This directory contains test certificates used for testing ssl handling.

These keystores and certificates can be used via applying the `elasticsearch.test-with-ssl` plugin.

The generated certificates are valid till 05. Jun 2030.

The certificates are generated using catch-all SAN in the following procedure:

1. Generate the node's keystore:

        result.output.contains("AnotherTest6 total executions: 2")
        result.output.contains("> There were failing tests. See the report at:")
    }

    def "reruns tests till max rerun count is reached"() {
        when:
        buildFile.text = """
        plugins {
          id 'java'
          id 'elasticsearch.internal-test-rerun'
        }

        repositories {

                           TF_Status*);

// TF_ExecuteOperation will, if in eager mode, execute, if in graph mode, maybe
// capture some inputs and then add a node in the graph. The output tensors are
// returned through the provided TF_OutputList.
// Any active tape will observe the effects of this execution.
void TF_ExecuteOperation(TF_AbstractOp* op, int num_inputs,

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            V1Field["Pydantic v1 Model"]
        end
        subgraph V1["Pydantic v1 Model"]
            V2Field["Pydantic v2 Model"]
        end
    end

    style V2 fill:#f9fff3
    style V1 fill:#fff6f0
    style V1Field fill:#fff6f0
    style V2Field fill:#f9fff3
```

...but, you can have separated models using Pydantic v1 and v2 in the same app.

```mermaid
graph TB
    subgraph "✅ Supported"
        direction TB

numpy>=2.2.6 ; python_version == "3.14"
wheel ~= 0.41.2
h5py >= 3.11.0, < 3.15.0 ; python_version <= "3.13"
h5py ~= 3.15.1 ; python_version == "3.14"
lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.4, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras

        assertSame(b, reused, "Buffer should be reused from cache");
        // And it should still be zeroed
        for (byte value : reused) {
            assertEquals(0, value, "Reused buffer must be zeroed");
        }
    }

    // Edge: cache size 0 means nothing is cached; release still zeroes argument
    @Test
    @DisplayName("Cache size 0: release zeroes but does not cache; getBuffer allocates new")

/// info

If you are using containers, for example with Docker or Kubernetes, I'll tell you more about that in the next chapter: [FastAPI in Containers - Docker](docker.md).

In particular, when running on **Kubernetes** you will probably **not** want to use workers and instead run **a single Uvicorn process per container**, but I'll tell you about it later in that chapter.

///

## Multiple Workers { #multiple-workers }

        These advantages can take
        [many forms](https://github.com/google/guava/wiki/PhilosophyExplained#utility), but taking
        the time to discuss them in detail will make it much clearer why this feature should be
        added to Guava.


        Please fill out the following fields to give us a better understanding of your proposed
        feature and its potential value for other Guava users.

  - type: textarea
    attributes:

# Requirements for NumPy 1.x
numpy ~= 1.26.0
wheel ~= 0.41.2
h5py >= 3.11.0, < 3.15.0
lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version