# These are supported funding model platforms

github: [jinzhu]
patreon: jinzhu

Sebastián Ramírez <******@****.***> 1589724233 +0200

    steps:
      - name: Stop old running containers (if any)
        shell: bash
        run: |
          running_containers=$(docker ps -q) && \
          if [[ $running_containers == "" ]]; then
            echo "No running containers";
          else
            echo "Running container(s) found" && \
            docker stop $running_containers;
          fi
          docker container prune -f

        pyver: ['3.10']
    steps:
      - name: Stop old running containers (if any)
        shell: bash
        run: |
          running_containers=$(docker ps -q) && \
          if [[ $running_containers == "" ]]; then
            echo "No running containers";
          else
            echo "Running container(s) found" && \
            docker stop $running_containers;
          fi
          docker container prune -f

    assertLessThan(NEW, STARTING);
    assertLessThan(NEW, TERMINATED);

    assertLessThan(STARTING, RUNNING);
    assertLessThan(STARTING, STOPPING);
    assertLessThan(STARTING, FAILED);

    assertLessThan(RUNNING, STOPPING);
    assertLessThan(RUNNING, FAILED);

    assertLessThan(STOPPING, FAILED);
    assertLessThan(STOPPING, TERMINATED);
  }

// Package-wide variables from generator "generated".
option go_package = "k8s.io/api/node/v1beta1";

// Overhead structure represents the resource overhead associated with running a pod.
message Overhead {
  // podFixed represents the fixed resource overhead associated with running a pod.
  // +optional
  map<string, k8s.io.apimachinery.pkg.api.resource.Quantity> podFixed = 1;
}

research](https://scholar.google.com/scholar?q=gpu+side+channel) shows that it
might be possible to use side channel attacks on the GPU to leak data from other
running models or processes in the same system. GPUs can also have
implementation bugs that might allow attackers to leave malicious code running
and leak or tamper with applications from other users. Please report
vulnerabilities to the vendor of the affected hardware accelerator.

Let's check back those deployment concepts from before:

* Security - HTTPS
* Running on startup
* Restarts
* **Replication (the number of processes running)**
* Memory
* Previous steps before starting

Up to this point, with all the tutorials in the docs, you have probably been running a **server program** like Uvicorn, running a **single process**.

// Package-wide variables from generator "generated".
option go_package = "k8s.io/api/node/v1";

// Overhead structure represents the resource overhead associated with running a pod.
message Overhead {
  // podFixed represents the fixed resource overhead associated with running a pod.
  // +optional
  map<string, k8s.io.apimachinery.pkg.api.resource.Quantity> podFixed = 1;
}

// Package-wide variables from generator "generated".
option go_package = "k8s.io/api/node/v1alpha1";

// Overhead structure represents the resource overhead associated with running a pod.
message Overhead {
  // podFixed represents the fixed resource overhead associated with running a pod.
  // +optional
  map<string, k8s.io.apimachinery.pkg.api.resource.Quantity> podFixed = 1;
}