Customizing WordPress within Docker

Adding themes and plugins

Because we’ve mapped the wordpress-data volume, any changes you make within the WordPress container (like installing plugins or themes) will persist across container restarts.

Via WordPress admin dashboard: Install themes and plugins as you normally would through the WordPress admin interface (Figure 5).

Figure 5: Adding plugins.

Manually: Access the container and place your themes or plugins directly.

Example:

docker exec -it wordpress_wordpress_1 bash
cd /bitnami/wordpress/wp-content/themes
# Add your theme files here

Managing and scaling WordPress with Docker and Traefik

Scaling your WordPress service

To handle increased traffic, you might want to scale your WordPress instances.

docker compose -p wordpress up -d –scale wordpress=3

Traefik will automatically detect the new instances and load balance traffic between them.

Note: Ensure that your WordPress setup supports scaling. You might need to externalize session storage or use a shared filesystem for media uploads.

Updating services

To update your services to the latest images:

Pull the latest images:

docker compose -p wordpress pull

Recreate containers:

docker compose -p wordpress up -d

Monitoring and logs

Docker logs:View logs for a specific service:

docker compose -p wordpress logs -f wordpress

Traefik dashboard:Use the Traefik dashboard to monitor routing, services, and health checks.

Optimizing your WordPress Docker setup

Implementing caching with Redis

To improve performance, you can add Redis for object caching.

Update wordpress-traefik-letsencrypt-compose.yml:

services:
redis:
image: redis:alpine
networks:
– wordpress-network
restart: unless-stopped

Configure WordPress to use Redis:

Install a Redis caching plugin like Redis Object Cache.

Configure it to connect to the redis service.

Security best practices

Secure environment variables:

Use Docker secrets or environment variables to manage sensitive information securely.

Avoid committing sensitive data to version control.

Restrict access to Docker socket:

The Docker socket is mounted read-only (:ro) to minimize security risks.

Keep images updated:

Regularly update your Docker images to include security patches and improvements.

Advanced Traefik configurations

Middleware: Implement middleware for rate limiting, IP whitelisting, and other request transformations.

Monitoring: Integrate with monitoring tools like Prometheus and Grafana for advanced insights.

Wildcard certificates: Configure Traefik to use wildcard certificates if you have multiple subdomains.

Wrapping up

Dockerizing your WordPress site with Traefik simplifies your development and deployment processes, offering consistency, scalability, and efficiency. By leveraging practical examples and incorporating your existing data, we’ve created a tailored guide to help you set up a robust WordPress environment.

Whether you’re managing an existing site or starting a new project, this setup empowers you to focus on what you do best — developing great websites — while Docker and Traefik handle the heavy lifting.

So go ahead, give it a shot! Embracing these tools is a step toward modernizing your workflow and staying ahead in the ever-evolving tech landscape.

Learn more

To further enhance your skills and optimize your setup, check out these resources:

Subscribe to the Docker Newsletter

Get the latest release of Docker Desktop

Docker documentation

Compose file reference

WordPress Docker Bitnami image

Traefik documentation

Understand Docker networking

Manage sensitive data with Docker secrets

WordPress plugins for Docker

Redis object cache plugin

Have questions? The Docker community is here to help.

New to Docker? Get started.

Quelle: https://blog.docker.com/feed/

Using AI Tools to Convert a PDF into Images

This ongoing Docker Labs GenAI series explores the exciting space of AI developer tools. At Docker, we believe there is a vast scope to explore, openly and without the hype. We will share our explorations and collaborate with the developer community in real time. Although developers have adopted autocomplete tooling like GitHub Copilot and use chat, there is significant potential for AI tools to assist with more specific tasks and interfaces throughout the entire software lifecycle. Therefore, our exploration will be broad. We will be releasing software as open source so you can play, explore, and hack with us, too.

How do you turn a PDF into a set of images? A modern suggestion could be to get Claude or GPT to write you a CLI command for something like ImageMagick. Let’s follow that train of thought.

