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  1. docs/security/README.md

    #### Secure Erasure and Locking
    
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  2. cni/README.md

        - the actual code is in pkg/install - including a readiness probe, monitoring.
        - it also sets up a UDS socket for istio-cni to send logs to this container.
        - based on config, it may run the 'repair' controller that detects pods where istio setup fails and restarts them, or created in corner cases.
        - if ambient is enabled, also runs an ambient controller, watching Pod, Namespace
    
    - `istio-cni`
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  3. docs/config/README.md

    In most setups this will keep the scanner slow enough to not impact overall system performance. Setting the `delay` key to a *lower* value will make the scanner faster and setting it to 0 will make the scanner run at full speed (not recommended in production). Setting it to a higher value will make the scanner slower, consuming less resources with the trade off of not collecting metrics for operations like healing and disk usage as fast.
    
    ```
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  4. README.md

    for more complete documentation.
    
    ### Stable
    
    Run the following command to run the latest stable image of MinIO as a container using an ephemeral data volume:
    
    ```sh
    podman run -p 9000:9000 -p 9001:9001 \
      quay.io/minio/minio server /data --console-address ":9001"
    ```
    
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  5. operator/README.md

    ```bash
    kubectl create ns $WATCH_NAMESPACE --dry-run -o yaml | kubectl apply -f -
    kubectl create ns $LEADER_ELECTION_NAMESPACE --dry-run -o yaml | kubectl apply -f -
    ```
    
    1. From the istio repo root directory, run `go run ./operator/cmd/operator/*.go server`
    
    To use Remote debugging with IntelliJ, replace above step 2 with following:
    
    1. From `./operator/cmd/operator` path run
    `
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  6. docs/bigdata/README.md

    ## **4. Run Sample Applications**
    
    After installing Hive, Hadoop and Spark successfully, we can now proceed to run some sample applications to see if they are configured appropriately.  We can use Spark Pi and Spark WordCount programs to validate our Spark installation. We can also explore how to run Spark jobs from the command line and Spark shell.
    
    ### **4.1 Spark Pi**
    
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  7. docs/bucket/replication/README.md

    To perform bi-directional replication, repeat the above process on the target site - this time setting the source bucket as the replication target. It is recommended that replication be run in a system with at least two CPU's available to the process, so that replication can run in its own thread.
    
    ![put](https://raw.githubusercontent.com/minio/minio/master/docs/bucket/replication/PUT_bucket_replication.png)
    
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  8. README.md

        desired TensorFlow version, for example, branch `r2.8` for version 2.8.
    *   Apply (that is, cherry-pick) the desired changes and resolve any code
        conflicts.
    *   Run TensorFlow tests and ensure they pass.
    *   [Build](https://www.tensorflow.org/install/source) the TensorFlow pip
        package from source.
    
    ## Continuous build status
    
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  9. README.md

    <a href="https://platform.sh/try-it-now/?utm_source=fastapi-signup&utm_medium=banner&utm_campaign=FastAPI-signup-June-2023" target="_blank" title="Build, run and scale your apps on a modern, reliable, and secure PaaS."><img src="https://fastapi.tiangolo.com/img/sponsors/platform-sh.png"></a>
    <a href="https://www.porter.run" target="_blank" title="Deploy FastAPI on AWS with a few clicks"><img src="https://fastapi.tiangolo.com/img/sponsors/porter.png"></a>
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