Tag Archives: Containers

OpenShift on OpenStack aims to ease VM, container management

Virtualization admins increasingly use containers to secure applications, but managing both VMs and containers in the same infrastructure presents some challenges.

IT can spin containers up and down more quickly than VMs, and they require less overhead, so there are several practical uses cases for the technology. Security can be a concern, however, because all containers share the same underlying OS. As such, mission-critical applications are still better suited to VMs.

Using both containers and VMs can be helpful, because they each have their place. Still, adding containers to a traditional virtual infrastructure adds another layer of complexity and management for admins to contend with. The free and open source OpenStack provides infrastructure as a service and VM management, and organizations can run Red Hat’s OpenShift on OpenStack — and other systems — for platform as a service and container management.

Here, Brian Gracely, director of OpenShift product strategy at Red Hat, based in Raleigh, N.C., explains how to manage VMs and containers, and he shares how OpenShift on OpenStack can help.

What are the top challenges of managing both VMs and containers in virtual environments?

Brian Gracely, director of OpenShift product strategy at Red HatBrian Gracely

Brian Gracely: The first one is really around people and existing processes. You have infrastructure teams who, over the years, have become very good at managing VMs and … replicating servers with VMs, and they’ve built a set of operational things around that. When we start having the operations team deal with containers, a couple of things are different. Not all of them are as fluent in Linux as you might expect; containers are [based on] the OS. A lot of the virtualization people, especially in the VMware world, came from a Windows background. So, they have to learn a certain amount about what to do with the OS and how to deal with Linux constructs and commands.

Container environments tend to be more closely tied to people who are doing application developments. Application developers are … making changes to the application more frequently and scaling them up and down. The concept of the environment changing more frequently is sort of new for VM admins.

What is the role of OpenStack in modern data centers where VMs and containers coexist?

Gracely: OpenStack can become either an augmentation of what admins used to do with VMware or a replacement for VMware that gives them all of the VM capabilities they want to have in terms of networking, storage and so forth. In most of those cases, they want to also have hybrid capabilities, across public and private. And they can use OpenShift on OpenStack as that abstraction layer that allows them to run containerized applications and/or VM applications in their own data center.

Then, they’ll run OpenShift in one of the public clouds — Amazon or Azure or Google — and the applications that run in the cloud will end up being containerized on OpenShift. It gives them consistency from what the operations look like, and then there’s a pretty simple way of determining which applications can also run in the public cloud, if necessary.

What OpenShift features are most important to container management?

Gracely: OpenShift is based on Kubernetes technology — the de facto standard for managing containers.

If you’re a virtualization person … it’s essentially like vCenter for containers. It centrally manages policies, it centrally manages deployments of containers, [and] it makes sure that you use your compute resources really efficiently. If a container dies, an application dies, it’s going to be constantly monitoring that and will restart it automatically. Kubernetes at the core of OpenShift is the thing that allows people to manage containers at scale, as opposed to managing them one by one.

What can virtualization admins do to improve their container management skills?

Gracely: Become Linux-literate, Linux-skilled. There are plenty of courses out there that allow you to get familiar with Linux. Container technology, fundamentally, is Linux technology, so that’s a fundamental thing. There are tools like Katacoda, which is an online training system; you just go in through your browser. It gives you a Kubernetes environment to play around with, and there’s also an OpenShift set of trainings and tools that are on there.

Kubernetes is the thing that allows people to manage containers at scale, as opposed to managing them one by one.
Brian Gracelydirector of OpenShift product strategy at Red Hat

How can admins streamline management practices between other systems for VMs and OpenShift for containers?

Gracely: OpenShift runs natively on top of both VMware and OpenStack, so for customers that just want to stay focused on VMs, their world can look pretty much the way it does today. They’re going to provision however many VMs they need, and then give self-service access to the OpenShift platform and allow their developers to place containers on there as necessary. The infrastructure team can simply make sure that it’s highly available, that it’s patched, and if more capacity is necessary, add VMs.

Where we see … things get more efficient is people who don’t want to have silos anymore between the ops team and the development team. They’re either going down a DevOps path or combining them together; they want to merge processes. This is where we see them doing much more around automating environments. So, instead of just statically [building] a bunch of VMs and leaving them alone, they’re using tools like Ansible to provision not only the VMs, but the applications that go on top of those VMs and the local database.

Will VMs and containers continue to coexist, or will containers overtake VMs in the data center?

Gracely: More and more so, we’re seeing customers taking a container-first approach with new applications. But … there’s always going to be a need for good VM management, being able to deliver high performance, high I/O stand-alone applications in VMs. We very much expect to see a lot of applications stay in VMs, especially ones that people don’t expect to need any sort of hybrid cloud environment for, some large databases for I/O reasons, or [applications that], for whatever reason, people don’t want to put in containers. Then, our job is to make sure that, as containers come in, that we can make that one seamless infrastructure.

Windows Server containers and Hyper-V containers explained

A big draw of Windows Server 2016 is the addition of containers that provide similar capabilities to those from…


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leading open source providers. This Microsoft platform actually offers two different types of containers: Windows Server containers and Hyper-V containers. Before you decide which option best meets your needs, take a look at these five quick tips so you have a better understanding of container architecture, deployment and performance management.

Windows Server containers vs. Hyper-V containers

Although Windows Server containers and Hyper-V containers do the same thing and are managed the same way, the level of isolation they provide is different. Windows Server containers share the underlying OS kernel, which makes them smaller than VMs because they don’t each need a copy of the OS. Security can be a concern, however, because if one container is compromised, the OS and all of the other containers could be at risk.

Hyper-V containers and their dependencies reside in Hyper-V VMs and provide an additional layer of isolation. For reference, Hyper-V containers and Hyper-V VMs have different use cases. Containers are typically used for microservices and stateless applications because they are deposable by design and, as such, don’t store persistent data. Hyper-V VMs, typically equipped with virtual hard disks, are better suited to mission-critical applications.

The role of Docker on Windows Server

One key advantage of Docker on Windows is support for container image automation.

In order to package, deliver and manage Windows container images, you need to download and install Docker on Windows Server 2016. Docker Swarm, supported by Windows Server, provides orchestration features that help with cluster creation and workload scheduling. After you install Docker, you’ll need to configure it for Windows, a process that includes selecting secured connections and setting disk paths.

One key advantage of Docker on Windows is support for container image automation. You can use container images for continuous integration cycles because they’re stored as code and can be quickly recreated when need be. You can also download and install a module to extend PowerShell to manage Docker Engine; just make sure you have the latest versions of both Windows and PowerShell before you do so.