If we enter a prompt like “How do I turn a PDF into a bunch of images using ImageMagick,” we will indeed get something that looks like it might be a solution.

Imagemagick includes a command-line tool called convert which you can use to convert PDF files into images. Here's how you can do it:

1. Open your terminal

2. Change directory to where your PDF is located:

“`
cd /path/to/your/pdf

“`
3. Use the following command to convert the PDF into images (in this case JPEG):

“`
convert -density 300 -quality 100 your_file.pdf output_name.jpg

“`

The agent will then explain how convert works and finish with a suggestion to “please make sure that you have installed ImageMagick before running these commands.”

Instead of worrying about whether ImageMagick is installed, however, let’s use Docker as our tool provider and prompt it to go ahead and run the command. If you’re following along in this series, you’ll have seen that we are using Markdown files to mix together tools and prompts.  Here’s the first prompt we tried:


tools:
– name: imagemagick

# prompt user

Use Imagemagick to convert the family.pdf file into a bunch of jpg images.

After executing this prompt, the LLM generated a tool call, which we executed in the Docker runtime, and it successfully converted family.pdf into nine .jpg files (my family.pdf file had nine pages). 

Figure 1 shows the flow from our VSCode Extension.

Figure 1: Workflow from VSCode Extension.

We have given enough context to the LLM that it is able to plan a call to this ImageMagick binary. And, because this tool is available on Docker Hub, we don’t have to “make sure that ImageMagick is installed.” This would be the equivalent command if you were to use docker run directly:

# family.pdf must be located in your $PWD

docker run –rm -v $PWD:/project –workdir /project vonwig/imageMagick:latest convert -density 300 -quality 300 family.pdf family.jpg

The tool ecosystem

How did this work? The process relied on two things:

Tool distribution and discovery (pulling tools into Docker Hub for distribution to our Docker Desktop runtime).

Automatic generation of Agent Tool interfaces.

When we first started this project, we expected that we’d begin with a small set of tools because the interface for each tool would take time to design. We thought we were going to need to bootstrap an ecosystem of tools that had been prepared to be used in these agent workflows. 

However, we learned that we can use a much more generic approach. Most tools already come with documentation, such as command-line help, examples, and man pages. Instead of treating each tool as something special, we are using an architecture where an agent responds to failures by reading documentation and trying again (Figure 2).

Figure 2: Agent process.

We see a process of experimenting with tools that is not unlike what we, as developers, do on the command line. Try a command line, read a doc, adjust the command line, and try again.

The value of this kind of looping has changed our expectations. Step one is simply pulling the tool into Docker Hub and seeing whether the agent can use it with nothing more than its out-of-the-box documentation. We are also pulling open source software (OSS)  tools directly from nixpkgs, which gives us access to tens of thousands of different tools to experiment with. 

Docker keeps our runtimes isolated from the host operating system, while the nixpkgs ecosystem and maintainers provide a rich source of OSS tools.

As expected, packaging agents still run into issues that force us to re-plan how tools are packaged. For example, the prompt we showed above might have generated the correct tool call on the first try, but the ImageMagick container failed on the first run with this terrible-looking error message:

function call failed call exited with non-zero code (1): Error: sh: 1: gs: not found

Fortunately, feeding that error back into the LLM resulted in the suggestion that convert needs another tool, called Ghostscript, to run successfully. Our agent was not able to fix this automatically today. However, we adjusted the image build slightly and now the “latest” version of the vonwig/imagemagick:latest no longer has this issue. This is an example of something we only need to learn once.

The LLM figured out convert on its own. But its agency came from the addition of a tool.

Read the Docker Labs GenAI series to see more of what we’ve been working on.

Learn more

Subscribe to the Docker Newsletter. 

Get the latest release of Docker Desktop.

Have questions? The Docker community is here to help.

New to Docker? Get started.

