- The Mapping Object
- Automatic Retries
- Canary Releases
- Circuit Breakers
- Cross-Origin Resource Sharing
- Method-based Routing
- Prefix Regex
- Traffic Shadowing
- Developer Portal
- Edge Policy Console
- The Ambassador Module
- Gzip Compression
- Host CRD, ACME Support, and External Load Balancer Configuration
- Ingress Controller
- Troubleshooting Ambassador
- Custom Filters
- Knative Serverless Framework
- Prometheus monitoring
- Frequently Asked Questions
Edge Control is the command-line tool for installing and managing the Ambassador Edge Stack. And Edge Control's outbound and intercept features allow developers to preview changes to their services while sharing a single development cluster.
If you are a developer working on a service that depends on other in-cluster services, use
edgectl connect to set up connectivity from your laptop to the cluster. This allows software on your laptop, such as your work-in-progress service running in your debugger, to connect to other services in the cluster.
When you want to test your service with traffic from the cluster, use
edgectl intercept to designate a subset of requests for this service to be redirected to your laptop. You can use those requests to test and debug your local copy of the service. All other requests will go to the existing service running in the cluster without disruption.
Edge Control is available as a downloadable executable for both Mac OS X and Linux. While Edge Control clients are available for Windows, these binaries do not support Service Preview.
curl -fLO https://metriton.datawire.io/downloads/darwin/edgectlchmod a+x edgectlxattr -d com.apple.quarantine edgectl # Give OS X permission to run the executablemv edgectl ~/bin # Somewhere in your PATH
curl -fLO https://metriton.datawire.io/downloads/linux/edgectlchmod a+x edgectlmv edgectl ~/bin # Somewhere in your PATH
Make sure you've terminated the daemon.
$ edgectl quitEdge Control Daemon quitting...
Download the latest binary, as above, and replace your existing binary.
Service Preview creates a connection between your local environment and the cluster. These connections are managed through the Traffic Manager, which is deployed in your cluster, and the
edgectl daemon, which runs in your local environment.
There are three basic commands that are used for Service Preview:
- Launch the edgectl daemon:
$ sudo edgectl daemonLaunching Edge Control Daemon v1.3.2 (api v1)
- Connect your laptop to the cluster. This will enable your local environment to initiate traffic to the cluster.
$ edgectl connectConnecting to traffic manager in namespace ambassador...Connected to context k3s-default (https://172.20.0.3:6443)
- Set up an intercept rule. This will enable the cluster initiate traffic to your local environment.
$ edgectl intercept add hello -n example -m x-dev=jane -t localhost:9000
Connect to the cluster. This command allows your local environment to initiate traffic to the cluster, allowing services running locally to send and receive requests to cluster services.
$ edgectl connectConnecting to traffic manager in namespace ambassador...Connected to context gke_us-east1-b_demo-cluster (https://184.108.40.206)
In order to mediate traffic to your clusters, Edge Control inserts itself into the DNS for your host (this is why it requires root access to run). It intercepts queries to your system’s primary DNS server, responds to queries that have to do with connected clusters, and forwards any other queries on to a fallback DNS server.
By default, the daemon intercepts queries to the primary DNS server listed in
/etc/resolv.conf, and uses Google DNS on 220.127.116.11 or 18.104.22.168 for its fallback DNS server. You can override the choice of which DNS server to intercept using the
--dns option, and you can override the fallback server using the
It's important that the primary DNS server and the fallback server be different. Otherwise Edge Control would forward queries to itself, resulting in a DNS loop.
The daemon’s logging output may be found in
$ sudo edgectl daemonLaunching Edge Control Daemon v1.0.0-ea5 (api v1)
/etc/resolv.conf is correct, but you have a local DNS server available on 10.0.0.1 that should be used for non-cluster queries, you could run Configure fallback server:
$ sudo edgectl daemon --fallback 10.0.0.1Launching Edge Control Daemon v1.0.0-ea5 (api v1)
Disconnect from the cluster.
Intercept enables the cluster to initiate traffic to the local environment. To prevent unwanted traffic from being routed to the cluster,
intercept creates routing rules that specify which traffic to send to the local environment. An
intercept is created on a per (Kubernetes) deployment basis. Each deployment must have a traffic agent installed in order for
intercept to function.
List available Kubernetes deployments for intercept.
$ edgectl intercept availableFound 2 interceptable deployment(s):1. xyz in namespace default2. hello in namespace default
List the current active intercepts.
Add an intercept. The basic format of this command is:
edgectl intercept add DEPLOYMENT -n NAME -t [HOST:]PORT -m HEADER=REGEX ...
- DEPLOYMENT specifies a Kubernetes deployment with a traffic agent installed. You can get the list of available deployments with the
-nspecifies a name for an intercept.
-tspecifies the target of an intercept. Typically, this is a service running in the local environment that is a virtual replacement for the deployment in the cluster.