Meet Hyper-V container requirements

If you prefer to use Hyper-V containers, make sure you have Server Core or Windows Server 2016 installed, along with the Hyper-V role. There is also a list of minimum resource requirements necessary to run Hyper-V containers. First, you need at least 4 GB of memory for the host VM. You also need a processor with Intel VT-x and at least two virtual processors for the host VM. Unfortunately, nested virtualization doesn’t support Advanced Micro Devices yet.

Although these requirements might not seem extensive, it’s important to carefully consider resource allocation and the workloads you intend to run on Hyper-V containers before deployment. When it comes to container images, you have two different options: a Windows Server Core image and a Nano Server image.

OS components affect both container types

Portability is a key advantage of containers. Because an application and all its dependencies are packaged within the container, it should be easy to deploy on other platforms. Unfortunately, there are different elements that can negatively affect this deployment flexibility. While containers share the underlying OS kernel, they do contain their own OS components, also known as the OS layer. If these components don’t match up with the OS kernel running on the host, the container will most likely be blocked.

The four-level version notation system Microsoft uses includes the major, minor, build and revision levels. Before Windows Server containers or Hyper-V containers will run on a Windows Server host, the major, minor and build levels must match, at minimum. The containers will still start if the revision level doesn’t match, but they might not work properly.

Antimalware tools and container performance

Because of shared components, like those of the OS layer, antimalware tools can affect container performance. The components or layers are shared through the use of placeholders; when those placeholders are read, the reads are redirected to the underlying component. If the container modifies a component, the container replaces the placeholder with the modified one.

Antimalware tools aren’t aware of the redirection and don’t know which components are placeholders and which components are modified, so the same components end up being scanned multiple times. Fortunately, there is a way to make antimalware tools aware of this activity. You can modify the container volume by attaching a parameter to the Create CallbackData flag and checking the Exchange Control Panel (ECP) redirection flags. ECP will then either indicate that the file was opened from a remote layer or that the file was opened from a local layer.

Next Steps

Ensure container isolation and prevent root access

Combine microservices and containers

Maintain high availability with containers and data mirroring

Microsoft empowers Windows containers to erase OS divide

Linux and Windows used to be like oil and water, but new approaches to Windows containers will find a way to blend them.

Containers are increasingly important to achieve DevOps velocity. Containerization pulls provisioning and configuration management data into the container image so apps don’t look to the host OS for that information. As intelligence gets baked into containers, the host OS becomes less important to manage the environment.

Windows containers must still catch up to the state of the art in Linux, where containers originated. But as the technology develops, traditionally separate Linux and Windows operations will begin to meld behind container orchestration software.

“Whether you’re on a Linux or Windows environment, you don’t have to worry as much about how you’re building the server,” said Andy Domeier, director of technology operations at SPS Commerce, a communications network for supply chain and logistics businesses based in Minneapolis. “You can use the same host image across [OS] platforms because you don’t have to worry about individual configuration needs for apps.”

Microsoft, which saw this trend coming, has jettisoned its Windows-only focus. Recent versions of products such as Azure Container Instances (ACI), ASP.NET Core 2016, Azure Web App for Containers, and the Azure App Service all support Linux and containers. Docker’s Enterprise Edition release in August 2017 also added support for clusters and multi-tier apps made up of a mix of Linux and Windows components.

“[Microsoft is] a cloud operating system company and all their focus is on selling compute and storage in Azure,” said Chris Riley, DevOps analyst at Fixate IO, a content strategy consulting firm based in Livermore, Calif., and a TechTarget contributor. “If Microsoft embraces open source and makes it easier to develop, then it’s going to get easier to get applications into Azure and increase adoption.”

If Microsoft embraces open source and makes it easier to develop, then it’s going to get easier to get applications into Azure and increase adoption.
Chris RileyDevOps analyst, Fixate IO

Longtime Windows shops said Linux may be the more efficient choice for future container-based app development pipelines.

“We’re looking to break down some of our bigger apps into microservices to run on OpenShift Origin [container management platform], and for those microservices we’re looking into Linux-based databases,” said Aloisio Rocha, operations specialist at NetEnt, an online gaming systems service provider in Sweden. “We’ve found that, for a large amount of data, we don’t need all the functionality that comes with Windows, and Windows databases are a bit too bloated.”

For Microsoft, containers recapture lost time

OS convergence is likely, especially among IT organizations that want DevOps on Microsoft systems, but there’s still work to do if Windows containers are to achieve parity with Linux. Microsoft is comparatively late to the containers game, with Docker container support first generally available in Windows Server 2016. Windows support for container orchestration platforms such as Kubernetes and ACI remains in the preview stage.

“Microsoft is trying to do progressive things and they’re taking the right kind of steps,” said Brandon Cipes, managing director of DevOps at cPrime, an Agile consulting firm in Foster City, Calif. “But if you want a good indicator of how containers are still hard for them, ACI is debuting on Linux and not Windows.”

Microsoft’s strategy for different versions of the Windows OS has also been in flux as the company strives to make Windows container images more efficient. The company revealed in August 2017 that it will no longer support its Nano Server operating system on host servers, but reserve the micro OS for use as a base image inside containers, while Server Core serves as the primary Windows OS for hosts.

“By removing components relating to hardware, and operating system parts which are not needed inside a container, Microsoft thinks it can make the Nano Server container smaller,” explained Thomas Maurer, cloud architect for Switzerland-based ItnetX, a consulting firm that works with large enterprise clients in Europe. “This will make the startup of the containers faster and cut down on their resource consumption.”

This is another area where Windows containers must catch up to their open source counterparts — several container-specific micro-operating systems are already generally available for Linux.

Beth Pariseau is senior news writer for TechTarget’s Data Center and Virtualization Media Group. Write to her at bpariseau@techtarget.com or follow @PariseauTT on Twitter.

Use NGINX to load balance across your Docker Swarm cluster

A practical walkthrough, in six steps

This basic example demonstrates NGINX and swarm mode in action, to provide the foundation for you to apply these concepts to your own configurations.

This document walks through several steps for setting up a containerized NGINX server and using it to load balance traffic across a swarm cluster. For clarity, these steps are designed as an end-to-end tutorial for setting up a three node cluster and running two docker services on that cluster; by completing this exercise, you will become familiar with the general workflow required to use swarm mode and to load balance across Windows Container endpoints using an NGINX load balancer.

The basic setup

This exercise requires three container hosts–two of which will be joined to form a two-node swarm cluster, and one which will be used to host a containerized NGINX load balancer. In order to demonstrate the load balancer in action, two docker services will be deployed to the swarm cluster, and the NGINX server will be configured to load balance across the container instances that define those services. The services will both be web services, hosting simple content that can be viewed via web browser. With this setup, the load balancer will be easy to see in action, as traffic is routed between the two services each time the web browser view displaying their content is refreshed.

