[tensorflow/build Docker images](https://hub.docker.com/r/tensorflow/build)
    (`tensorflow/tensorflow:devel` and `tensorflow/tensorflow:devel-gpu` are no
    longer supported for development). Use TF SIG Build Dockerfiles in
    development to avoid installing the packages directly on your system (in
    which case remember to change the directory from `/root` to `/tensorflow`

Docker installed on your machine. Download the relevant installer from [here](https://www.docker.com/community-edition#/download).

## Run Standalone MinIO on Docker

*Note*: Standalone MinIO is intended for early development and evaluation. For production clusters, deploy a [Distributed](https://docs.min.io/community/minio-object-store/operations/deployments/baremetal-deploy-minio-as-a-container.html) MinIO deployment.

    "path": "platforms/native/platform-native",
    "unitTests": true,
    "functionalTests": true,
    "crossVersionTests": false
  },
  {
    "name": "plugin-development",
    "path": "platforms/extensibility/plugin-development",
    "unitTests": true,
    "functionalTests": true,
    "crossVersionTests": true
  },
  {
    "name": "plugin-use",
    "path": "platforms/extensibility/plugin-use",

 * during handshake, and then take the agreed masterSecret from private fields of the session.
 *
 * Copy WireSharkKeyLoggerListener to your test code to use in development.
 *
 * This logs TLSv1.2 on a JVM (OpenJDK 11+) without any additional code.  For TLSv1.3
 * an existing external tool is required.
 *

Containers also have their own **isolated** running processes (commonly just one process), file system, and network, simplifying deployment, security, development, etc.

## What is a Container Image { #what-is-a-container-image }

A **container** is run from a **container image**.

TensorFlow has several execution modes, with Eager-mode being the default in v2.
Eager mode lets users write imperative-style statements that can be easily
inspected and debugged and it is intended to be used during the development
phase.

As part of the differences that make Eager mode easier to debug, the [shape
inference
functions](https://www.tensorflow.org/guide/create_op#define_the_op_interface)

2. Provide graceful fallback mechanisms
3. Extensive testing with various server configurations
4. Phased rollout with beta testing

## Resource Requirements

### Development Team
- 2-3 Senior Java developers with SMB protocol expertise
- 1 QA engineer for test infrastructure
- 1 DevOps engineer for CI/CD setup

### Timeline
- **Total Duration**: 6-8 months for all features

├── main/resources/
│   ├── suggest_indices/            # Index mappings and settings
│   └── suggest_settings/           # Default configurations
└── test/                          # Comprehensive test suite
```

## Development

### Building from Source

```bash
# Clone the repository
git clone https://github.com/codelibs/fess-suggest.git
cd fess-suggest

# Compile the project
mvn compile

# Run tests

* der Serverworker
* der Uvicorn-Worker
* der Gunicorn-Worker
* der Workerprozess
* die Workerklasse
* die Workload

* das Deployment
* deployen

* das SDK
* das Software Development Kit

* der `APIRouter`
* die `requirements.txt`
* das Bearer-Token
* der Breaking Change
* der Bug
* der Button
* das Callable
* der Code
* der Commit
* der Contextmanager

And it will work and will be useful **during development**.

But if your connection to the server is lost, the **running process** will probably die.