Source: Kubernetes best practices: mapping external services from Google Cloud Platform
By Sandeep Dinesh, Developer Advocate
If you’re like most Kubernetes users, chances are you use services that live outside your cluster. For example, maybe you use the Twillio API to send text messages, or maybe the Google Cloud Vision API to do image analysis.
If your applications in your different environments connect to the same external endpoint, and have no plans to bring the external service into your Kubernetes cluster, it is perfectly fine to use the external service endpoint directly in your code. However, there are many scenarios where this is not the case.
A good example of this are databases. While some cloud-native databases such as Cloud Firestore or Cloud Spanner use a single endpoint for all access, most databases have separate endpoints for different instances.
At this point, you may be thinking that a good solution to finding the endpoint is to use ConfigMaps. Simply store the endpoint address in a ConfigMap, and use it in your code as an environment variable. While this solution works, there are a few downsides. You need to modify your deployment to include the ConfigMap and write additional code to read from the environment variables. But most importantly, if the endpoint address changes you may need to restart all running containers to get the updated endpoint address.
In this episode of “Kubernetes best practices”, let’s learn how to leverage Kubernetes’ built-in service discovery mechanisms for services running outside the cluster, just like you can for services inside the cluster! This gives you parity across your dev and prod environments, and if you eventually move the service inside the cluster, you don’t have to change your code at all.
A very common scenario is when you are hosting your own database, but doing so outside the cluster, for example on a Google Compute Engine instance. This is very common if you run some services inside Kubernetes and some outside, or need more customization or control than Kubernetes allows.
Hopefully, at some point, you can move all services inside the cluster, but until then you are living in a hybrid world. Thankfully, you can use static Kubernetes services to ease some of the pain.
In this example, I created a MongoDB server using Cloud Launcher. Because it is created in the same network (or VPC) as the Kubernetes cluster, it can be accessed using the high performance internal IP address. In Google Cloud, this is the default setup, so there is nothing special you need to configure.
Now that we have the IP address, the first step is to create a service:
kind: Service apiVersion: v1 metadata: name: mongo Spec: type: ClusterIP ports: - port: 27017 targetPort: 27017
You might notice there are no Pod selectors for this service. This creates a service, but it doesn’t know where to send the traffic. This allows you to manually create an Endpoints object that will receive traffic from this service.
kind: Endpoints apiVersion: v1 metadata: name: mongo subsets: - addresses: - ip: 10.240.0.4 ports: - port: 27017
You can see that the Endpoints manually defines the IP address for the database, and it uses the same name as the service. Kubernetes uses all the IP addresses defined in the Endpoints as if they were regular Kubernetes Pods. Now you can access the database with a simple connection string:
No need to use IP addresses in your code at all! If the IP address changes in the future, you can update the Endpoint with the new IP address, and your applications won’t need to make any changes.
If you are using a hosted database service from a third party, chances are they give you a unified resource identifier (URI) that you can use to connect to. If they give you an IP address, you can use the method in Scenario 1.
In this example, I have two MongoDB databases hosted on mLab. One of them is my dev database, and the other is production.
The connection strings for these databases are as follows:
mLab gives you a dynamic URI and a dynamic port, and you can see that they are both different. Let’s use Kubernetes to create an abstraction layer over these differences. In this example, let’s connect to the dev database.
You can create a “ExternalName” Kubernetes service, which gives you a static Kubernetes service that redirects traffic to the external service. This service does a simple CNAME redirection at the kernel level, so there is very minimal impact on your performance.
The YAML for the service looks like this:
kind: Service apiVersion: v1 metadata: name: mongo spec: type: ExternalName externalName: ds149763.mlab.com
Now, you can use a much more simplified connection string:
Because “ExternalName” uses CNAME redirection, it can’t do port remapping. This might be okay for services with static ports, but unfortunately it falls short in this example, where the port is dynamic. mLab’s free tier gives you a dynamic port number and you cannot change it. This means you need a different connection string for dev and prod.
However, if you can get the IP address, then you can do port remapping as I will explain in the next section.
While the CNAME redirect works great for services with the same port for each environment, it falls short in scenarios where the different endpoints for each environment use different ports. Thankfully we can work around that using some basic tools.
The first step is to get the IP address from the URI.
If you run the nslookup, hostname, or ping command against the URI, you can get the IP address of the database.
You can now create a service that remaps the mLab port and an endpoint for this IP address.
kind: Service apiVersion: v1 metadata: name: mongo spec: ports: - port: 27017 targetPort: 49763 --- kind: Endpoints apiVersion: v1 metadata: name: mongo subsets: - addresses: - ip: 220.127.116.11 ports: - port: 49763
Note: A URI might use DNS to load-balance to multiple IP addresses, so this method can be risky if the IP addresses change! If you get multiple IP addresses from the above command, you can include all of them in the Endpoints YAML, and Kubernetes will load balance traffic to all the IP addresses.
With this, you can connect to the remote database without needing to specify the port. The Kubernetes service does the port remapping transparently!
Mapping external services to internal ones gives you the flexibility to bring these services into the cluster in the future while minimizing refactoring efforts. Even if you don’t plan to bring them in today, you never know what tomorrow might bring! Additionally, it makes it easier to manage and understand which external services your organization is using.
If the external service has a valid domain name and you don’t need port remapping, then using the “ExternalName” service type is an easy and quick way to map the external service to an internal one. If you don’t have a domain name or need to do port remapping, simply add the IP addresses to an endpoint and use that instead.
Going to Google Cloud Next18? Stop by to meet me and other Kubernetes team members in the “Meet the Experts” zone! Hope to see you there!