The figure below provides a visualization of this three-node setup. Two of the nodes, the “Swarm Manager” node and the “Swarm Worker” node together form a two-node swarm mode cluster, running two Docker web services, “S1” and “S2”. A third node (the “NGINX Host” in the figure) is used to host a containerized NGINX load balancer, and the load balancer is configured to route traffic across the container endpoints for the two container services. This figure includes example IP addresses and port numbers for the two swarm hosts and for each of the six container endpoints running on the hosts.


System requirements

Three* or more computer systems running Windows 10 Creators Update (available today for members of the Windows Insiders program), setup as a container host (see the topic, Windows Containers on Windows 10 for more details on how to get started with Docker containers on Windows 10).

Additionally, each host system should be configured with the following:

  • The microsoft/windowsservercore container image
  • Docker Engine v1.13.0 or later
  • Open ports: Swarm mode requires that the following ports be available on each host.
    • TCP port 2377 for cluster management communications
    • TCP and UDP port 7946 for communication among nodes
    • TCP and UDP port 4789 for overlay network traffic

*Note on using two nodes rather than three:
These instructions can be completed using just two nodes. However, currently there is a known bug on Windows which prevents containers from accessing their hosts using localhost or even the host’s external IP address (for more background on this, see Caveats and Gotchas below). This means that in order to access docker services via their exposed ports on the swarm hosts, the NGINX load balancer must not reside on the same host as any of the service container instances.
Put another way, if you use only two nodes to complete this exercise, one of them will need to be dedicated to hosting the NGINX load balancer, leaving the other to be used as a swarm container host (i.e. you will have a single-host swarm cluster and a host dedicated to your containerized NGINX load balancer).

Step 1: Build an NGINX container image

In this step, we’ll build the container image required for your containerized NGINX load balancer. Later we will run this image on the host that you have designated as your NGINX container host.

Note: To avoid having to transfer your container image later, complete the instructions in this section on the container host that you intend to use for your NGINX load balancer.

NGINX is available for download from nginx.org. An NGINX container image can be built using a simple Dockerfile that installs NGINX onto a Windows base container image and configures the container to run as an NGINX executable. For the purpose of this exercise, I’ve made a Dockerfile downloadable from my personal GitHub repo; access the NGINX Dockerfile here, then save it to some location (e.g. C:tempnginx) on your NGINX container host machine. From that location, build the image using the following command:

C:tempnginx> docker build -t nginx .

Now the image should appear with the rest of the docker images on your system (you can check this using the docker images command).

(Optional) Confirm that your NGINX image is ready

First, run the container:

C:temp> docker run -it -p 80:80 nginx

Next, open a new cmdlet window and use the docker ps command to see that the container is running. Note its ID. The ID of your container is the value of <CONTAINERID> in the next command.

Get the container’s IP address:

C:temp> docker exec <CONTAINERID> ipconfig

For example, your container’s IP address may be, as in the example output shown below.


Next, open a browser on your container host and put your container’s IP address in the address bar. You should see a confirmation page, indicating that NGINX is successfully running in your container.



Step 2: Build images for two containerized IIS Web services

In this step, we’ll build container images for two simple IIS-based web applications. Later, we’ll use these images to create two docker services.

Note: Complete the instructions in this section on one of the container hosts that you intend to use as a swarm host.

Build a generic IIS Web Server image

On my personal GitHub repo, I have made a Dockerfile available for creating an IIS Web server image. The Dockerfile simply enables the Internet Information Services (IIS) Web server role within a microsoft/windowsservercore container. Download the Dockerfile from here, and save it to some location (e.g. C:tempiis) on one of the host machines that you plan to use as a swarm node. From that location, build the image using the following command:

 C:tempiis> docker build -t iis-web .

(Optional) Confirm that your IIS Web server image is ready

First, run the container:

 C:temp> docker run -it -p 80:80 iis-web

Next, use the docker ps command to see that the container is running. Note its ID. The ID of your container is the value of <CONTAINERID> in the next command.

Get the container’s IP address:

C:temp> docker exec <CONTAINERID> ipconfig

Now open a browser on your container host and put your container’s IP address in the address bar. You should see a confirmation page, indicating that the IIS Web server role is successfully running in your container.


Build two custom IIS Web server images

In this step, we’ll be replacing the IIS landing/confirmation page that we saw above with custom HTML pages–two different pages, corresponding to two different web container images. In a later step, we’ll be using our NGINX container to load balance across instances of these two images. Because the images will be different, we will easily see the load balancing in action as it shifts between the content being served by the containers instances of the two images.

First, on your host machine create a simple file called, index_1.html. In the file type any text. For example, your index_1.html file might look like this:


Now create a second file, index_2.html. Again, in the file type any text. For example, your index_2.html file might look like this:


Now we’ll use these HTML documents to make two custom web service images.

If the iis-web container instance that you just built is not still running, run a new one, then get the ID of the container using:

C:temp> docker exec <CONTAINERID> ipconfig

Now, copy your index_1.html file from your host onto the IIS container instance that is running, using the following command:

C:temp> docker cp index_1.html <CONTAINERID>:C:inetpubwwwrootindex.html

Next, stop and commit the container in its current state. This will create a container image for the first web service. Let’s call this first image, “web_1.”

C:> docker stop <CONTAINERID>
C:> docker commit <CONTAINERID> web_1

Now, start the container again and repeat the previous steps to create a second web service image, this time using your index_2.html file. Do this using the following commands:

C:> docker start <CONTAINERID>
C:> docker cp index_2.html <CONTAINERID>:C:inetpubwwwrootindex.html
C:> docker stop <CONTAINERID>
C:> docker commit <CONTAINERID> web_2

You have now created images for two unique web services; if you view the Docker images on your host by running docker images, you should see that you have two new container images—“web_1” and “web_2”.

Put the IIS container images on all of your swarm hosts

To complete this exercise you will need the custom web container images that you just created to be on all of the host machines that you intend to use as swarm nodes. There are two ways for you to get the images onto additional machines:

  • Option 1: Repeat the steps above to build the “web_1” and “web_2” containers on your second host.
  • Option 2 [recommended]: Push the images to your repository on Docker Hub then pull them onto additional hosts.

