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Kubernetes Reverse Proxy

access_time Updated Dec 5, 2022

Introduction

In this example, the Signal Sciences agent runs in a sidecar container and proxies all incoming requests for inspection before sending them upstream to the application container.

Integrating the Signal Sciences Agent

The Signal Sciences Agent can be installed as a sidecar into each pod or as a service for some specialized needs.

The recommended way of installing the Signal Sciences Agent in Kubernetes is by integrating the sigsci-agent into a pod as a sidecar. This means adding the sigsci-agent as an additional container to the Kubernetes pod. As a sidecar, the agent will scale with the app/service in the pod instead of having to do this separately. However, in some situations, it may make more sense to install the sigsci-agent container as a service and scale it separately from the application.

The sigsci-agent container can be configured in various ways depending on the installation type and module being used.

You can use the preStop container hook to slow the pod's shutdown and ensure drain timeouts are met.

preStop:
  exec:
    command:
      - sleep
      - "30"

Getting and Updating the Signal Sciences Agent Container Image

An official signalsciences/sigsci-agent container image is available from the Signal Sciences account on Docker Hub.

Alternatively, if you want to build your own image or need to customize the image, then follow the sigsci-agent build instructions.

These instructions reference the latest version of the agent with imagePullPolicy: Always, which will pull the latest agent version even if one already exist locally. This is so the documentation does not fall out of date and anyone using this will not have an agent that stays stagnant. However, this may not be what if you need to keep installations consistent or on a specific version of the agent. In these cases, you should specify an agent version. Images on Docker Hub are tagged with their versions and a list of versions is available on Docker Hub.

Whether you choose to use the latest image or a specific version, there are a few items to consider to keep the agent up-to-date:

Using the latest Signal Sciences Container Image

If you do choose to use the latest image, then you will want to consider how you will keep the agent up to date.

  • If you have used the imagePullPolicy: Always option, then the latest image will be pulled on each startup and your agent will continue to get updates.

  • Alternatively, you may instead choose to manually update the local cache by periodically forcing a pull instead of always pulling on startup:

    docker pull signalsciences/sigsci-agent:latest
    

    Then, use latest with imagePullPolicy: Never set in the configuration so that pulls are never done on startup (only manually as above):

    - name: sigsci-agent
       image: signalsciences/sigsci-agent:latest
       imagePullPolicy: Never
       ...
    

Using a Versioned Signal Sciences Container Image

To use a specific version of the agent, replace latest with the agent version. You may also want to change imagePullPolicy: IfNotPresent in this case as the image should not change.

- name: sigsci-agent
   image: signalsciences/sigsci-agent:4.1.0
   imagePullPolicy: IfNotPresent
   ...

This will pull the specified agent version and cache it locally. If you use this method, then it is recommended that you parameterize the agent image, using Helm or similar, so that it is easier to update the agent images later on.

Using a Custom Tag for the Signal Sciences Container Image

It is also possible to apply a custom tag to a local agent image. To do this, pull the agent image (by version or use latest), apply a custom tag, then use that custom tag in the configuration. You will need to specify imagePullPolicy: Never so local images are only updated manually. After doing so, you will need to periodically update the local image to keep the agent up-to-date.

For example:

docker pull signalsciences/sigsci-agent:latest
docker tag signalsciences/sigsci-agent:latest signalsciences/sigsci-agent:testing

Then use this image tag in the configuration:

- name: sigsci-agent
   image: signalsciences/sigsci-agent:testing
   imagePullPolicy: Never
...

Configuring the Signal Sciences Agent Container

Agent configuration is normally done via the environment. Most configuration options are available as environment variables. Environment variables names have the configuration option name all capitalized, prefixed with SIGSCI_ and any dashes (-) changed to underscores (_). For example, the max-procs option would become the SIGSCI_MAX_PROCS environment variable. For more details on what options are available, see the Agent Configuration documentation.

The sigsci-agent container has a few required options that need to be configured:

  • Agent credentials (Agent Access Key and Agent Secret Key).

  • A volume to write temporary files.

Agent Credentials

The sigsci-agent credentials are configured with two environment variables. These variables must be set or the agent will not start.

  • SIGSCI_ACCESSKEYID: The Agent Access Key identifies which site in the Signal Sciences console that the agent is configured for.
  • SIGSCI_SECRETACCESSKEY: The Agent Secret Key is the shared secret key to authenticate and authorize the agent.

The credentials can be found by following these steps:

  1. Log in to the Signal Sciences console.

  2. Select a site if you have more than one site.

  3. Click Agents in the navigation bar. The agents page appears.

  4. Click View agent keys. The agent keys window appears.

    The 'View agent keys' button.
  5. Copy the Agent Access Key and Agent Secret Key.

    The agent keys window.

Because of the sensitive nature of these values, we recommend you use the built in secrets functionality of Kubernetes. With this configuration, the agent will pull the values from the secrets data instead of reading hardcoded values into the deployment configuration. This also makes any desired agent credential rotation easier to manage by having to change them in only one place.