Quelle: https://blog.docker.com/feed/

Maximizing Docker Desktop: How Signing In Unlocks Advanced Features

Docker Desktop is more than just a local application for containerized development — it’s your gateway to an integrated suite of cloud-native tools that streamline the entire development workflow. While Docker Desktop can be used without signing in, doing so unlocks the full potential of Docker’s powerful, interconnected ecosystem. By signing in, you gain access to advanced features and services across Docker Hub, Build Cloud, Scout, and Testcontainers Cloud, enabling deeper collaboration, enhanced security insights, and scalable cloud resources. 

This blog post explores the full range of capabilities unlocked by signing in to Docker Desktop, connecting you to Docker’s integrated suite of cloud-native development tools. From enhanced security insights with Docker Scout to scalable build and testing resources through Docker Build Cloud and Testcontainers Cloud, signing in allows developers and administrators to fully leverage Docker’s unified platform.

Note that the following sections refer to specific Docker subscription plans. With Docker’s newly streamlined subscription plans — Docker Personal, Docker Pro, Docker Team, and Docker Business — developers and organizations can access a scalable suite of tools, from individual productivity boosters to enterprise-grade governance and security. Visit the Docker pricing page to learn more about how these plans support different team sizes and workflows. 

Benefits for developers when logged in

Docker Personal

Access to private repositories: Unlock secure collaboration through private repositories on Docker Hub, ensuring that your sensitive code and dependencies are managed securely across teams and projects.

Increased pull rate: Boost your productivity with an increased pull rate from Docker Hub (40 pulls/hour per user), ensuring smoother, uninterrupted development workflows without waiting on rate limits. The rate limit without authentication is 10 pulls/hour per IP.

Docker Scout CLI: Leverage Docker Scout to proactively secure your software supply chain with continuous security insights from code to production. By signing in, you gain access to powerful CLI commands that help prevent vulnerabilities before they reach production. 

Build Cloud and Testcontainers Cloud: Experience the full power of Docker Build Cloud and Testcontainers Cloud with free trials (7-day for Build Cloud, 30-day for Testcontainers Cloud). These trials give you access to scalable cloud infrastructure that speeds up image builds and enables more reliable integration testing.

Docker Pro/Team/Business 

For users with a paid Docker subscription, additional features are unlocked.

Unlimited pull rate: No Hub rate limit will be enforced for users with a paid subscription plan. 

Docker Scout base image recommendations: Docker Scout offers continuous recommendations for base image updates, empowering developers to secure their applications at the foundational level and fix vulnerabilities early in the development lifecycle.

Figure 1: Docker Scout showing recommendations.

Docker Debug: The docker debug CLI command can help you debug containers, while the images contain the minimum required to run your application.

FIgure 2: Docker debug CLI.

Docker Debug functionalities have also been integrated into the container view of the Docker Desktop UI.

Figure 3: Debug functionalities integrated into the container view of Docker Desktop.

Synchronized file shares: Host to Docker Desktop VM file sharing via bind mounts can be quite slow for large codebases. Speed up your development cycle with synchronized file shares, allowing you to sync large codebases into containers quickly and efficiently without performance bottlenecks—helping developers iterate faster on critical projects.

Figure 4: Synchronized file shares.

Additional free minutes for Docker Build Cloud: Docker Build Cloud helps developer teams speed up image builds by offloading the build process to the cloud. The following benefits are available for users depending on the subscription plan. 

Docker Pro: 200 mins/month per org

Docker Team: 500 mins/month per org

Docker Business: 1500 mins/month per org

Additional free minutes for Testcontainers Cloud: Testcontainers Cloud simplifies the process for developers to run reliable integration tests using real dependencies defined in code, whether on their laptops or within their team’s CI pipeline. Depending on the subscription plan, the following benefits are available for users:

Docker Pro: 100 mins/month per org

Docker Team: 500 mins/month per org

Docker Business: 1,500 mins/month per org

Benefits for administrators when your users are logged in

Docker Business

Security and governance

The Docker Business plan offers enterprise-grade security and governance controls, which are only applicable if users are signed in. As of Docker Desktop 4.35.0, these features include:

Image Access Management and Registry Access Management: Enhance security governance by controlling exactly which images and registries your developers can access or push to, ensuring compliance with organizational security policies and minimizing risk exposure.