A note on Docker Hub:
Using Docker Hub is a convenient way to leverage the lightweight nature of containers across all of your machines, and to share your images with others. Visit the following Docker resources to get started with pushing/pulling images with Docker Hub:
Create a Docker Hub account and repository
Tag, push and pull your image


Step 3: Join your hosts to a swarm

As a result of the previous steps, one of your host machines should have the nginx container image, and the rest of your hosts should have the Web server images, “web_1” and “web_2”. In this step, we’ll join the latter hosts to a swarm cluster.

Note: The host running the containerized NGINX load balancer cannot run on the same host as any container endpoints for which it is performing load balancing; the host with your nginx container image must be reserved for load balancing only. For more background on this, see Caveats and Gotchas below.

First, run the following command from any machine that you intend to use as a swarm host. The machine that you use to execute this command will become a manager node for your swarm cluster.

  • Replace <HOSTIPADDRESS> with the public IP address of your host machine
C:temp> docker swarm init --advertise-addr=<HOSTIPADDRESS> --listen-addr <HOSTIPADDRESS>:2377

Now run the following command from each of the other host machines that you intend to use as swarm nodes, joining them to the swarm as a worker nodes.

  • Replace <MANAGERIPADDRESS> with the public IP address of your host machine (i.e. the value of <HOSTIPADDRESS> that you used to initialize the swarm from the manager node)
  • Replace <WORKERJOINTOKEN> with the worker join-token provided as output by the docker swarm init command (you can also obtain the join-token by running docker swarm join-token worker from the manager host)
C:temp> docker swarm join --token <WORKERJOINTOKEN> <MANAGERIPADDRESS>:2377

Your nodes are now configured to form a swarm cluster! You can see the status of the nodes by running the following command from your manage node:

C:temp> docker node ls

Step 4: Deploy services to your swarm

Note: Before moving on, stop and remove any NGINX or IIS containers running on your hosts. This will help avoid port conflicts when you define services. To do this, simply run the following commands for each container, replacing <CONTAINERID> with the ID of the container you are stopping/removing:

C:temp> docker stop <CONTAINERID>
C:temp> docker rm <CONTAINERID>

Next, we’re going to use the “web_1” and “web_2” container images that we created in previous steps of this exercise to deploy two container services to our swarm cluster.

To create the services, run the following commands from your swarm manager node:

C: > docker service create --name=s1 --publish mode=host,target=80 --endpoint-mode dnsrr web_1 powershell -command {echo sleep; sleep 360000;}
C: > docker service create --name=s2 --publish mode=host,target=80 --endpoint-mode dnsrr web_2 powershell -command {echo sleep; sleep 360000;}

You should now have two services running, s1 and s2. You can view their status by running the following command from your swarm manager node:

C: > docker service ls

Additionally, you can view information on the container instances that define a specific service with the following commands (where <SERVICENAME> is replaced with the name of the service you are inspecting (for example, s1 or s2):

# List all services
C: > docker service ls
# List info for a specific service
C: > docker service ps <SERVICENAME>

(Optional) Scale your services

The commands in the previous step will deploy one container instance/replica for each service, s1 and s2. To scale the services to be backed by multiple replicas, run the following command:

C: > docker service scale <SERVICENAME>=<REPLICAS>
# e.g. docker service scale s1=3

Step 5: Configure your NGINX load balancer

Now that services are running on your swarm, you can configure the NGINX load balancer to distribute traffic across the container instances for those services.

Of course, generally load balancers are used to balance traffic across instances of a single service, not multiple services. For the purpose of clarity, this example uses two services so that the function of the load balancer can be easily seen; because the two services are serving different HTML content, we’ll clearly see how the load balancer is distributing requests between them.

The nginx.conf file

First, the nginx.conf file for your load balancer must be configured with the IP addresses and service ports of your swarm nodes and services. An example nginx.conf file was included with the NGINX download that was used to create your nginx container image in Step 1. For the purpose of this exercise, I copied and adapted the example file provided by NGINX and used it to create a simple template for you to adapt with your specific node/container information.

Download the nginx.conf file template that I prepared for this exercise from my personal GitHub repo, and save it onto your NGINX container host machine. In this step, we’ll adapt the template file and use it to replace the default nginx.conf file that was originally downloaded onto your NGINX container image.

You will need to adjust the file by adding the information for your hosts and container instances. The template nginx.conf file provided contains the following section:

upstream appcluster {
     server <HOSTIP>:<HOSTPORT>;
     server <HOSTIP>:<HOSTPORT>;
     server <HOSTIP>:<HOSTPORT>;
     server <HOSTIP>:<HOSTPORT>;
     server <HOSTIP>:<HOSTPORT>;
     server <HOSTIP>:<HOSTPORT>;

To adapt the file for your configuration, you will need to adjust the <HOSTIP>:<HOSTPORT> entries in the template config file. You will have an entry for each container endpoint that defines your web services. For any given container endpoint, the value of <HOSTIP> will be the IP address of the container host upon which that container is running. The value of <HOSTPORT> will be the port on the container host upon which the container endpoint has been published.

When the services, s1 and s2, were defined in the previous step of this exercise, the --publish mode=host,target=80 parameter was included. This parameter specified that the container instances for the services should be exposed via published ports on the container hosts. More specifically, by including --publish mode=host,target=80 in the service definitions, each service was configured to be exposed on port 80 of each of its container endpoints, as well as a set of automatically defined ports on the swarm hosts (i.e. one port for each container running on a given host).

First, identify the host IPs and published ports for your container endpoints

Before you can adjust your nginx.conf file, you must obtain the required information for the container endpoints that define your services. To do this, run the following commands (again, run these from your swarm manager node):

C: > docker service ps s1
C: > docker service ps s2

The above commands will return details on every container instance running for each of your services, across all of your swarm hosts.

  • One column of the output, the “ports” column, includes port information for each host of the form *:<HOSTPORT>->80/tcp. The values of <HOSTPORT> will be different for each container instance, as each container is published on its own host port.
  • Another column, the “node” column, will tell you which machine the container is running on. This is how you will identify the host IP information for each endpoint.

You now have the port information and node for each container endpoint. Next, use that information to populate the upstream field of your nginx.conf file; for each endpoint, add a server to the upstream field of the file, replacing the field with the IP address of each node (if you don’t have this, run ipconfig on each swarm host machine to obtain it), and the field with the corresponding host port.

For example, if you have two swarm hosts (IP addresses and, each running three containers your list of servers will end up looking something like this:

upstream appcluster {

Once you have changed your nginx.conf file, save it. Next, we’ll copy it from your host to the NGINX container image itself.

Replace the default nginx.conf file with your adjusted file

If your nginx container is not already running on its host, run it now:

C:temp> docker run -it -p 80:80 nginx

Next, open a new cmdlet window and use the docker ps command to see that the container is running. Note its ID. The ID of your container is the value of <CONTAINERID> in the next command.

