.. _install_sandboxes_front_proxy:
Front Proxy
===========
To get a flavor of what Envoy has to offer as a front proxy, we are releasing a
`docker compose <https://docs.docker.com/compose/>`_ sandbox that deploys a front
envoy and a couple of services (simple flask apps) colocated with a running
service envoy. The three containers will be deployed inside a virtual network
called ``envoymesh``.
Below you can see a graphic showing the docker compose deployment:
.. image:: /_static/docker_compose_v0.1.svg
:width: 100%
All incoming requests are routed via the front envoy, which is acting as a reverse proxy sitting on
the edge of the ``envoymesh`` network. Port ``80`` is mapped to port ``8000`` by docker compose
(see :repo:`/examples/front-proxy/docker-compose.yml`). Moreover, notice
that all traffic routed by the front envoy to the service containers is actually routed to the
service envoys (routes setup in :repo:`/examples/front-proxy/front-envoy.yaml`). In turn the service
envoys route the request to the flask app via the loopback address (routes setup in
:repo:`/examples/front-proxy/service-envoy.yaml`). This setup
illustrates the advantage of running service envoys collocated with your services: all requests are
handled by the service envoy, and efficiently routed to your services.
Running the Sandbox
~~~~~~~~~~~~~~~~~~~
The following documentation runs through the setup of an envoy cluster organized
as is described in the image above.
**Step 1: Install Docker**
Ensure that you have a recent versions of ``docker, docker-compose`` and
``docker-machine`` installed.
A simple way to achieve this is via the `Docker Toolbox <https://www.docker.com/products/docker-toolbox>`_.
**Step 2: Docker Machine setup**
First let's create a new machine which will hold the containers::
$ docker-machine create --driver virtualbox default
$ eval $(docker-machine env default)
**Step 4: Clone the Envoy repo, and start all of our containers**
If you have not cloned the envoy repo, clone it with ``git clone git@github.com:envoyproxy/envoy``
or ``git clone https://github.com/envoyproxy/envoy.git``::
$ pwd
envoy/examples/front-proxy
$ docker-compose up --build -d
$ docker-compose ps
Name Command State Ports
-------------------------------------------------------------------------------------------------------------
example_service1_1 /bin/sh -c /usr/local/bin/ ... Up 80/tcp
example_service2_1 /bin/sh -c /usr/local/bin/ ... Up 80/tcp
example_front-envoy_1 /bin/sh -c /usr/local/bin/ ... Up 0.0.0.0:8000->80/tcp, 0.0.0.0:8001->8001/tcp
**Step 5: Test Envoy's routing capabilities**
You can now send a request to both services via the front-envoy.
For service1::
$ curl -v $(docker-machine ip default):8000/service/1
* Trying 192.168.99.100...
* Connected to 192.168.99.100 (192.168.99.100) port 8000 (#0)
> GET /service/1 HTTP/1.1
> Host: 192.168.99.100:8000
> User-Agent: curl/7.43.0
> Accept: */*
>
< HTTP/1.1 200 OK
< content-type: text/html; charset=utf-8
< content-length: 89
< x-envoy-upstream-service-time: 1
< server: envoy
< date: Fri, 26 Aug 2016 19:39:19 GMT
< x-envoy-protocol-version: HTTP/1.1
<
Hello from behind Envoy (service 1)! hostname: f26027f1ce28 resolvedhostname: 172.19.0.6
* Connection #0 to host 192.168.99.100 left intact
For service2::
$ curl -v $(docker-machine ip default):8000/service/2
* Trying 192.168.99.100...
* Connected to 192.168.99.100 (192.168.99.100) port 8000 (#0)
> GET /service/2 HTTP/1.1
> Host: 192.168.99.100:8000
> User-Agent: curl/7.43.0
> Accept: */*
>
< HTTP/1.1 200 OK
< content-type: text/html; charset=utf-8
< content-length: 89
< x-envoy-upstream-service-time: 2
< server: envoy
< date: Fri, 26 Aug 2016 19:39:23 GMT
< x-envoy-protocol-version: HTTP/1.1
<
Hello from behind Envoy (service 2)! hostname: 92f4a3737bbc resolvedhostname: 172.19.0.2
* Connection #0 to host 192.168.99.100 left intact
Notice that each request, while sent to the front envoy, was correctly routed
to the respective application.
**Step 6: Test Envoy's load balancing capabilities**
Now let's scale up our service1 nodes to demonstrate the clustering abilities
of envoy.::
$ docker-compose scale service1=3
Creating and starting example_service1_2 ... done
Creating and starting example_service1_3 ... done
Now if we send a request to service1 multiple times, the front envoy will load balance the
requests by doing a round robin of the three service1 machines::
$ curl -v $(docker-machine ip default):8000/service/1
* Trying 192.168.99.100...