Use the valueFrom option instead of the value option to utilize the secrets functionality. For example:

env:
 - name: SIGSCI_ACCESSKEYID
   valueFrom:
     secretKeyRef:
       # Update "my-site-name-here" to the correct site name or similar identifier
       name: sigsci.my-site-name-here
       key: accesskeyid
 - name: SIGSCI_SECRETACCESSKEY
   valueFrom:
     secretKeyRef:
       # Update "my-site-name-here" to the correct site name or similar identifier
       name: sigsci.my-site-name-here
       key: secretaccesskey

The secrets functionality keeps secrets in various stores in Kubernetes. This guide uses the generic secret store in its examples, however any equivalent store can be used. Agent secrets can be added to the generic secret store using YAML similar to the following example:

apiVersion: v1
kind: Secret
metadata:
  name: sigsci.my-site-name-here
stringData:
  accesskeyid: 12345678-abcd-1234-abcd-1234567890ab
  secretaccesskey: abcdefg_hijklmn_opqrstuvwxy_z0123456789ABCD

This can also be created from the command line with kubectl such as with the following example:

kubectl create secret generic sigsci.my-site-name-here \
  --from-literal=accesskeyid=12345678-abcd-1234-abcd-1234567890ab \
  --from-literal=secretaccesskey=abcdefg_hijklmn_opqrstuvwxy_z0123456789ABCD

Additional information about Kubernetes secrets functionality can be found here.

Agent Temporary Volume

For added security, we recommended the sigsci-agent container be executed with the root filesystem mounted as read only. However, the agent still needs to write some temporary files such as the socket file for RPC communication and some periodically updated files such as GeoIP data.

To accomplish this with a read only root filesystem, there needs to be a writeable volume mounted. This writeable volume can also be shared to expose the RPC socket file to other containers in the same pod.

The recommended way of creating a writeable volume is to use the builtin emptyDir volume type. This is typically configured in the volumes section of a deployment, as shown in the following example:

volumes:
 - name: sigsci-tmp
   emptyDir: {}

Containers will then mount this volume at /sigsci/tmp:

volumeMounts:
 - name: sigsci-tmp
   mountPath: /sigsci/tmp

The default in the official agent container image is to have the temporary volume mounted at /sigsci/tmp. If this needs to be moved for the agent container, then the following agent configuration options should also be changed from their defaults to match the new mount location:

  • rpc-address defaults to /sigsci/tmp/sigsci.sock
  • shared-cache-dir defaults to /sigsci/tmp/cache

Signal Sciences agent as a reverse proxy in front of a web application without the Signal Sciences module

If your web application does not support a Signal Sciences Module (or you prefer not to install a module), then you can configure the sigsci-agent container to run as a reverse proxy in front of the web application in the same pod.

To configure the Signal Sciences agent to run in reverse proxy mode in a sidecar container, you must:

  • Add the sigsci-agent container to the pod, configured in reverse proxy mode to:

    • listen for incoming requests (on a new port or by reconfiguring your application or Kubernetes service accordingly)
    • proxy requests to your web application container
  • Add an emptyDir{} volume as a place for the sigsci-agent to write temporary data.

The following configuration exposes an example application (helloworld) on port 8000, adding the sigsci-agent as a reverse proxy listener on a new port 8001 with an upstream of the example web application port 8000.

Add the Signal Sciences agent as a reverse proxy

...
      containers:
      # Example helloworld app running on port 8000 without sigsci configured
      - name: helloworld
        image: signalsciences/example-helloworld:latest
        imagePullPolicy: IfNotPresent
        args:
        - localhost:8000
        ports:
        - containerPort: 8000
      # Signal Sciences Agent running in reverse proxy mode (SIGSCI_REVPROXY_LISTENER configured)
      - name: sigsci-agent
        image: signalsciences/sigsci-agent:latest
        imagePullPolicy: Always
        env:
        - name: SIGSCI_ACCESSKEYID
          valueFrom:
            secretKeyRef:
              name: sigsci.my-site-name-here
              key: accesskeyid
        - name: SIGSCI_SECRETACCESSKEY
          valueFrom:
            secretKeyRef:
              name: sigsci.my-site-name-here
              key: secretaccesskey
        # Configure the revproxy listener to listen on a new port 8001
        # forwarding to the app on the original port 8000 as the upstream
        - name: SIGSCI_REVPROXY_LISTENER
          value: "http:{listener='http://0.0.0.0:8001',upstreams='http://0.0.0.0:8000',access-log='/dev/stdout'}"
        ports:
        - containerPort: 8001
        securityContext:
          # The sigsci-agent container should run with its root filesystem read only
          readOnlyRootFilesystem: true
        volumeMounts:
        # Default volume mount location for sigsci-agent writeable data
        # NOTE: Also change `SIGSCI_SHARED_CACHE_DIR` (default `/sigsci/tmp/cache`)
        #       if mountPath is changed, but best not to change.
        - name: sigsci-tmp
          mountPath: /sigsci/tmp

Note: The above modification assumes that sigsci secrets were added to the system.

Adding the Signal Sciences agent temp volume definition to the deployment

You must define the agent temp volume for use by the other containers in the pod. This example uses the builtin emptyDir: {} volume type.

...
      volumes:
      # Define a volume where sigsci-agent will write temp data and share the socket file,
      # which is required with the root filesystem is mounted read only
      - name: sigsci-tmp
        emptyDir: {}

Changing the service definition and adding the Signal Sciences agent as a reverse proxy

In the example above, the sigsci-agent reverse proxy listens on a new port, leaving the original application listener in place. You may wish for requests to be routed to the sigsci-agent at the original application port to make the agent addition as seamless as possible. One way to do this is to modify the Kubernetes service definition to route traffic to the sigsci-agent reverse proxy listener port instead of directly to the web application.

Change the service definition to point to the Signal Sciences agent port

Change the service targetPort from pointing directly to the application, to instead point to the sigsci-agent reverse proxy listener port. The sigsci-agent will then proxy to the application port:

apiVersion: v1
kind: Service
metadata:
  name: helloworld
  labels:
    app: helloworld
spec:
  ports:
  - name: http
    port: 8000
    # Target is now sigsci-agent on port 8001
    targetPort: 8001
  selector:
    app: helloworld
  type: LoadBalancer