Linkerd
Linkerd is a service mesh for Kubernetes. It makes running services easier and safer by giving you runtime debugging, observability, reliability, and security—all without requiring any changes to your code.
Step 0: Setup
Before we can do anything, we need to ensure you have access to modern Kubernetes cluster and a functioning kubectl command on your local machine. (If you don’t already have a Kubernetes cluster, one easy option is to run one on your local machine. There are many ways to do this, including kind, k3d, Docker for Desktop, and more.)
You can validate your setup by running:
You should see output with both a Client Version and Server Version component.
Now that we have our cluster, we’ll install the Linkerd CLI and use it validate that your cluster is capable of hosting the Linkerd control plane.
(Note: if you’re using a GKE “private cluster”, there are some extra steps required before you can proceed to the next step.)
Step 1: Install the CLI
If this is your first time running Linkerd, you will need to download the linkerd command-line interface (CLI) onto your local machine. The CLI will allow you to interact with your Linkerd deployment.
To install the CLI manually, run:
Be sure to follow the instructions to add it to your path.
Alternatively, if you use Homebrew, you can install the CLI with brew install linkerd. You can also download the CLI directly via the Linkerd releases page.
Once installed, verify the CLI is running correctly with:
You should see the CLI version, and also Server version: unavailable. This is because you haven’t installed the control plane on your cluster. Don’t worry—we’ll fix that soon enough.
Step 2: Validate your Kubernetes cluster
Kubernetes clusters can be configured in many different ways. Before we can install the Linkerd control plane, we need to check and validate that everything is configured correctly. To check that your cluster is ready to install Linkerd, run:
If there are any checks that do not pass, make sure to follow the provided links and fix those issues before proceeding.
Step 3: Install the control plane onto your cluster
Now that you have the CLI running locally and a cluster that is ready to go, it’s time to install the control plane.
The first step is to install the control plane core. To do this, run:
The linkerd install command generates a Kubernetes manifest with all the core control plane resources. (Feel free to inspect the output.) Piping this manifest into kubectl apply then instructs Kubernetes to add those resources to your cluster.
Note
Some control plane resources require cluster-wide permissions. If you are installing on a cluster where these permissions are restricted, you may prefer the alternative multi-stage install process, which will split these “sensitive” components into a separate, self-contained step which can be handed off to another party.
Now let’s wait for the control plane to finish installing. Depending on the speed of your cluster’s Internet connection, this may take a minute or two. Wait for the control plane to be ready (and verify your installation) by running:
Next, we’ll install some extensions. Extensions add non-critical but often useful functionality to Linkerd. For this guide, we will need:
The viz extension, which will install an on-cluster metric stack; or
The buoyant-cloud extension, which will connect to a hosted metrics stack.
For this guide, you can install either or both. To install the viz extension, run:
To install the buoyant-cloud extension, run:
Once you’ve installed your extensions, let’s validate everything one last time:
Assuming everything is green, we’re ready for the next step!
Step 4: Explore Linkerd!
With the control plane and extensions installed and running, we’re now ready to explore Linkerd! If you installed the viz extension, run:
You should see a screen like this:
If you installed the buoyant-cloud extension, run:
You should see a screen lke this:
Click around, explore, and have fun! One thing you’ll see is that, even if you don’t have any applications running on this cluster, you still have traffic! This is because Linkerd’s control plane components all have the proxy injected (i.e. the control plane runs on the data plane), so traffic between control plane compnments is also part of the mesh.
Step 5: Install the demo app
To get a feel for how Linkerd would work for one of your services, you can install a demo application. The emojivoto application is a standalone Kubernetes application that uses a mix of gRPC and HTTP calls to allow the users to vote on their favorite emojis.
Install emojivoto into the emojivoto namespace by running:
Before we mesh it, let’s take a look at the app. If you’re using Docker Desktop at this point you can visit http://localhost directly. If you’re not using Docker Desktop, we’ll need to forward the web-svc service. To forward web-svc locally to port 8080, you can run:
Now visit http://localhost:8080. Voila! The emojivoto app in all its glory.
Clicking around, you might notice that some parts of emojivoto are broken! For example, if you click on a doughnut emoji, you’ll get a 404 page. Don’t worry, these errors are intentional. (And we can use Linkerd to identify the problem. Check out the debugging guide if you’re interested in how to figure out exactly what is wrong.)
Next, let’s add Linkerd to emojivoto by running:
This command retrieves all of the deployments running in the emojivoto namespace, runs the manifest through linkerd inject, and then reapplies it to the cluster. The linkerd inject command adds annotations to the pod spec instructing Linkerd to “inject” the proxy as a container to the pod spec.
As with install, inject is a pure text operation, meaning that you can inspect the input and output before you use it. Once piped into kubectl apply, Kubernetes will execute a rolling deploy and update each pod with the data plane’s proxies, all without any downtime.
Congratulations! You’ve now added Linkerd to existing services! Just as with the control plane, it is possible to verify that everything worked the way it should with the data plane. To do this check, run:
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