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Running Python based service on Giant Swarm

Here we show how suricate can be run using giantswarm.io. Giant Swarm is a cool solution to run your containerized app in the cloud. Especially the environment & companies concept makes it a compelling solution to do your devops.

Setup

Setup swarm command and log-in:

$ swarm login

Create a company & switch to a dev environment:

$ swarm company create engjoy
$ swarm env engjoy/dev

The basics - pushing the suricate image

Login, build the image (use this Dockerfile) and push it up:

$ sudo docker login https://registry.giantswarm.io
$ sudo docker build -t registry.giantswarm.io/engjoy/suricate:1.1 .
$ sudo docker push registry.giantswarm.io/engjoy/suricate:1.1

Create the swarm configuration

Pretty straight forward - very similar to how you would write a docker-compose file. See the references for all the details.

$ cat swarm.json
...

Note that we have not take into account auto-scaling etc. This is just a single user dev environment. It is recommend to use TLS & sth like oauth2 to make suricate multi-tenant and more secure.

Run it and check status

$ swarm up
$ swarm status suricate
$ swarm stats <instance id>

Now you can visit the URL provided too you to access suricate.

To tear it down & cleanup:

$ swarm stop
$ swarm delete

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Python based data science service running on GiantSwarm

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