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Boundary
HCP administration

Manage multi-hop sessions with HCP Boundary

  • 15min
  • |
  • HCP
  • Boundary

HCP Boundary allows organizations to register their own self-managed workers. Self-managed workers can be deployed in private networks while still communicating with an upstream HCP Boundary cluster.

Starting with Boundary 0.12, workers can be chained together through reverse-proxy connections. Multi-hop is when two or more workers are connected, creating multiple "hops" in the chain from a worker to a controller.

Note

Deploying self-managed workers with HCP Boundary requires the Boundary Enterprise binary for the Linux, MacOS, Windows or other system the worker is deployed on. The workers should also be up-to-date with the HCP control plane's version, otherwise new features will not work as expected. The control plane version can be checked in the HCP Boundary portal. Multi-hop sessions require the 0.12.0 version of the binary or greater.

HCP Boundary is an identity-aware proxy that sits between users and the infrastructure they want to connect to. The proxy has two components:

  1. A control plane that manages state around users under management, targets, and access policies.
  2. Worker nodes, assigned by the control plane once a user authenticates into HCP Boundary and selects a target.

Multi-hop introduces the concept of “upstream” and “downstream” workers. Viewing controllers as the “top” of a multi-hop chain, downstream workers are those below a worker in the chain, while upstreams are those above a worker in the chain. In the diagram below, worker2’s upstream is worker1, and its downstream is worker3.

Multi-Hop Workers

A chain of workers can be deployed in scenarios where inbound network traffic is not allowed. A worker in a private network will send outbound communication to its upstream worker, and can create reverse proxies for session establishment.

Multi-Hop Workers

Target worker filters can be used with workers to allow for fine grained control on which workers handle ingress and egress for session traffic to a target. Ingress worker filters determine which workers users will connect with to initiate a session, and egress worker filters determine which workers will be used to access targets.

The table below describes the features available in HCP Boundary vs Boundary Community Edition.

No filterIngress-onlyEgress-onlyIngress + Egress
CommunitySingle-hop, any workerXSingle-hop, worker selected with egress filterX
HCPSingle-hop, directly connected worker (will be HCP-managed)Single-hop, worker selected with ingress filterMulti-hop*, client connects to HCP worker as ingress worker, egress worker connects to hostMulti-hop*, client connects to ingress worker, egress worker connects to host
  • If egress and ingress worker filters result in the same selected worker(s), or an egress filter results in a single-hop route, this is effectively single-hop.

Note

Ingress worker filters are not available in Boundary Community Edition.

Multi-Hop Workers

This tutorial demonstrates the basics of deploying and managing workers in a multi-hop scenario using HCP Boundary.

Prerequisites

This tutorial assumes you have:

  • Access to an HCP Boundary instance
  • Completed the previous HCP Administration tutorials
  • A Boundary binary greater than 0.12.0 in your PATH. This tutorial uses the 0.13.2 version of Boundary.

This tutorial provides two options for configuring the multi-hop worker scenario:

  1. Configuring of a downstream worker using AWS
  2. Deploying a downstream worker locally as a proof-of-concept

Regardless of the method used, workers must install the HCP Boundary worker binary to be registered with HCP. If deploying a worker manually on AWS, you can follow this guide to create a publicly accessible Amazon EC2 instance to use for this tutorial.

Configure the downstream worker

To configure a downstream worker, the following details are required:

  • HCP Cluster URL (Boundary address)
  • Auth Method ID (from the Admin Console)
  • Admin login name and password

Visit the Getting Started on HCP tutorial if you need to locate any of these values. For a comprehensive guide on deploying a worker, review the Self-Managed Worker Registration with HCP Boundary tutorial.

Select the AWS or Local Worker workflows to continue the tutorial setup.

This tutorial picks up where the Self-Managed Worker Registration with HCP Boundary tutorial left off. This workflow assumes you already have an Ubuntu target and a pre-configured worker registered with HCP Boundary.

This workflow requires a publicly accessible Ubuntu instance to be used as a downstream worker. This setup is similar to the process for defining a single worker in the Self-Managed Worker Registration with HCP Boundary tutorial, with some additional configuration in the worker config file.

You should already have an Ubuntu target accessible via a worker. This worker can be considered the "upstream" worker, which the downstream worker will proxy traffic through when managing sessions to the target.

