A solution which scales both at the container and the IaaS levels for providing true compute elasticity, on-demand. Ideal for deploying workloads with variable footprint. Comes with an example monitoring stack.

• Realized using Azure VM Scale Sets
• Linux Diagnostics extension used for getting the guest VM metrics used for triggering scaling in/out based on CPU and Memory use.
• CPU bound tested with stress tool encapsulated as a docker image
• Azure deployment jsons created with acs-engine chosing DockerCE (Swarm Mode) orchestrator.
• Grafana dashboard json in /grafana directory.
• Docker experimental mode enabled before installing monitoring stack.
• All scripts in /scripts directory.
  • cputest (cputest.sh) is itself deployed as a swarm mode service in the global mode.
  • clean_swarm.sh utility for cleaning up "Down" nodes from swarm master after cluster scales in.
  • Additional container allocation visualization tool can be deployed using setup_visualizer.sh script. This needs to be run on the master on the "local" docker daemon bound to the docker0 eth interface.
  • deploy_monitoring.sh for deploying the monitoring stack consisting of the following components:
    • cAdvisor for container metrics,
    • node-exporter voor VM metrics,
    • Prometheus for making the time series data stream,
    • Grafana dashboard for displaying the metrics.

Architecture diagram is as follows:

Sample dashboard looks like following when cputest is running, demonstrating scaling out of the smarm mode cluster automatically and scaling in when cputest is stopped:

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