All Projects → confluentinc → Confluent Hybrid Cloud Workshop

confluentinc / Confluent Hybrid Cloud Workshop

Licence: apache-2.0
Confluent Hybrid Cloud Workshop

Labels

Projects that are alternatives of or similar to Confluent Hybrid Cloud Workshop

Terraform Google Jenkins
This module handles the creation of a GCE instance running Jenkins, configured to run builds on Google Cloud.
Stars: ✭ 17 (-34.62%)
Mutual labels:  hcl
Hashiconf 2018
Stars: ✭ 23 (-11.54%)
Mutual labels:  hcl
Terraform Modules
Terraform Modules
Stars: ✭ 25 (-3.85%)
Mutual labels:  hcl
Rancher Flocker
Packaging and deploying Flocker on top of Rancher
Stars: ✭ 17 (-34.62%)
Mutual labels:  hcl
Jenkins Fargate
Stars: ✭ 22 (-15.38%)
Mutual labels:  hcl
Terraform Aws Openfaas Fargate
Create an OpenFaaS platform for AWS Fargate using Terraform
Stars: ✭ 24 (-7.69%)
Mutual labels:  hcl
Kallewheel
A custom color wheel extension for Adobe Photoshop
Stars: ✭ 16 (-38.46%)
Mutual labels:  hcl
Terraform Rancher Starter Template
Stars: ✭ 25 (-3.85%)
Mutual labels:  hcl
Terraform Openstack Rke
Terraform Openstack RKE
Stars: ✭ 23 (-11.54%)
Mutual labels:  hcl
Terraform Google Vault
Terraform module to deploy Vault as a container on Google Cloud Run
Stars: ✭ 25 (-3.85%)
Mutual labels:  hcl
Gitlab Ecs Terraform
Installing GitLab on Amazon ECS by Terraform
Stars: ✭ 18 (-30.77%)
Mutual labels:  hcl
Terraform Aks Autoscaler
AKS cluster with node autoscaler and horizontal pod autoscaler.
Stars: ✭ 19 (-26.92%)
Mutual labels:  hcl
Terraform Aws Docker
A POC using Terraform to create two EC2 instances running Docker with containerized Nginx daemon.
Stars: ✭ 24 (-7.69%)
Mutual labels:  hcl
Terraform Aws Vpc Peering
A Terraform module to configure a VPC Peering connection in AWS.
Stars: ✭ 17 (-34.62%)
Mutual labels:  hcl
Terraform Aws Config
A quick example of configuring the AWS Config service with terraform
Stars: ✭ 25 (-3.85%)
Mutual labels:  hcl
Terraform Google Gitlab Runner
Terraform module for provisioning a GitLab CI Runner in a GCP project using the docker+machine executor.
Stars: ✭ 17 (-34.62%)
Mutual labels:  hcl
Fdb Cloud Test
Packer + Terraform setup to experiment with FDB clusters in the cloud.
Stars: ✭ 23 (-11.54%)
Mutual labels:  hcl
Terraform Guides
Example usage of HashiCorp Terraform
Stars: ✭ 931 (+3480.77%)
Mutual labels:  hcl
Lambda Deployment Example
Automated Lambda Deployments with Terraform & CodePipeline
Stars: ✭ 25 (-3.85%)
Mutual labels:  hcl
Terraform Best Practices
Terraform Best Practices for AWS users
Stars: ✭ 931 (+3480.77%)
Mutual labels:  hcl

Confluent Hybrid-Cloud Workshop

Overview

This repository allows you to configure and provision a cloud-based workshop using your preferred cloud provider GCP, AWS or Azure. Each workshop participant connects to their own virtual machine and is intended to act as a psuedo on-premise datacenter. A single Confluent Cloud cluster is shared by all workshop participants.

For a single workshop participant, the logical architecture looks like this.

workshop

From a physical architecture point of view, each component, except for Confluent Cloud, is hosted on the participant's virtual machine.

Each workshop participant will work through a series of Labs to create the following ksqlDB Supply & Demand Application.

workshop

Prerequisites

  • macOS or Linux
  • Terraform 0.12.20 or later
  • Python + Yaml
  • A GCP/AWS/Azure account with the appropriate privileges
  • A Confluent Cloud Account
  • MongoDB Realm CLI (required if you use the MongoDB Atlas extension)

Provisioning a Workshop

Create an empty directory somewhere that will contain your workshop configuration file.

mkdir ~/myworkshop

Copy workshop-example-<cloud provider>.yaml to workshop.yaml in the directory you just created.

cp workshop-<cloud provider>-example.yaml ~/myworkshop/workshop.yaml

Edit ~/myworkshop/workshop.yaml and make the required changes.

Change your current directory to the root of the repository

cd ~/confluent-hybrid-cloud-workshop

To start provisioning the workshop, run workshop-create.py and pass in your workshop directory

python workshop-create.py --dir ~/myworkshop

When you are finished with the workshop you can destroy it using workshop-destroy.py

python workshop-destroy.py --dir ~/myworkshop

License

This project is licensed under the Apache 2.0 - see the LICENSE.md file for details

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].