Multi-Hop Workers

This setup is designed to allow the target and egress worker to exist on their own private network, which the ingress worker will proxy the Boundary connection to. This allows the target to use a private IP address instead of the public address utilized in the previous tutorials. The extra steps of defining a private network are not taken in this tutorial.

Deploy an additional worker

The next step is to deploy a new egress worker in the downstream chain to the target. This new worker will be downstream of worker1 from the previous tutorial, and will serve as the new egress worker that establishes connections to targets. worker1 from the previous tutorial will now serve as the ingress worker, upstream from this new worker, worker2.

Note

You will need the public IP address of the upstream worker configured in the Self-Managed Worker Registration with HCP Boundary tutorial. Copy this value for use in the following steps.

Next, deploy an additional publicly accessible Ubuntu instance to be used as an downstream worker. You can follow this guide to create a publicly accessible Amazon EC2 instance to use for this tutorial.

Warning

For the purposes of this tutorial it is important that the security group policy for the AWS worker instance accepts incoming TCP connections on port 9202 to allow Boundary client connections. To learn more about creating this security group and attaching it to your instance, check the AWS EC2 security group documentation. The screenshot below shows an example of this security group policy.

AWS Worker Security Group

Log in and download Boundary Enterprise

Log in to the Ubuntu instance that will be configured as the downstream worker.

For example, using SSH:

$ ssh ubuntu@198.51.100.1 -i /path/my-key-pair.pem
The authenticity of host 'ec2-198-51-100-1.compute-1.amazonaws.com (198-51-100-1)' can't be established.
ECDSA key fingerprint is l4UB/neBad9tvkgJf1QZWxheQmR59WgrgzEimCG6kZY.
Are you sure you want to continue connecting (yes/no)? yes

ubuntu@ip-172-31-88-177:~

Note

The above example is for demonstrative purposes. You will need to supply your Ubuntu instance's username, public IP address, and public key to connect. If using AWS EC2, check this article to learn more about connecting to a Linux instance using SSH.

Create a new folder to store your Boundary config file. This tutorial creates the boundary/ directory in the user's home directory to store the worker config. If you do not have permission to create this directory, create the folder elsewhere.

$ mkdir /home/ubuntu/boundary/ && cd /home/ubuntu/boundary/

Next, download and install the Boundary Enterprise binary.

Note

The binary version should match the version of the HCP control plane. Check the control plane's version in the HCP Boundary portal, and download the appropriate version using wget. The example below installs the 0.13.2 version of the Boundary Enterprise binary, versioned as 0.13.2+ent.

Enter the following command to install the latest version of the Boundary Enterprise binary on Ubuntu.

$ curl -fsSL https://apt.releases.hashicorp.com/gpg | sudo gpg --dearmor -o /usr/share/keyrings/hashicorp-archive-keyring.gpg ;\
echo "deb [signed-by=/usr/share/keyrings/hashicorp-archive-keyring.gpg] https://apt.releases.hashicorp.com $(lsb_release -cs) main" | sudo tee /etc/apt/sources.list.d/hashicorp.list ;\
sudo apt update && sudo apt install boundary-enterprise -y

Once installed, verify the version of the boundary binary.

$ boundary version

Version information:
  Build Date:          2023-06-07T16:41:10Z
  Git Revision:        b1f75f5c731c843f5c987feae310d86e635806c7
  Metadata:            ent
  Version Number:      0.13.2+ent

Ensure the Version Number matches the version of the HCP Boundary control plane. They should match in order to get the latest HCP Boundary features.

Write the worker config

Note

This workflow utilizes a worker-initiated authorization flow to register with the HCP controller.

Next, create a new file named /home/ubuntu/boundary/downstream-worker.hcl.

$ touch /home/ubuntu/boundary/downstream-worker.hcl

Open the file with a text editor, such as Vi.

Paste the following configuration into the worker config file:

/home/ubuntu/boundary/downstream-worker.hcl

disable_mlock = true

listener "tcp" {
  address = "0.0.0.0:9202"
  purpose = "proxy"
}

worker {
  public_addr = "<worker_public_addr>"
  initial_upstreams = ["<upstream_worker_public_addr>:9202"]
  auth_storage_path = "/home/ubuntu/boundary/worker2"
  tags {
    type = ["worker2", "downstream"]
  }
}

Update the following values in the downstream-worker.hcl file:

  • <worker_public_addr> on line 9 should be replaced with the public IP address of this ubuntu egress worker, such as 18.206.227.218
  • <upstream_worker_public_addr> on line 10 should be replaced with the public IP address of the original ubuntu (ingress) worker, such as 107.22.128.152

The public_addr should match the public IP or DNS name of this Ubuntu instance being configured as an egress worker.

