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  1. ci/official/README.md

    from the `envs` directory that is filled with configuration options:
    
    -   Nightly jobs (Run nightly on the `nightly` branch)
        -   Uses `wheel.sh`, `libtensorflow.sh`, `code_check_full.sh`
    -   Continuous jobs (Run on every GitHub commit)
        -   Uses `pycpp.sh`
    -   Presubmit jobs (Run on every GitHub PR)
        -   Uses `pycpp.sh`, `code_check_changed_files.sh`
    
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  2. docs/distributed/README.md

    start using the least used cluster. This expansion strategy works endlessly, so you can perpetually expand your clusters as needed.  When you restart, it is immediate and non-disruptive to the applications. Each group of servers in the command-line is called a pool. There are 2 server pools in this example. New objects are placed in server pools in proportion to the amount of free space in each pool. Within each pool, the location of the erasure-set of drives is determined based on a deterministic hashing...
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  3. docs/tls/README.md

    Run the following command to generate a private `.key` file:
    
    ```
    certtool.exe --generate-privkey --outfile private.key
    ```
    
    A response similar to this one should be displayed:
    
    ```
    Generating a 3072 bit RSA private key...
    ```
    
    #### 3.3.3 Generate a public certificate
    
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  4. docs/debugging/README.md

    Wildcards can be used, for example `mc support inspect ALIAS/bucket/path/**/xl.meta` will collect all `xl.meta` recursively. `mc support inspect ALIAS/bucket/path/to/file.txt/*/part.*` will collect parts for all versions for the object located at `bucket/path/to/file.txt`.
    
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