Settings management: Enforce organization-wide security policies by locking default settings across Docker Desktop instances, ensuring consistent configuration and compliance throughout your team’s development environment.

Enhanced Container Isolation: Protect developer environments from malicious containers with rootless containers and much more.

Air-gapped containers: Restrict network activity originating from containers.

Private extensions marketplace: Limit Docker Desktop extensions that developers can install.

Kerberos and NTLM authentication for proxies: Centralize Docker Desktop authentication to network proxies without prompts.

SOCKS5 proxy support: Enable the usage of SOCKS5 proxies for Docker Desktop.

License management

Tracking usage for licensing purposes can be challenging for administrators due to Docker Desktop not requiring authentication by default. By ensuring all users are signed in, administrators can use Docker Hub’s organization members list to manage licenses effectively.

This can be coupled with Docker Business’s Single Sign-On and SCIM capabilities to ease this process further. 

Insights

Administrators and other stakeholders (such as engineering managers) must comprehensively understand Docker Desktop usage within their organization. With developers signed into Docker Desktop, admins gain actionable insights into usage, from feature adoption to image usage trends and login activity, helping administrators optimize team performance and security. A dashboard offering insights is now available to simplify monitoring. Contact your account rep to enable the dashboard.

Figure 5: Desktop Insights view when users log in to your organization.

Enforce sign-in for Docker Desktop

Docker Desktop includes a feature that allows administrators to require authentication at start-up. Admins can ensure that all developers sign in to access Docker Desktop, enabling full integration with Docker’s security and productivity features. Sign-in enforcement helps maintain continuous compliance with governance policies across the organization.

Figure 6: Prompting sign in.

Developers can then click on the sign-in button, which takes them through the authentication flow. 

More information on how to enforce sign-in can be found in the documentation. 

Unlock the full potential of Docker’s integrated suite

Signing into Docker Desktop unlocks significant benefits for both developers and administrators, enabling teams to fully leverage Docker’s integrated, cloud-native suite. Whether improving productivity, securing the software supply chain, or enforcing governance policies, signing in maximizes the value of Docker’s unified platform — especially for organizations using Docker’s paid subscription plans.

Note that new features are introduced with each new release, so keep an eye on our blog and subscribe to the Docker Newsletter for the latest product and feature updates.

Up next

Read Announcing Upgraded Docker Plans: Simpler, More Value, Better Development and Productivity.

Learn more about the new Docker subscriptions.

Get started with Docker Desktop.

Subscribe to the Docker Newsletter.

Quelle: https://blog.docker.com/feed/

Docker Desktop 4.35: Organization Access Tokens, Docker Home, Volumes Export, and Terminal in Docker Desktop

Key features of the Docker Desktop 4.35 release include: 

Secure development environments with organization access tokens (Beta) 

Docker Home enhances your Docker experience (Beta) 

Accelerate development with a terminal in Docker Desktop (GA)  

Volumes Export (GA)

Improved performance on macOS

Docker Desktop for Red Hat Enterprise Linux

Organization access tokens (Beta) 

Before the beta release of organization access tokens, managing developer access to Docker resources was challenging, as it relied heavily on individual user accounts, leading to security risks and administrative inefficiencies. 

Organization access tokens let you manage access at the organizational level, providing enhanced security. This feature allows teams to operate more securely and efficiently with centralized user management, reduced administrative overhead, and the flexibility to scale access as the organization grows. For businesses, this feature offers significant value by improving governance, enhancing security, and supporting scalable infrastructure from an administrative perspective. 

Organizational access tokens empower organizations to maintain tighter control over their resources and security, making Docker Desktop even more valuable for enterprise users. This is one piece of the continuous updates we’re releasing to support administrators across large enterprise companies, ensuring they have the tools needed to manage complex environments with efficiency and confidence.

