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• Design Goal / Requirement

BD-703. To add Docker containers as a new granularity in the VM elasticity module, thus expands its functionality.

• Design questions and answers

  :

1. Should an extractor type be managed by both an VM image and docker, or only one of them?
   A: only one for simplicity. So need to specify this piece of information in the config file.
2. Docker image storage: docker hub, or a private registry?
   A: go with the docker hub for now. Setting up a private registry takes time and a secure one requires getting a certificate from a CA. Can do it later when needed. Use ncsa/clowder-ocr, ncsa/clowder-python-base, ncsa/clowder-opencv-closeups, etc. for now. Done.
3. How do we restart a docker container if the application crashed/stopped?
   A: docker run --restart=always ...
   This will retry indefinitely, but with a delay that doubles before each retry, starting from 100 ms (0.1 second), to avoid flooding the server. Can also consider using "--restart=on-failure[:max-retries]" to limit the number of retries, but then that could leave a container in the stopped state, without any component to restart it. Usually a RabbitMQ server restart would cause an error, and the error was observed to persist for about 2 minutes.
4. How do we scale up an application managed by docker?
   A: see below.
5. How do we scale down?
   A: see below.
   1. Do we suspend and resume docker VMs, or always keep them running?
      A: We suspend and resume docker VMs, but keep at least 1.
6. We need to run some VMs exclusively to host the docker containers. How do we start them – externally bootstrap, or start them using the elasticity module?
   A: need to add the docker VM image info in the config file, so the module knows how to start a new docker VM. Can start one at the beginning of the elasticity. Later on as needed start more.
7. How do we detect idle extractors managed by docker?
   A: Same logic using the RabbitMQ API as before. After detection, perform docker-specific commands to stop the idle extractors.
8. How do we detect idle docker machines if no container runs on them?
   A: add data structure for docker machines. Find docker VMs that have no extractors running on them, add them to the idle machine list, or somehow signal that they can be suspended.
9. How do we specify mapping of docker images with extractors?
   A: add a [Docker] section in the config file, with line items such as: "extr1: dockerimg1". When starting the elasticity module, load the config file, and check for errors: one extractor type should be managed only by one method: either docker or a VM image. If such configuration errors exist, print out, and use a default type such as docker – also make this choice a configurable item in the config file.

• Algorithm / Logic

Assumptions:

The following assumptions are made in the design:

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1. This logic is suitable for a production environment. For a testing environment or a system that's not busy, this logic could suspend many or even all VMs since there is not much or no request, and lead to a slow start – only the next time the check is done (say, every minute), this module will notice that the number of extractors for the queues are 0 and resume the VMs. We could make it configurable whether or not to maintain at least one extractor running for each queue – it's a balance of potential waste of system resource vs. fast processing startup time.
2. In the future, we could support migrating extractors. For example, if 4 extractors run on vm1, and only extractor 1 has work to do, and there is an open slot to run extractor 1 on vm2 (where extractor 1 is already running), we could migrate the extractor 1 instance from vm1 to vm2, and suspend vm1 – but this is considered lower priority.

• Programming Language and Application Type

Continue with the existing use of Python and a stand-alone program.

• Testing

• Input
  Use a script to generate high request rates with OCR, OpenCV extractors to test the scaling up part. Stop sending the requests to test the scaling down part.
• Output
  Use the OpenStack CLI / web UI for the VM part, RabbitMQ web UI and SSH into the docker machines for the extractor part, to verify that the docker containers are started/stopped, and docker VMs are started/resumed/suspended as expected.

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