-mspecifies a match rule on requests. Requests that are sent to the traffic agent that match this rule will be routed to the target.
A few other options to
--namespaceto specify the Kubernetes namespace in which to create a mapping for intercept
-pwhich specifies a prefix to intercept (the default is
Intercept all requests to the
hello deployment that match the HTTP
x-dev header with a value of
jane to a service running locally on port 9000:
$ edgectl intercept add hello -n example -m x-dev=jane -t localhost:9000Added intercept "example"
Pause the daemon. The network overrides used by the edgectl daemon are temporarily disabled. Typically, this is used for connecting with a VPN that is not compatible with Edge Control.
$ edgectl pauseNetwork overrides paused.Use "edgectl resume" to reestablish network overrides.
Quit the daemon. Ensure that the daemon has quit prior to upgrades.
Resume the daemon. Used after
Print the status of Edge Control, including the Kubernetes context that is currently being used.
$ edgectl statusConnectedContext: gke_us-east1-b_demo-cluster (https://22.214.171.124)Proxy: ON (networking to the cluster is enabled)Interceptable: 2 deploymentsIntercepts: 0 total, 0 local
- Starting with an empty cluster, add the simple microservice from above.
$ kubectl get svc,deployNAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGEservice/kubernetes ClusterIP 10.43.0.1 <none> 443/TCP 27s$ kubectl apply -f hello.yamlservice/hello createddeployment.apps/hello created$ kubectl get svc,deployNAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGEservice/hello ClusterIP 10.43.111.189 <none> 80/TCP 7sservice/kubernetes ClusterIP 10.43.0.1 <none> 443/TCP 2m12sNAME READY UP-TO-DATE AVAILABLE AGEdeployment.extensions/hello 0/1 1 0 7s
- Use Edge Control to set up outbound connectivity to your cluster.
$ edgectl statusNot connected$ edgectl connectConnecting...Connected to context default (https://localhost:6443)Unable to connect to the traffic manager in your cluster.The intercept feature will not be available.Error was: kubectl get svc/deploy telepresency-proxy: exit status 1$ edgectl statusConnectedContext: default (https://localhost:6443)Proxy: ON (networking to the cluster is enabled)Intercepts: Unavailable: no traffic manager$ curl -L helloHello, world!
You are now able to connect to services directly from your laptop, as demonstrated by the
curl command above.
- When you’re done working with this cluster, disconnect.
$ edgectl disconnectDisconnected$ edgectl statusNot connected
- Install the traffic manager in your cluster and the traffic agent in the simple microservice as described above.
$ kubectl apply -f traffic-manager.yamlservice/telepresence-proxy createddeployment.apps/telepresence-proxy created$ kubectl apply -f hello-intercept.yamlservice/hello configureddeployment.apps/hello configured
- Launch a local service on your laptop. If you were debugging the hello service, you might run a local copy in your debugger. In this example, we will start an arbitrary service on port 9000.
$ # using Python$ python3 -m http.server 9000Serving HTTP on 0.0.0.0 port 9000 (http://0.0.0.0:9000/) ...[...]$ # using NodeJS$ npx http-server -p 9000npx: installed 27 in 1.907sStarting up http-server, serving ./Available on:http://127.0.0.1:9000http://10.213.69.250:9000Hit CTRL-C to stop the server[...]
- Connect to the cluster to set up outbound connectivity and check that you can access the hello service in the cluster with
$ edgectl connectConnecting...Connected to context default (https://localhost:6443)$ edgectl statusConnectedContext: default (https://localhost:6443)Proxy: ON (networking to the cluster is enabled)Interceptable: 1 deploymentsIntercepts: 0 total, 0 local$ curl -L helloHello, world!
- Set up an intercept. In this example, we’ll capture requests that have the x-dev header set to $USER.
$ edgectl intercept availFound 1 interceptable deployment(s):1. hello$ edgectl intercept listNo intercepts$ edgectl intercept add hello -n example -m x-dev=$USER -t localhost:9000Added intercept "example"$ edgectl intercept list1. exampleIntercepting requests to hello when- x-dev: ark3and redirecting them to localhost:9000$ curl -L helloHello, world!$ curl -L -H x-dev:$USER hello<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN" "http://www.w3.org/TR/html4/strict.dtd"><html><head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"><title>Directory listing for /</title></head><body><h1>Directory listing for /</h1><hr><ul></ul><hr></body></html>
As you can see, the second request, which includes the specified x-dev header, is served by the local server.
- Next, remove the intercept to restore normal operation.
$ edgectl intercept remove exampleRemoved intercept "example"$ curl -L -H x-dev:$USER helloHello, world!
Requests are no longer intercepted.
Multiple intercepts of the same deployment can run at the same time too. You can direct them to the same machine, allowing you to “or” together intercept conditions. Also, multiple developers can intercept the same deployment simultaneously. As long as their match patterns don’t collide, they don’t need to worry about disrupting one another.