Docker Home (Beta) 

Sign in to your Docker account to see the release of the new Docker Home page (Figure 1). The new Docker Home marks a milestone in Docker’s journey as a multi-product company, reinforcing Docker’s commitment to providing an expanding suite of solutions that help developers and businesses containerize applications with ease.

Unified experience: The home page provides a central hub for users to access Docker products, manage subscriptions, adjust settings, and find resources — all in one place. This approach simplifies navigation for developers and admins.

Admin access: Administrators can manage organizations, users, and onboarding processes through the new portal, with access to dashboards for monitoring Docker usage.

Future enhancements: Future updates will add personalized features for different roles, and business subscribers will gain access to tools like the Docker Support portal and organization-wide notifications.

Figure 1: New Docker home page.

Terminal experience in Docker Desktop

Our terminal feature in Docker Desktop is now generally available. While managing containerized applications, developers have often faced friction and inefficiencies when switching between the Docker Desktop CLI and GUI. This constant context switching disrupted workflows and reduced productivity. 

The terminal enhancement integrates a terminal directly within the Docker Desktop GUI, enabling seamless transitions between CLI and GUI interactions within a single window. By incorporating a terminal shell into the Docker Desktop interface (Figure 2), we significantly reduce the friction associated with context switching for developers.

Figure 2: Terminal shell in Docker Desktop.

This functionality is designed to streamline workflows, accelerate delivery times, and enhance overall developer productivity.

Volumes Export is GA 

With the 4.35 release, we’ve elevated volume backup capabilities in Docker Desktop, introducing an upgraded feature set (Figure 3). This enhancement directly integrates the previous Volumes Backup & Share extension directly into Docker Desktop, streamlining your backup processes.

Figure 3: Docker Desktop Volumes view showcasing new backup functionality.

Although this release marks a significant step forward, it’s just the beginning. We’re committed to expanding these capabilities, adding even more value in future updates. Check out the beta of Scheduled Backups as well as External Cloud Storage backups, which are also available. 

Significantly improved performance experience on macOS (Beta)

Docker Desktop 4.35 also includes a beta release of Docker VMM, a container-optimized hypervisor for Apple Silicon Macs. Local developer workflows rely heavily on the performance of the hypervisor layer for everything from handling individual timer interrupts to accessing files and downloading images from the network. 

Docker VMM allows us to optimize the Linux kernel and hypervisor layer together, massively improving the speed of many common developer tasks. For example, iterating over a large shared file system with find is now 2x faster than on Docker Desktop 4.34 with a cold cache and up to 25x faster — faster than running natively on the Mac — when the cache is warm. This is only the beginning. Thanks to Docker VMM, we have many exciting new performance improvements in the pipeline.

Enable Docker VMM via Settings > General > Virtual Machine options and try it for your developer workflows today (Figure 4).

Figure 4: Docker VMM.

Docker Desktop for Red Hat Enterprise Linux 

Today we are excited to announce the general availability of Docker Desktop for Red Hat Enterprise Linux (RHEL). This feature marks a great milestone for both Docker and our growing community of developers.

By making Docker Desktop available on RHEL, we’re not only extending our reach — we’re meeting developers where they are. RHEL users can now access a seamless containerized development experience directly on the same OS that might power their production environments.

Docker Desktop for RHEL (Figure 5) offers the same intuitive interface, integrated tooling, and performance optimizations that you’ve come to expect on the other supported Linux distributions.

Figure 5: Docker Desktop for RHEL.

How to install Docker Desktop on Red Hat Enterprise Linux

Download links and information can be found in our release notes. 

Looking for support?

Did you know that you can get Premium Customer Support for Docker Desktop with a Pro or Team subscription? With this GA release, we’re now ready to officially help support you if you’re thinking about using Docker Desktop. Check out our pricing page to learn more about what’s included in a Pro or Team subscription, and if it’s right for you.

Explore the latest updates

With this latest wave of updates, from the security enhancements of organization access tokens to the performance boost of Docker VMM for Apple Silicon Macs, we’re pushing Docker Desktop forward to meet the evolving needs of developers and organizations alike. Each new feature is designed to make development smoother, faster, and more secure — whether you’re managing large teams or optimizing your individual workflow. 

