Kubernetes Envoy
Last updated 2023-05-04
In this example, the Signal Sciences agent runs in a Docker sidecar and communicates directly with an Envoy proxy deployed on the application.
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.
1preStop:2 exec:3 command:4 - sleep5 - "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 This is so the documentation does not fall out of date and anyone using this will not have an agent that stays stagnant.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:latestThen, use
latest
withimagePullPolicy: Never
set in the configuration so that pulls are never done on startup (only manually as above):1- name: sigsci-agent2 image: signalsciences/sigsci-agent:latest3 imagePullPolicy: Never4 ...
Using a versioned Signal Sciences container image
To use a specific version of the agent, replace latest
with the agent version (represented here by x.xx.x
). You may also want to change imagePullPolicy: IfNotPresent
in this case as the image should not change.
1- name: sigsci-agent2 image: signalsciences/sigsci-agent:x.xx.x3 imagePullPolicy: IfNotPresent4 ...
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:
1- name: sigsci-agent2 image: signalsciences/sigsci-agent:testing3 imagePullPolicy: Never4...
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:
Log in to the Signal Sciences console.
From the Sites menu, select a site if you have more than one site.
Click Agents in the navigation bar. The agents page appears.
Click View agent keys. The agent keys window appears.
Copy the Agent Access Key and Agent Secret Key.
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 use the secrets
functionality. For example:
1env:2 - name: SIGSCI_ACCESSKEYID3 valueFrom:4 secretKeyRef:5 # Update my-site-name-here to the correct site name or similar identifier6 name: sigsci.my-site-name-here7 key: accesskeyid8 - name: SIGSCI_SECRETACCESSKEY9 valueFrom:10 secretKeyRef:11 # Update my-site-name-here to the correct site name or similar identifier12 name: sigsci.my-site-name-here13 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:
1apiVersion: v12kind: Secret3metadata:4 name: sigsci.my-site-name-here5stringData:6 accesskeyid: 12345678-abcd-1234-abcd-1234567890ab7 secretaccesskey: abcdefg_hijklmn_opqrstuvwxy_z0123456789ABCD
This can also be created from the command line with kubectl
such as with the following example:
1$ kubectl create secret generic sigsci.my-site-name-here \2 --from-literal=accesskeyid=12345678-abcd-1234-abcd-1234567890ab \3 --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:
1volumes:2 - name: sigsci-tmp3 emptyDir: {}
Containers will then mount this volume at /sigsci/tmp
:
1volumeMounts:2 - name: sigsci-tmp3 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
Integrating the Signal Sciences agent into an Envoy Proxy
You can deploy the Signal Sciences Agent for integration with the Envoy Proxy via the External Authorization (ext_authz
), HTTP filter. This filter communicates with the sigsci-agent
via gRPC.
Generic Envoy Proxy
Configuration for Envoy and the Signal Sciences agent are documented with the other modules in the Envoy install guide. This guide is for deploying the Signal Sciences agent as a sidecar to your existing Envoy configuration. Deploying the sigsci-agent
container as a sidecar to Envoy is similar to a typical module based deployment, but configuration is slightly different.
To deploy the Signal Sciences agent as a sidecar to Envoy, you must:
- Modify your existing Envoy configuration as noted in the Envoy install guide.
- Add the
sigsci-agent
container to the pod, configured in Envoy gRPC listener mode. - Add an
emptyDir{}
volume as a place for thesigsci-agent
to write temporary data.
Modifying the Envoy Proxy configuration
Modify your existing Envoy configuration as detailed in the Envoy install guide.
Add the Signal Sciences Agent as an Envoy gRPC Service:
1...2 containers:3 # Example Envoy front proxy running on port 80004 - name: envoy-frontproxy5 image: signalsciences/envoy-frontproxy:latest6 imagePullPolicy: IfNotPresent7 args:8 - -c9 - /etc/envoy/envoy.yaml10 - --service-cluster11 - front-proxy12 - -l13 - info14 ports:15 - containerPort: 800016 # Example helloworld app running on port 8080 without sigsci configured (accessed via Envoy proxy)17 - name: helloworld18 image: signalsciences/example-helloworld:latest19 imagePullPolicy: IfNotPresent20 args:21 # Address for the app to listen on22 - localhost:808023 ports:24 - containerPort: 808025 # Signal Sciences Agent running in Envoy gRPC mode (SIGSCI_ENVOY_GRPC_ADDRESS configured)26 - name: sigsci-agent27 image: signalsciences/sigsci-agent:latest28 imagePullPolicy: IfNotPresent29 # Configure the agent to use Envoy gRPC on port 999930 env:31 - name: SIGSCI_ACCESSKEYID32 valueFrom:33 secretKeyRef:34 # This secret needs added (see docs on sigsci secrets)35 name: sigsci.my-site-name-here36 key: accesskeyid37 - name: SIGSCI_SECRETACCESSKEY38 valueFrom:39 secretKeyRef:40 # This secret needs added (see docs on sigsci secrets)41 name: sigsci.my-site-name-here42 key: secretaccesskey43 # Configure the Envoy to expect response data (if using a gRPC access log config for Envoy)44 - name: SIGSCI_ENVOY_EXPECT_RESPONSE_DATA45 value: "1"46 # Configure the Envoy gRPC listener address on any unused port47 - name: SIGSCI_ENVOY_GRPC_ADDRESS48 value: localhost:999949 ports:50 - containerPort: 999951 securityContext:52 # The sigsci-agent container should run with its root filesystem read only53 readOnlyRootFilesystem: true
Adding the Signal Sciences agent temp volume definition to the deployment
The agent temp volume must be defined for use by the other containers in the pod. This example uses the builtin emptyDir: {}
volume type:
1...2 volumes:3 # Define a volume where sigsci-agent will write temp data and share the socket file,4 # which is required with the root filesystem is mounted read only5 - name: sigsci-tmp6 emptyDir: {}
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