* Connected to 192.168.99.100 (192.168.99.100) port 8000 (#0)
> GET /service/1 HTTP/1.1
> Host: 192.168.99.100:8000
> User-Agent: curl/7.43.0
> Accept: */*
>
< HTTP/1.1 200 OK
< content-type: text/html; charset=utf-8
< content-length: 89
< x-envoy-upstream-service-time: 1
< server: envoy
< date: Fri, 26 Aug 2016 19:40:21 GMT
< x-envoy-protocol-version: HTTP/1.1
<
Hello from behind Envoy (service 1)! hostname: 85ac151715c6 resolvedhostname: 172.19.0.3
* Connection #0 to host 192.168.99.100 left intact
$ curl -v $(docker-machine ip default):8000/service/1
* Trying 192.168.99.100...
* Connected to 192.168.99.100 (192.168.99.100) port 8000 (#0)
> GET /service/1 HTTP/1.1
> Host: 192.168.99.100:8000
> User-Agent: curl/7.43.0
> Accept: */*
>
< HTTP/1.1 200 OK
< content-type: text/html; charset=utf-8
< content-length: 89
< x-envoy-upstream-service-time: 1
< server: envoy
< date: Fri, 26 Aug 2016 19:40:22 GMT
< x-envoy-protocol-version: HTTP/1.1
<
Hello from behind Envoy (service 1)! hostname: 20da22cfc955 resolvedhostname: 172.19.0.5
* Connection #0 to host 192.168.99.100 left intact
$ curl -v $(docker-machine ip default):8000/service/1
* Trying 192.168.99.100...
* Connected to 192.168.99.100 (192.168.99.100) port 8000 (#0)
> GET /service/1 HTTP/1.1
> Host: 192.168.99.100:8000
> User-Agent: curl/7.43.0
> Accept: */*
>
< HTTP/1.1 200 OK
< content-type: text/html; charset=utf-8
< content-length: 89
< x-envoy-upstream-service-time: 1
< server: envoy
< date: Fri, 26 Aug 2016 19:40:24 GMT
< x-envoy-protocol-version: HTTP/1.1
<
Hello from behind Envoy (service 1)! hostname: f26027f1ce28 resolvedhostname: 172.19.0.6
* Connection #0 to host 192.168.99.100 left intact
**Step 7: enter containers and curl services**
In addition of using ``curl`` from your host machine, you can also enter the
containers themselves and ``curl`` from inside them. To enter a container you
can use ``docker-compose exec <container_name> /bin/bash``. For example we can
enter the ``front-envoy`` container, and ``curl`` for services locally::
$ docker-compose exec front-envoy /bin/bash
root@81288499f9d7:/# curl localhost:80/service/1
Hello from behind Envoy (service 1)! hostname: 85ac151715c6 resolvedhostname: 172.19.0.3
root@81288499f9d7:/# curl localhost:80/service/1
Hello from behind Envoy (service 1)! hostname: 20da22cfc955 resolvedhostname: 172.19.0.5
root@81288499f9d7:/# curl localhost:80/service/1
Hello from behind Envoy (service 1)! hostname: f26027f1ce28 resolvedhostname: 172.19.0.6
root@81288499f9d7:/# curl localhost:80/service/2
Hello from behind Envoy (service 2)! hostname: 92f4a3737bbc resolvedhostname: 172.19.0.2
**Step 8: enter containers and curl admin**
When envoy runs it also attaches an ``admin`` to your desired port. In the example
configs the admin is bound to port ``8001``. We can ``curl`` it to gain useful information.
For example you can ``curl`` ``/server_info`` to get information about the
envoy version you are running. Additionally you can ``curl`` ``/stats`` to get
statistics. For example inside ``frontenvoy`` we can get::
$ docker-compose exec front-envoy /bin/bash
root@e654c2c83277:/# curl localhost:8001/server_info
envoy 10e00b/RELEASE live 142 142 0
root@e654c2c83277:/# curl localhost:8001/stats
cluster.service1.external.upstream_rq_200: 7
...
cluster.service1.membership_change: 2
cluster.service1.membership_total: 3
...
cluster.service1.upstream_cx_http2_total: 3
...
cluster.service1.upstream_rq_total: 7
...
cluster.service2.external.upstream_rq_200: 2
...
cluster.service2.membership_change: 1
cluster.service2.membership_total: 1
...
cluster.service2.upstream_cx_http2_total: 1
...
cluster.service2.upstream_rq_total: 2
...
Notice that we can get the number of members of upstream clusters, number of requests
fulfilled by them, information about http ingress, and a plethora of other useful
stats.