We’re continuing to make improvements, with more tools and features on the way to help you build, manage, and scale your projects efficiently. Explore the latest updates and see how they can enhance your development experience

Learn more

Subscribe to the Docker Newsletter.

Authenticate and update to receive your subscription level’s newest Docker Desktop features.

New to Docker? Create an account.

Learn more about host networking support.

Have questions? The Docker community is here to help.

Quelle: https://blog.docker.com/feed/

Model-Based Testing with Testcontainers and Jqwik

When testing complex systems, the more edge cases you can identify, the better your software performs in the real world. But how do you efficiently generate hundreds or thousands of meaningful tests that reveal hidden bugs? Enter model-based testing (MBT), a technique that automates test case generation by modeling your software’s expected behavior.

In this demo, we’ll explore the model-based testing technique to perform regression testing on a simple REST API.

We’ll use the jqwik test engine on JUnit 5 to run property and model-based tests. Additionally, we’ll use Testcontainers to spin up Docker containers with different versions of our application.

Model-based testing

Model-based testing is a method for testing stateful software by comparing the tested component with a model that represents the expected behavior of the system. Instead of manually writing test cases, we’ll use a testing tool that:

Takes a list of possible actions supported by the application

Automatically generates test sequences from these actions, targeting potential edge cases

Executes these tests on the software and the model, comparing the results

In our case, the actions are simply the endpoints exposed by the application’s API. For the demo’s code examples, we’ll use a basic service with a CRUD REST API that allows us to:

Find an employee by their unique employee number

Update an employee’s name

Get a list of all the employees from a department

Register a new employee

Figure 1: Finding an employee, updating their name, finding their department, and registering a new employee.

Once everything is configured and we finally run the test, we can expect to see a rapid sequence of hundreds of requests being sent to the two stateful services:

Figure 2: New requests being sent to the two stateful services.

Docker Compose

Let’s assume we need to switch the database from Postgres to MySQL and want to ensure the service’s behavior remains consistent. To test this, we can run both versions of the application, send identical requests to each, and compare the responses.

We can set up the environment using a Docker Compose that will run two versions of the app:

Model (mbt-demo:postgres): The current live version and our source of truth.

Tested version (mbt-demo:mysql): The new feature branch under test.

services:
## MODEL
app-model:
image: mbt-demo:postgres
# …
depends_on:
– postgres
postgres:
image: postgres:16-alpine
# …

## TESTED
app-tested:
image: mbt-demo:mysql
# …
depends_on:
– mysql
mysql:
image: mysql:8.0
# …

Testcontainers

At this point, we could start the application and databases manually for testing, but this would be tedious. Instead, let’s use Testcontainers’ ComposeContainer to automate this with our Docker Compose file during the testing phase.

In this example, we’ll use jqwik as our JUnit 5 test runner. First, let’s add the jqwik and Testcontainers and the jqwik-testcontainers dependencies to our pom.xml:

<dependency>
<groupId>net.jqwik</groupId>
<artifactId>jqwik</artifactId>
<version>1.9.0</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>net.jqwik</groupId>
<artifactId>jqwik-testcontainers</artifactId>
<version>0.5.2</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.testcontainers</groupId>
<artifactId>testcontainers</artifactId>
<version>1.20.1</version>
<scope>test</scope>
</dependency>

As a result, we can now instantiate a ComposeContainer and pass our test docker-compose file as argument:

@Testcontainers
class ModelBasedTest {

@Container
static ComposeContainer ENV = new ComposeContainer(new File("src/test/resources/docker-compose-test.yml"))
.withExposedService("app-tested", 8080, Wait.forHttp("/api/employees").forStatusCode(200))
.withExposedService("app-model", 8080, Wait.forHttp("/api/employees").forStatusCode(200));

// tests
}

Test HTTP client

Now, let’s create a small test utility that will help us execute the HTTP requests against our services:

class TestHttpClient {
ApiResponse<EmployeeDto> get(String employeeNo) { /* … */ }