Get the container’s IP address:

C:temp> docker exec <CONTAINERID> ipconfig

With the container running, use the following command to replace the default nginx.conf file with the file that you just configured (run the following command from the directory in which you saved your adjusted version of the nginx.conf on the host machine):

C:temp> docker cp nginx.conf <CONTAINERID>:C:nginxnginx-1.10.3conf

Now use the following command to reload the NGINX server running within your container:

C:temp> docker exec <CONTAINERID> nginx.exe -s reload

Step 6: See your load balancer in action

Your load balancer should now be fully configured to distribute traffic across the various instances of your swarm services. To see it in action, open a browser and

  • If accessing from the NGINX host machine: Type the IP address of the nginx container running on the machine into the browser address bar. (This is the value of <CONTAINERID> above).
  • If accessing from another host machine (with network access to the NGINX host machine): Type the IP address of the NGINX host machine into the browser address bar.

Once you’ve typed the applicable address into the browser address bar, press enter and wait for the web page to load. Once it loads, you should see one of the HTML pages that you created in step 2.

Now press refresh on the page. You may need to refresh more than once, but after just a few times you should see the other HTML page that you created in step 2.

If you continue refreshing, you will see the two different HTML pages that you used to define the services, web_1 and web_2, being accessed in a round-robin pattern (round-robin is the default load balancing strategy for NGINX, but there are others). The animated image below demonstrated the behavior that you should see.

As a reminder, below is the full configuration with all three nodes. When you’re refreshing your web page view, you’re repeatedly accessing the NGINX node, which is distributing your GET request to the container endpoints running on the swarm nodes. Each time you resend the request, the load balancer has the opportunity to route you to a different endpoint, resulting in your being served a different web page, depending on whether your request was routed to an S1 or S2 endpoint.


Caveats and gotchas

Q: Is there a way to publish a single port for my service, so that I can load balance across each of my services rather than each of the individual endpoints for my services?

Unfortunately, we do not yet support publishing a single port for a service on Windows. This feature is swarm mode’s routing mesh feature—a feature that allows you to publish ports for a service, so that that service is accessible to external resources via that port on every swarm node.

Routing mesh for swarm mode on Windows is not yet supported, but will be coming soon.


Q: Why can’t I run my containerized load balancer on one of my swarm nodes?

Currently, there is a known bug on Windows, which prevents containers from accessing their hosts using localhost or even the host’s external IP address. This means containers cannot access their host’s exposed ports—the can only access exposed ports on other hosts.

In the context of this exercise, this means that the NGINX load balancer must be running on its own host, and never on the same host as any services that it needs to access via exposed ports. Put another way, for the containerized NGINX load balancer to balance across the two web services defined in this exercise, s1 and s2, it cannot be running on a swarm node—if it were running on a swarm node, it would be unable to access any containers on that node via host exposed ports.

Of course, an additional caveat here is that containers do not need to be accessed via host exposed ports. It is also possible to access containers directly, using the container IP and published port. If this instead were done for this exercise, the NGINX load balancer would need to be configured to:

  • Access containers that share its host by their container IP and port
  • Access containers that do not share its host by their host’s IP and exposed port

There is no problem with configuring the load balancer in this way, other than the added complexity that it introduces compared to simply putting the load balancer on its own machine, so that containers can be uniformly accessed via their host’s IPs and exposed ports.

Overlay Network Driver with Support for Docker Swarm Mode Now Available to Windows Insiders on Windows 10

Windows 10 Insiders can now take advantage of overlay networking and Docker swarm mode  to manage containerized applications in both single-host and clustering scenarios.

Containers are a rapidly growing technology, and as they evolve so must the technologies that support them as members of a broader collection of compute, storage and networking infrastructure components. For networking, in particular, this means continually striving to achieve better connectivity, higher reliability and easier management for container networking. Less than six months ago, Microsoft released Windows 10 Anniversary Edition and Windows Server 2016, and even as our first versions of Windows with container support were being celebrated we were already hard at work on new container features, including several container networking features.

Our last Windows release showcased Docker Compose and service discovery—two key features for single-host container deployment and networking scenarios. Now, we’re expanding the reach of Windows container networking to multi-host (clustering) scenarios with the addition of a native overlay network driver and support for Docker swarm mode, available today to Windows Insiders as part of the upcoming Windows 10, Creators Update.

Docker swarm mode is Docker’s native orchestration tool, designed to simplify the experiencing of declaring, managing and scaling container services. The Windows overlay network driver (which uses VXLAN and virtual overlay networking technology) makes it possible to connect container endpoints running on separate hosts to the same, isolated network. Together, swarm mode and overlay enable easy management and complete scalability of your containerized applications, allowing you to leverage the full power of your infrastructure hosts.

What is “swarm mode”?

Swarm mode is a Docker feature that provides built in container orchestration capabilities, including native clustering of Docker hosts and scheduling of container workloads. A group of Docker hosts form a “swarm” cluster when their Docker engines are running together in “swarm mode.”

A swarm is composed of two types of container hosts: manager nodes, and worker nodes. Every swarm is initialized via a manager node, and all Docker CLI commands for controlling and monitoring a swarm must be executed from one of its manager nodes. Manager nodes can be thought of as “keepers” of the Swarm state—together, they form a consensus group that maintains awareness of the state of services running on the swarm, and it’s their job to ensure that the swarm’s actual state always matches its intended state, as defined by the developer or admin.

Note: Any given swarm can have multiple manager nodes, but it must always have at least one.

Worker nodes are orchestrated by Docker swarm via manager nodes. To join a swarm, a worker node must use a “join token” that was generated by the manager node when the swarm was initialized. Worker nodes simply receive and execute tasks from manager nodes, and so they require (and possess) no awareness of the swarm state.


Figure 1: A four-node swarm cluster running two container services on isolated overlay networks.

Figure 1 offers a simple visualization of a four-node cluster running in swarm mode, leveraging the overlay network driver. In this swarm, Host A is the manager node and Hosts B-D are worker nodes. Together, these manager and worker nodes are running two Docker services which are backed by a total of ten container instances, or “replicas.” The yellow in this figure distinguishes the first service, Service 1; the containers for Service 1 are connected by an overlay network. Similarly, the blue in this figure represents the second service, Service 2; the containers for Service 2 are also attached by an overlay network.

Note: In this case, the two Docker services happen to be connected by separate/isolated overlay networks. It is also possible, however, for multiple container services to be attached to the same overlay network.

