In that case, it could be better to have only 2 servers and use a higher percentage of their resources (CPU, memory, disk, network bandwidth, etc).

The **number of processes** on this image is **computed automatically** from the CPU **cores** available.

This means that it will try to **squeeze** as much **performance** from the CPU as possible.

You can also adjust it with the configurations using **environment variables**, etc.

But it also means that as the number of processes depends on the CPU the container is running, the **amount of memory consumed** will also depend on that.

        *   `tf.raw_ops.Bucketize` op on CPU.
        *   `tf.where` op for data types
            `tf.int32`/`tf.uint32`/`tf.int8`/`tf.uint8`/`tf.int64`.
        *   `tf.random.normal` op for output data type `tf.float32` on CPU.
        *   `tf.random.uniform` op for output data type `tf.float32` on CPU.
        *   `tf.random.categorical` op for output data type `tf.int64` on CPU.

*   `tensorflow.experimental.tensorrt`:

    * This solves a vulnerability that could allow denial of service attacks by using many small multipart fields/files (parts), consuming high CPU and memory.
    * Only applications using forms (e.g. file uploads) could be affected.
    * For most cases, upgrading won't have any breaking changes.

## 0.91.0

### Upgrades