EdgeSentinel Deployment Guide
3 min
this document aims to describe the process of deploying the edgesentinel control plane edgesentinel is a platform that applies configuration and services to a fleet of fws (for fw deployment help, reach out to info\@seastreet com ) edgesentinel is a microservice based architecture with services deployed as containers this document provides the necessary steps to deploy or gain access to a running edgesentinel control plane there are a few different ways to gain access to a running environment cloud hosted a control plane hosted in the cloud that sea street deploys and manages access to this can be set up many different ways, to inquire about this option email info\@seastreet com self hosted docker environment this option is for engineers who want to install docker themselves and manage pulling edgesentinel container images themselves vm image sea street currently offers a qcow2 image for easy deploy including docker and the full suite of edgesentinel containers the rest of this document will describe the deploy and startup steps for ' self hosted docker ' and ' edgesentinel vm image ' self hosted docker prerequisites before deploying the control plane verify you have the following docker installed on the device that is to run the control plane recommended compute requirements on that device 16 gb ram 8 vcpu 50 gb disk sea street has provided you with a user and token to their github container registry that hosts the edgesentinel container images note this can be requested by emailing info\@seastreet com deployment steps this guide will provide steps to install the container images that make up the edgesentinel control plane once installed, additional steps are provided for starting/stopping the platform clone repository https //github com/seastreettechnologies/seastreet eval git on the device to host the control plane follow the readme md instructions in the following directory {{install location}}seastreet eval/deployment/controlplane/docker/readme md note after following those instructions, you should have a running edgesentinel on that device see section 'verify deployment' to verify the control plane is actively running edgesentinel vm image prerequisites before deploying the control plane image, verify you have the following a hypervisor that can support qcow2 images vm size recommendation 16 gb ram 8 vcpu 50 gb disk sea street has provided you with a user and token to their github container registry that hosts the edgesentinel image note this can be requested by emailing info\@seastreet com to request a different image type, please email info\@seastreet com deployment steps this section will install the vm image that represents the edgesentinel control plane once installed, steps to start/stop the platform on that vm this image contains linux os docker application edgesentinel container images download vm image from sea street the edgesentinel image may be downloaded from ghcr io with the orasclient , found here https //oras land/docs/installation install this client before running the following commands run command in terminal window oras login ghcr io username {{username}} you will be prompted for a 'password ' provide the token given to you by sea street run command in terminal window oras pull ghcr io/seastreettechnologies/edgesentinel controlplane eval qcow2\ oras eval 1 0 0 rc 3 at this point, you will have the image in hand load the image into your hypervisor per their documentation and start the vm start/stop edgesentinel log into the console of that vm navigate to the following directory /home/eval/docker cd /home/eval/docker run the following command to create and start all of the services docker compose up detach run the following command to stop all of the services docker compose down note 'docker compose down' will blow away the db running on the control plane only run if you want to start fresh verify deployment log into a browser on the machine that hosts edgesentinel or has access to it go to http //{{host/ip of vm}} 8080/firewall api/swagger ui/index html verify the browser loads a swagger ui that looks like the following