Windows Network Stack Implementation

Under the covers, Swarm and overlay are enabled by enhancements to the Host Network Service (HNS) and Windows libnetwork plugin for the Docker engine, which leverage the Azure Virtual Filtering Platform (VFP) forwarding extension in the Hyper-V Virtual Switch. Figure 2 shows how these components work together on a given Windows container host, to enable overlay and swarm mode functionality.

Figure 2: Key components involved in enabling swarm mode and overlay networking on Windows container hosts.

Figure 2: Key components involved in enabling swarm mode and overlay networking on Windows container hosts.

The HNS overlay network driver plugin and VFP forwarding extension

Overlay networking was enabled with the addition of an overlay network driver plugin to the HNS service, which creates encapsulation rules using the VFP forwarding extension in the Hyper-V Virtual Switch; the HNS overlay plugin communicates with the VFP forwarding extension to perform the VXLAN encapsulation required to enable overlay networking functionality.

On Windows, the Azure Virtual Filtering Platform (VFP) is a software defined networking (SDN) element, installed as a programmable Hyper-V Virtual Switch forwarding extension. It is a shared component with the Azure platform, and was added to Windows 10 with Windows 10 Anniversary Edition. It is designed as a high performance, rule-flow based engine, to specify per-endpoint rules for forwarding, transforming, or blocking network traffic. The VFP extension has been used for implementing the l2bridge and l2tunnel Windows container networking modes and is now also used to implement the overlay networking mode. As we continue to expand container networking capabilities on Windows, we plan to further leverage the VFP extension to enable more fine-grained policy.

Enhancements to the Windows libnetwork plugin

Overlay networking support was the main hurdle that needed to be overcome to achieve Docker swarm mode support on Windows. Aside from that, additions also needed to be made to the Windows libnetwork Plugin—the plugin to the Docker engine that enables container networking functionality on Windows by facilitating communication between the Docker engine and the HNS service.

Load balancing: Windows routing mesh coming soon

Currently, Windows supports DNS Round-Robin load balancing between services. The routing mesh for Windows Docker hosts is not yet supported, but will be coming soon. Users seeking an alternative load balancing strategy today can setup an external load balancer (e.g. NGINX) and use Swarm’s publish-port mode to expose container host ports over which to load balance.

Boost your DevOps cycle and manage containers across Windows hosts by leveraging Docker swarm mode today

Together, Docker Swarm and support for overlay container networks enable multi-host scenarios and rapid scalability of your Windows containerized applications and services. This new support, combined with service discovery and the rest of the capabilities that you are used to leveraging in single-host configurations, makes for a clean and straight-forward experience developing containerized apps on Windows for multi-host environments.

To get started with Docker Swarm and overlay networking on Windows, start here .

The Datacenter and Cloud Networking team worked alongside our partners internally and at Docker to bring overlay networking mode and Docker swarm mode support to Windows. Again, this is an exciting milestone in our ongoing work to achieve better container networking support to Windows users. We’re constantly seeking more ways to improve your experience working with containers on Windows, and it’s only with your feedback that we can best decide what to do next to enable you and your DevOps teams.

We encourage you to share your experiences, questions and feedback with us, to help us learn more about what you’re doing with container networking on Windows today, and to understand what you’d like to achieve in the future. Visit our Contact Page to learn more about the forums that you can use to be in touch with us.

Introducing the Host Compute Service (HCS)


This post introduces a low level container management API in Hyper-V called the Host Compute Service (HCS).  It tells the story behind its creation, and links to a few open source projects that make it easier to use.

Motivation and Creation

Building a great management API for Docker was important for Windows Server Containers.  There’s a ton of really cool low-level technical work that went into enabling containers on Windows, and we needed to make sure they were easy to use.  This seems very simple, but figuring out the right approach was surprisingly tricky.

Our first thought was to extend our existing management technologies (e.g. WMI, PowerShell) to containers.  After investigating, we concluded that they weren’t optimal for Docker, and started looking at other options.

Next, we considered mirroring the way Linux exposes containerization primitives (e.g. control groups, namespaces, etc.).  Under this model, we could have exposed each underlying feature independently, and asked Docker to call into them individually.  However, there were a few questions about that approach that caused us to consider alternatives:

  1. The low level APIs were evolving (and improving) rapidly.  Docker (and others) wanted those improvements, but also needed a stable API to build upon.  Could we stabilize the underlying features fast enough to meet our release goals?
  2. The low level APIs were interesting and useful because they made containers possible.  Would anyone actually want to call them independently?

After a bit of thinking, we decided to go with a third option.  We created a new management service called the Host Compute Service (HCS), which acts as a layer of abstraction above the low level functionality.  The HCS was a stable API Docker could build upon, and it was also easier to use.  Making a Windows Server Container with the HCS is just a single API call.  Making a Hyper-V Container instead just means adding a flag when calling into the API.  Figuring out how those calls translate into actual low-level implementation is something the Hyper-V team has already figured out.

linux-arch windows-arch

Getting Started with the HCS

If you think this is nifty, and would like to play around with the HCS, here’s some infomation to help you get started.  Instead of calling our C API directly, I recommend using one the friendly wrappers we’ve built around the HCS.  These wrappers make it easy to call the HCS from higher level languages, and are released open source on GitHub.  They’re also super handy if you want to figure out how to use the C API.  We’ve released two wrappers thus far.  One is written in Go (and used by Docker), and the other is written in C#.

You can find the wrappers here:

If you want to use the HCS (either directly or via a wrapper), or you want to make a Rust/Haskell/InsertYourLanguage wrapper around the HCS, please drop a comment below.  I’d love to chat.

For a deeper look at this topic, I recommend taking a look at John Stark’s DockerCon presentation: https://www.youtube.com/watch?v=85nCF5S8Qok

John Slack
Program Manager
Hyper-V Team

Use Docker Compose and Service Discovery on Windows to scale-out your multi-service container application

Article by Kallie Bracken and Jason Messer

The containers revolution popularized by Docker has come to Windows so that developers on Windows 10 (Anniversary Edition) or IT Pros using Windows Server 2016 can rapidly build, test, and deploy Windows “containerized” applications!

Based on community feedback, we have made several improvements to the Windows containers networking stack to enable multi-container, multi-service application scenarios. Support for Service Discovery and the ability to create (or re-use existing) networks are at the center of the improvements that were made to bring the efficiency of Docker Compose to Windows. Docker Compose enables developers to instantly build, deploy and scale-out their “containerized” applications running in Windows containers with just a few simple commands. Developers define their application using a ‘Compose file’ to specify the services, corresponding container images, and networking infrastructure required to run their application. Service Discovery itself is a key requirement to scale-out multi-service applications using DNS-based load-balancing and we are proud to announce support for Service Discovery in the most recent versions of Windows 10 and Windows Server 2016.