You set the initial_upstreams when you connect workers together as part of a multi-hop chain. In this example, the upstream is the ingress worker that you created in the previous tutorial, which has access to the HCP Boundary cluster.

The initial_upstreams should match the public IP or DNS name of your original worker Ubuntu instance deployed in the previous tutorial, and include the TCP listening port of worker1. It serves as the ingress worker and is "upstream" from the downstream egress worker being configured here.

Note the listener "tcp" stanza:

listener "tcp" {
  address = "0.0.0.0:9202"
  purpose = "proxy"
}

The address port is set to 0.0.0.0:9202. This port should already be configured by the AWS security group for this instance to accept inbound TCP connections. If a custom listener port is desired, it should be defined here.

Ensure that the initial_upstreams defined in the worker stanza include the TCP listening port of the ingress worker. For example:

worker {
  public_addr = "18.206.227.218"
  initial_upstreams = ["107.22.128.152:9202"]
  auth_storage_path = "/home/ubuntu/boundary/worker2"
  tags {
    type = ["worker2", "downstream"]
  }
}

In the above example initial_upstreams is specified, which indicates the address or addresses a worker will use when initially connecting to Boundary. The hcp_boundary_cluster_id should be omitted, since this worker will forward connections to an upstream worker, which in this case is the original worker1 ingress worker. Do not configure the hcp_boundary_cluster_id and initial_upstreams in the same config file, as the HCP cluster ID will take precedence over the initial upstreams.

To see all valid config options, refer to the worker configuration docs.

Save this file.

Start the downstream worker

With the worker config defined, start the worker server. Provide the full path to the worker config file (such as /home/ubuntu/boundary/downstream-worker.hcl).

$ boundary server -config="/home/ubuntu/boundary/downstream-worker.hcl"

==> Boundary server configuration:

                               Cgo: disabled
                        Listener 1: tcp (addr: "0.0.0.0:9202", max_request_duration: "1m30s", purpose: "proxy")
                         Log Level: info
                             Mlock: supported: true, enabled: false
                           Version: Boundary v0.13.2+ent
                       Version Sha: d8aaf3500f65fb7d605d27db232457fe3a26bf43
        Worker Auth Current Key Id: harddisk-stunt-serve-shininess-essay-courier-manger-deface
  Worker Auth Registration Request: GzusqckarbczHoLGQ4UA25uSRvw33DNChURoR2CF1BXRUm7frqLSncV64LeYWxQDCstE25Vj6QSBQ1aGh8BUo1dnz899rt3LgktzRGU4vWYcHmvPQKpsSUTJqA42nJxBfpxopKyCvzxZNxgbTSw5BNN9BUsnoy58niY5ui38NhKPKdmKjVDoU4TRVd4Bvti4F2H5C8pBB3qhY6qyeaSRoKjDcEzdTa7S3JicVzbtmfWnfyMLTJ21jRypH2S5haK4RBhFP319mw6DYNhVo7opBkBoW2FaaJbeowGj8b5wFX
          Worker Auth Storage Path: /home/ubuntu/boundary/worker2
          Worker Public Proxy Addr: 44.204.92.85:9202

==> Boundary server started! Log data will stream in below:

The downstream worker will start and begin attempting to connect to its upstream, worker1, which is also the ingress worker.

The worker also outputs its authorization request as Worker Auth Registration Request. This will also be saved to a file, auth_request_token, defined by the auth_storage_path in the worker config.

Note the Worker Auth Registration Request: value on line 12. This value can also be located in the /boundary/auth_request_token file. Copy this value.

Exit the downstream Ubuntu worker.

Register the worker with HCP

HCP workers can be registered using the Boundary CLI or Admin Console Web UI.

Authenticate to HCP Boundary as the admin user.

  1. Log in to the HCP portal.

  2. From the HCP Portal's Boundary page, click Open Admin UI - a new page will open.

  3. Enter the admin username and password you created when you deployed the new instance and click Authenticate.

Once logged in, navigate to the Workers page.

From the previous Self-Managed Worker Registration with HCP Boundary tutorial there should already be a worker registered.

Click New.