ApiResponse<Void> put(String employeeNo, String newName) { /* … */ }

ApiResponse<List<EmployeeDto>> getByDepartment(String department) { /* … */ }

ApiResponse<EmployeeDto> post(String employeeNo, String name) { /* … */ }

record ApiResponse<T>(int statusCode, @Nullable T body) { }

record EmployeeDto(String employeeNo, String name) { }
}

Additionally, in the test class, we can declare another method that helps us create TestHttpClients for the two services started by the ComposeContainer:

static TestHttpClient testClient(String service) {
int port = ENV.getServicePort(service, 8080);
String url = "http://localhost:%s/api/employees".formatted(port);
return new TestHttpClient(service, url);
}

jqwik

Jqwik is a property-based testing framework for Java that integrates with JUnit 5, automatically generating test cases to validate properties of code across diverse inputs. By using generators to create varied and random test inputs, jqwik enhances test coverage and uncovers edge cases.

If you’re new to jqwik, you can explore their API in detail by reviewing the official user guide. While this tutorial won’t cover all the specifics of the API, it’s essential to know that jqwik allows us to define a set of actions we want to test.

To begin with, we’ll use jqwik’s @Property annotation — instead of the traditional @Test — to define a test:

@Property
void regressionTest() {
TestHttpClient model = testClient("app-model");
TestHttpClient tested = testClient("app-tested");
// …
}

Next, we’ll define the actions, which are the HTTP calls to our APIs and can also include assertions.

For instance, the GetOneEmployeeAction will try to fetch a specific employee from both services and compare the responses:

record ModelVsTested(TestHttpClient model, TestHttpClient tested) {}

record GetOneEmployeeAction(String empNo) implements Action<ModelVsTested> {
@Override
public ModelVsTested run(ModelVsTested apps) {
ApiResponse<EmployeeDto> actual = apps.tested.get(empNo);
ApiResponse<EmployeeDto> expected = apps.model.get(empNo);

assertThat(actual)
.satisfies(hasStatusCode(expected.statusCode()))
.satisfies(hasBody(expected.body()));
return apps;
}
}

Additionally, we’ll need to wrap these actions within Arbitrary objects. We can think of Arbitraries as objects implementing the factory design pattern that can generate a wide variety of instances of a type, based on a set of configured rules.

For instance, the Arbitrary returned by employeeNos() can generate employee numbers by choosing a random department from the configured list and concatenating a number between 0 and 200:

static Arbitrary<String> employeeNos() {
Arbitrary<String> departments = Arbitraries.of("Frontend", "Backend", "HR", "Creative", "DevOps");
Arbitrary<Long> ids = Arbitraries.longs().between(1, 200);
return Combinators.combine(departments, ids).as("%s-%s"::formatted);
}

Similarly, getOneEmployeeAction() returns an Aribtrary action based on a given Arbitrary employee number:

static Arbitrary<GetOneEmployeeAction> getOneEmployeeAction() {
return employeeNos().map(GetOneEmployeeAction::new);
}

After declaring all the other Actions and Arbitraries, we’ll create an ActionSequence:

@Provide
Arbitrary<ActionSequence<ModelVsTested>> mbtJqwikActions() {
return Arbitraries.sequences(
Arbitraries.oneOf(
MbtJqwikActions.getOneEmployeeAction(),
MbtJqwikActions.getEmployeesByDepartmentAction(),
MbtJqwikActions.createEmployeeAction(),
MbtJqwikActions.updateEmployeeNameAction()
));
}

static Arbitrary<Action<ModelVsTested>> getOneEmployeeAction() { /* … */ }
static Arbitrary<Action<ModelVsTested>> getEmployeesByDepartmentAction() { /* … */ }
// same for the other actions

Now, we can write our test and leverage jqwik to use the provided actions to test various sequences. Let’s create the ModelVsTested tuple and use it to execute the sequence of actions against it:

@Property
void regressionTest(@ForAll("mbtJqwikActions") ActionSequence<ModelVsTested> actions) {
ModelVsTested testVsModel = new ModelVsTested(
testClient("app-model"),
testClient("app-tested")
);
actions.run(testVsModel);
}

That’s it — we can finally run the test! The test will generate a sequence of thousands of requests trying to find inconsistencies between the model and the tested service:

INFO com.etr.demo.utils.TestHttpClient — [app-tested] PUT /api/employeesFrontend-129?name=v
INFO com.etr.demo.utils.TestHttpClient — [app-model] PUT /api/employeesFrontend-129?name=v
INFO com.etr.demo.utils.TestHttpClient — [app-tested] GET /api/employees/Frontend-129
INFO com.etr.demo.utils.TestHttpClient — [app-model] GET /api/employees/Frontend-129
INFO com.etr.demo.utils.TestHttpClient — [app-tested] POST /api/employees { name=sdxToS, empNo=Frontend-91 }
INFO com.etr.demo.utils.TestHttpClient — [app-model] POST /api/employees { name=sdxToS, empNo=Frontend-91 }
INFO com.etr.demo.utils.TestHttpClient — [app-tested] PUT /api/employeesFrontend-4?name=PZbmodNLNwX
INFO com.etr.demo.utils.TestHttpClient — [app-model] PUT /api/employeesFrontend-4?name=PZbmodNLNwX
INFO com.etr.demo.utils.TestHttpClient — [app-tested] GET /api/employees/Frontend-4
INFO com.etr.demo.utils.TestHttpClient — [app-model] GET /api/employees/Frontend-4
INFO com.etr.demo.utils.TestHttpClient — [app-tested] GET /api/employees?department=ٺ⯟桸
INFO com.etr.demo.utils.TestHttpClient — [app-model] GET /api/employees?department=ٺ⯟桸

Catching errors

If we run the test and check the logs, we’ll quickly spot a failure. It appears that when searching for employees by department with the argument ٺ⯟桸 the model produces an internal server error, while the test version returns 200 OK:

Original Sample
—————
actions:
ActionSequence[FAILED]: 8 actions run [
UpdateEmployeeAction[empNo=Creative-13, newName=uRhplM],
CreateEmployeeAction[empNo=Backend-184, name=aGAYQ],
UpdateEmployeeAction[empNo=Backend-3, newName=aWCxzg],
UpdateEmployeeAction[empNo=Frontend-93, newName=SrJTVwMvpy],
UpdateEmployeeAction[empNo=Frontend-129, newName=v],
CreateEmployeeAction[empNo=Frontend-91, name=sdxToS],
UpdateEmployeeAction[empNo=Frontend-4, newName=PZbmodNLNwX],
GetEmployeesByDepartmentAction[department=ٺ⯟桸]
]
final currentModel: ModelVsTested[model=com.etr.demo.utils.TestHttpClient@5dc0ff7d, tested=com.etr.demo.utils.TestHttpClient@64920dc2]
Multiple Failures (1 failure)
— failure 1 —
expected: 200
but was: 500

Upon investigation, we find that the issue arises from a native SQL query using Postgres-specific syntax to retrieve data. While this was a simple issue in our small application, model-based testing can help uncover unexpected behavior that may only surface after a specific sequence of repetitive steps pushes the system into a particular state.

Wrap up

In this post, we provided hands-on examples of how model-based testing works in practice. From defining models to generating test cases, we’ve seen a powerful approach to improving test coverage and reducing manual effort. Now that you’ve seen the potential of model-based testing to enhance software quality, it’s time to dive deeper and tailor it to your own projects.

Clone the repository to experiment further, customize the models, and integrate this methodology into your testing strategy. Start building more resilient software today!

Thank you to Emanuel Trandafir for contributing this post.

Learn more

Clone the model-based testing practice repo.

Subscribe to the Docker Newsletter. 

Visit the Testcontainers website.

Get started with Testcontainers Cloud by creating a free account.

Have questions? The Docker community is here to help.

New to Docker? Get started.

Quelle: https://blog.docker.com/feed/