Take your next step in mastering development with Windows Containers, and keep letting us know what great capabilities you would like to see next!

When it comes to using Docker to manage Windows containers, with just a little background it’s easy to get simple container instances up and running. Once you’ve covered the basics, the next step is to build your own custom container images using Dockerfiles to install features, applications and other configuration layers on top of the Windows base container images. From there, the next step is to get your hands dirty building multi-tier applications, composed of multiple services running in multiple container instances. It’s here—in the modularization and scaling-out of your application—that Docker Compose comes in; Compose is the perfect tool for streamlining the specification and deployment of multi-tier, multi-container applications. Docker Compose registers each container instance by service name through the Docker engine thereby allowing containers to ‘discover’ each other by name when sending intra-application network traffic. Application services can also be scaled-out to multiple container instances using Compose. Network traffic destined to a multi-container service is then round-robin’d using DNS load-balancing across all container instances implementing that service.

This post walks through the process of creating and deploying a multi-tier blog application using Docker Compose (Compose file and application shown in Figure 1).


Figure 1: The Compose File used to create the blog application, including its BlogEngine.NET front-end (the ‘web’ service) and SQL Server back-end (the ‘db’ service).

Note: Docker Compose can be used to scale-out applications on a single host which is the scope of this post. To scale-out your ‘containerized’ application across multiple hosts, the application should be deployed on a multi-node cluster using a tool such as Docker Swarm. Look for multi-host networking support in Docker Swarm on Windows in the near future.

The first tier of the application is an ASP.NET web app, BlogEngine.NET, and the back-end tier is a database built on SQL Server Express 2014. The database is created to manage and store blog posts from different users which are subsequently displayed through the Blog Engine app.

New to Docker or Windows Containers?

This post assumes familiarity with the basics of Docker, Windows containers and ‘containerized’ ASP.NET applications. Here are some good places to start if you need to brush up on your knowledge:


System Prerequisites

Before you walk through the steps described in this post, check that your environment meets the following requirements and has the most recent versions of Docker and Windows updates installed:

  • Windows 10 Anniversary Edition (Professional or Enterprise) or Windows Server 2016
    Windows Containers requires your system to have critical updates installed. Check your OS version by running winver.exe, and ensure you have installed the latest KB 3192366 and/or Windows 10 updates.
  • The latest version of Docker-Compose (available with Docker-for-Windows) must be installed on your system.

NOTE: The current version of Docker Compose on Windows requires that the Docker daemon be configured to listen to a TCP socket for new connections. A Pull Request (PR) to fix for this issue is in review and will be merged soon. For now, please ensure that you do the following:

Please configure the Docker Engine by adding a “hosts” key to the daemon.json file (example shown below) following the instructions here. Be sure to restart the Docker service after making this change.

"hosts":["tcp://", “npipe:////./pipe/win_engine"]

When running docker-compose, you will either need to explicitly reference the host port by adding the option “-H tcp://localhost:2375” to the end of this command (e.g. docker-compose -H “tcp://localhost:2375” or by setting your DOCKER_HOST environment variable to always use this port (e.g. $env:DOCKER_HOST=”tcp://localhost:2375”

Blog Application Source with Compose and Dockerfiles

This blog application is based on the Blog Engine ASP.NET web app availably publicly here: http://www.dnbe.net/docs/.  To follow this post and build the described application, a complete set of files is available on GitHub. Download the Blog Application files from GitHub and extract them to a location somewhere on your machine, e.g. ‘C:build’ directory.

The blog application directory includes:

  • A ‘web’ folder that contains the Dockerfile and resources that you’ll need to build the image for the blog application’s ASP.NET front-end.
  • A ‘db’ folder that contains the Dockerfile and resources that you’ll need to build the blog application’s SQL database back-end.
  • A ‘docker-compose.yml’ file that you will use to build and run the application using Docker Compose.

The top-level of the blog application source folder is the main working directory for the directions in this post. Open an elevated PowerShell session and navigate there now – e.g.

PS C:> cd c:build

The Blog Application Container Images

Database Back-End Tier: The ‘db’ Service

The database back-end Dockerfile is located in the ‘db’ sub-folder of the blog application source files and can be referenced here: The Blog Database Dockerfile. The main function of this Dockerfile is to run two scripts over the Windows Server Core base OS image to define a new database as well as the tables required by the BlogEngine.NET application.

The SQL scripts referenced by the Dockerfile to construct the blog database are included in the ‘db’ folder, and copied from host to container when the container image is created so that they can be run on the container.

BlogEngine.NET Front-End

The BlogEngine.NET Dockerfile is in the ‘web’ sub-folder of the blog application source files.

This Dockerfile refers to a PowerShell script (buildapp.ps1) that does the majority of the work required to configure the web service image. The buildapp.ps1 PowerShell Script obtains the BlogEngine.NET project files using a download link from Codeplex, configures the blog application using the default IIS site, grants full permission over the BlogEngine.NET project files (something that is required by the application) and executes the commands necessary to build an IIS web application from the BlogEngine.NET project files.

After running the script to obtain and configure the BlogEngine.NET web application, the Dockerfile finishes by copying the Web.config file included in the ‘web’ sub-folder to the container, to overwrite the file that was downloaded from Codeplex. The config file provided has been altered to point the ‘web’ service to the ‘db’ back-end service.

Streamlining with Docker Compose

When dealing with only one or two independent containers, it is simple to use the ‘docker run’ command to create and start a container image. However, as soon as an application begins to gain complexity, perhaps by including several inter-dependent services or by deploying multiple instances of any one service, the notion of configuring and running that app “manually” becomes impractical. To simplify the definition and deployment of an application, we can use Docker Compose.

A Compose file is used to define our “containerized” application using two services—a ‘web’ service and a ‘db’ service.  The blog application’s Compose File (available here for reference) defines the ‘web’ service which runs the BlogEngine.NET web front-end tier of the application and the ‘db’ service which runs the SQL Server 2014 Express back-end database tier. The compose file also handles network configuration for the blog application (with both application-level and service-level granularity).