HCP Workers

The new worker page can be used to construct the contents of the downstream-worker.hcl file.

Do not fill in any of the worker fields.

Providing the following details will construct the worker config file contents for you:

  • Boundary Cluster ID
  • Worker Public Address
  • Config file path
  • Worker Tags

The instructions on this page provide details for installing the HCP boundary binary and deploying the constructed config file.

Because the worker has already been deployed, only the Worker Auth Registration Request key needs to be provided on this page.

Scroll down to the bottom of the New Worker page and paste the Worker Auth Registration Request key you copied earlier.

Click Register Worker.

HCP Workers

Click Done and notice the new worker on the Workers page.

HCP Workers

Worker-aware targets

From the Manage Targets tutorial you should already have the ubuntu-target configured in Boundary.

Boundary uses worker tags that define key-value pairs targets can use to determine where they should route connections.

A simple tag was included in the downstream-worker.hcl file from before:

worker {
  tags {
    type = ["worker2", "downstream"]
  }
}

This config creates the resulting tags on the worker:

Tags:
  Worker Configuration:
    type: ["worker2" "downstream"]
  Canonical:
    type: ["worker2" "downstream"]

The Tags can be used to create a worker filter for the target.

Open the Boundary Admin Console UI navigate to the Targets page within the IT_Support org.

Click on the ubuntu-target. Scroll to the bottom of the target details page and click Edit Form.

Toggle the Ingress worker filter switch to add an ingress worker filter that searches for workers with the upstream tag:

"upstream" in "/tags/type"

Toggle the Egress worker filter switch to add an egress worker filter that searches for workers that have the downstream tag:

"downstream" in "/tags/type"

HCP Workers

When finished, click Save.

Note

The type: "worker2" tag could have also been used for the egress filter, or a filter that searches for the name of the worker, if assigned. (such as "/name" == "downstream-worker").

With the filters assigned, any connections to this target will be forced to proxy through the ingress worker, which will forward connections to the next downstream worker until it reaches the egress worker. In this example only one "hop" is made directly from the ingress worker to the egress worker.

Finally, establish a connection to the target. Enter your instance's login name after the -l option and the path to your instance's public key after the -i option.

Note

The Boundary Desktop App can also be used to establish a session with the target and manage sessions.

$ boundary connect ssh -target-id $TARGET_ID -- -l ubuntu -i /path/to/key.pem

Welcome to Ubuntu 22.04 LTS (GNU/Linux 5.15.0-1011-aws x86_64)

 * Documentation:  https://help.ubuntu.com
 * Management:     https://landscape.canonical.com
 * Support:        https://ubuntu.com/advantage

  System information as of Tue Sep 20 17:54:00 UTC 2022

  System load:  0.0               Processes:             98
  Usage of /:   22.7% of 7.58GB   Users logged in:       0
  Memory usage: 25%               IPv4 address for eth0: 172.31.93.237
  Swap usage:   0%

 * Ubuntu Pro delivers the most comprehensive open source security and
   compliance features.

   https://ubuntu.com/aws/pro

0 updates can be applied immediately.


The list of available updates is more than a week old.
To check for new updates run: sudo apt update

Last login: Tue Sep 20 17:41:48 2022 from 44.194.155.74
To run a command as administrator (user "root"), use "sudo <command>".
See "man sudo_root" for details.

ubuntu@ip-172-31-93-237:~$

You can verify that the ingress worker handles the initial connection to the worker using the CLI or Admin Console.

Navigate to the Workers page while the connection to the Ubuntu target is still open.

Notice the Session Count next to the worker configured as the ingress worker.

HCP Workers

Sessions can be managed using the same methods discussed in the Manage Sessions tutorial.

When finished, the session can be terminated manually, or canceled via another authenticated Boundary command. Sessions can also be managed using the Admin Console UI.

Note

To cancel this session using the CLI, you will need to open a new terminal window and re-export the BOUNDARY_ADDR and BOUNDARY_AUTH_METHOD_ID environment variables. Then log back into Boundary using boundary authenticate.

Summary

The HCP Administration tutorial collection demonstrated the common HCP Boundary management workflows.

This tutorial demonstrated configuring multi-hop workers with HCP Boundary and discussed worker management.

To continue learning about Boundary, check out the Inject SSH credentials with HCP Boundary tutorial.

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This tutorial also appears in:

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    Worker management
    Learn about worker management.
    • Boundary