Something to note in the blog application Compose file, is that the ‘expose’ option is used in place of the ‘ports’ option for the ‘db’ service. The ‘ports’ option is analogous to using the ‘-p’ argument in a ‘docker run’ command, and specifies HOST:CONTAINER port mapping for a service. However, this ‘ports’ option specifies a specific container host port to use for the service thereby limiting the service to only one container instance since multiple instances can’t re-use the same host port. The ‘expose’ option, on the other hand, can be used to define the internal container port with a dynamic, external port selected automatically by Docker through the Windows Host Networking Service – HNS. This allows for the creation of multiple container instances to run a single service; where the ‘ports’ option requires that every container instance for a service be mapped as specified, the ‘expose’ option allows Docker Compose to handle port mapping as required for scaled-out scenarios.

The ‘networks’ key in the Compose file specifies the network to which the application services will be connected. In this case, we define the default network for all services to use as external meaning a network will not be created by Docker Compose. The ‘nat’ network referenced is the default NAT network created by the Docker Engine when Docker is originally installed.

‘docker-compose build’

In this step, Docker Compose is used to build the blog application. The Compose file references the Dockerfiles for the ‘web’ and ‘db’ services and uses them to build the container image for each service.

From an elevated PowerShell session, navigate to the top level of the Blog Application directory. For example,

cd C:build

Now use Docker Compose to build the blog application:

docker-compose build

‘docker-compose up’

Now use Docker Compose to run the blog application:

docker-compose up

This will cause a container instance to be run for each application service. Execute the command to see that the blog application is now up and running.

docker-compose ps

You can access the blog application through a browser on your local machine, as described below.

Define Multiple, Custom NAT Networks

In previous Windows Server 2016 technical previews, Windows was limited to a single NAT network per container host. While this is still technically the case, it is possible to define custom NAT networks by segmenting the default NAT network’s large, internal prefix into multiple subnets.

For instance, if the default NAT internal prefix was, a custom NAT network could be carved out from this prefix. The ‘networks’ section in the Compose file could be replaced with the following:

    driver: nat
      driver: default
      - subnet:

This would create a user-defined NAT network with a user-defined IP subnet prefix (in this case, The ipam option is used to specify this custom IPAM configuration.

Note: Ensure that any custom nat network defined is a subset of the larger nat internal prefix previously created. To obtain your host nat network’s internal prefix, run ‘docker network inspect nat’.

View the Blog Application

Now that the containers for the ‘web’ and ‘db’ services are running, the blog application can be accessed from the local container host using the internal container IP and port (80). Use the command docker inspect <web container instance> to determine this internal IP address.

To access the application, open an internet browser on the container host and navigate to the following URL: “http://<container ip>//BlogEngine/” appended. For instance, you might enter:

To access the application from an external host that is connected to the container host’s network, you must use the Container Host IP address and mapped port of the web container. The mapped port of the web container endpoint is displayed from docker-compose ps or docker ps commands. For instance, you might enter:

The blog application may take a moment to load, but soon your browser should present the following page.

Screenshot of page

Screenshot of page

Taking Advantage of Service Discovery

Built in to Docker is Service Discovery, which offers two key benefits: service registration and service name to IP (DNS) mapping. Service Discovery is especially valuable in the context of scaled-out applications, as it allows multi-container services to be discovered and referenced in the same way as single container services; with Service Discovery, intra-application communication is simple and concise—any service can be referenced by name, regardless of the number of container instances that are being used to run that service.

Service registration is the piece of Service Discovery that makes it possible for containers/services on a given network to discover each other by name. As a result of service registration, every application service is registered with a set of internal IP addresses for the container endpoints that are running that service. With this mapping, DNS resolution in the Docker Engine responds to any application endpoint seeking to communicate with a given service by sending a randomly ordered list of the container IP addresses associated with that service. The DNS client in the requesting container then chooses one of these IPs for container-container communication. This is referred to as DNS load-balancing.

Through DNS mapping Docker abstracts away the added complexity of managing multiple container endpoints; because of this piece of Service Discovery a single service can be treated as an atomic entity, no matter how many container instances it has running behind the scenes.

Note: For further context on Service Discovery, visit this Docker resource. However, note that Windows does not support the “-link” options.

Scale-Out with ‘docker-compose scale’

DockerCompose Scale

While the service registration benefit of Service Discovery is leveraged by an application even when one container instance is running for each application service, a scaled-out scenario is required for the benefit of DNS load-balancing to truly take effect.

To run a scaled-out version of the blog application, use the following command (either in place of ‘docker-compose up’ or even after the compose application is up and running). This command will run the blog application with one container instance for the ‘web’ service and three container instances for the ‘db’ service.

docker-compose scale web=1 db=3

Recall that the docker-compose.yml file provided with the blog application project files does not allow for scaling multiple instances of the ‘web’ service. To scale the web service, the ‘ports’ option for the web service must be replaced with the ‘expose’ option. However, without a load-balancer in front of the web service, a user would need to reference individual container endpoint IPs and mapped ports for external access into the web front-end of this application. An improvement to this application would be to use volume mapping so that all ‘db’ container instances reference the same SQL database files. Stay tuned for a follow-on post on these topics.

Service Discovery in action

In this step, Service Discovery will be demonstrated through a simple interaction between the ‘web’ and ‘db’ application services. The idea here is to ping different instances of the ‘db’ service to see that Service Discovery allows it to be accessed as a single service, regardless of how many container instances are implementing the service.

Before you begin: Run the blog application using the ‘docker-compose scale’ instruction described above.

Return to your PowerShell session, and run the following command to ping the ‘db’ back-end service from your web service. Notice the IP address from which you receive a reply.

docker run blogengine ping db

Now run the ping command again, and notice whether or not you receive a reply from a different IP address (i.e. a different ‘db’ container instance).*

docker run blogengine ping db

The image below demonstrates the behavior you should see—after pinging 2-3 times, you should receive replied from at least two different ‘db’ container instances:

PowerShell Output

* There is a chance that Docker will return the set of IPs making up the ‘db’ service in the same order as your first request. In this case, you may not see a different IP address. Repeat the ping command until you receive a reply from a new instance.

Technical Note: Service Discovery implemented in Windows

On Linux, the Docker daemon starts a new thread in each container namespace to catch service name resolution requests. These requests are sent to the Docker engine which implements a DNS resolver and responds back to the thread in the container with the IP address/es of the container instance/s which correspond to the service name.

In Windows, service discovery is implemented differently due to the need to support both Windows Server Containers (shared Windows kernel) and Hyper-V Containers (isolated Windows kernel). Instead of starting a new thread in each container, the primary DNS server for the Container endpoint’s IP interface is set to the default gateway of the (NAT) network. A request to resolve the service name will be sent to the default gateway IP where it is caught by the Windows Host Networking Service (HNS) in the container host. The HNS service then sends the request to the Docker engine which replies with the IP address/es of the container instance/s for the service. HNS then returns the service name (DNS) query to the container.