COPY --from=build /go/bin/mc* /usr/bin/
COPY --from=build /go/bin/cur* /usr/bin/

COPY CREDITS /licenses/CREDITS
COPY LICENSE /licenses/LICENSE
COPY dockerscripts/docker-entrypoint.sh /usr/bin/docker-entrypoint.sh

EXPOSE 9000
VOLUME ["/data"]

ENTRYPOINT ["/usr/bin/docker-entrypoint.sh"]

				max="${backup.max.history}" compressionLevel="9" />
		</RollingFile>
	</Appenders>

	<Loggers>
		<Logger name="org.codelibs.fess" additivity="false" level="${log.level}">
			<AppenderRef ref="AppFile" />
		</Logger>
		<Root level="${root.log.level}">
			<AppenderRef ref="AppFile" />
		</Root>
	</Loggers>

				max="${backup.max.history}" compressionLevel="9" />
		</RollingFile>
	</Appenders>

	<Loggers>
		<Logger name="org.codelibs.fess" additivity="false" level="${log.level}">
			<AppenderRef ref="AppFile" />
		</Logger>
		<Root level="${root.log.level}">
			<AppenderRef ref="AppFile" />
		</Root>
	</Loggers>

	replicationRecentBacklogCount      = "recent_backlog_count"
)

var (
	replicationAverageActiveWorkersMD = NewGaugeMD(replicationAverageActiveWorkers,
		"Average number of active replication workers")
	replicationAverageQueuedBytesMD = NewGaugeMD(replicationAverageQueuedBytes,
		"Average number of bytes queued for replication since server start")
	replicationAverageQueuedCountMD = NewGaugeMD(replicationAverageQueuedCount,

        FATAL,
    }

    /** Factory for LoggerAdapter */
    protected static final LoggerAdapterFactory factory = getLoggerAdapterFactory();

    /** Map of loggers keyed by class */
    protected static final Map<Class<?>, Logger> loggers = newHashMap();

    /** Flag indicating initialization is complete. */
    private static boolean initialized;

    /** Logger adapter. */
    private final LoggerAdapter log;

ics-vidhya/deploy-machine-learning-models-with-keras-fastapi-redis-and-docker-4940df614ece title: Deploy Machine Learning Models with Keras, FastAPI, Redis and Docker - author: Mandy Gu author_link: https://towardsdatascience.com/@mandygu link: https://towardsdatascience.com/deploying-iris-classifications-with-fastapi-and-docker-7c9b83fdec3a title: 'Towards Data Science: Deploying Iris Classifications with FastAPI and Docker' - author: Michael Herman author_link: https://testdriven.io/authors/herman...

Pour plus de détails, consultez le [guide d'installation](https://fess.codelibs.org/14.17/install/index.html).

### Docker

Nous fournissons des images Docker sur [ghcr.io](https://github.com/orgs/codelibs/packages). Nous fournissons également un fichier Docker Compose (YAML) dans [ce dépôt](https://github.com/codelibs/docker-fess/tree/master/compose). 

### Interface Web

- Interface de recherche : http://localhost:8080/

    $ ./bin/fess

Para mais detalhes, veja o [Guia de Instalação](https://fess.codelibs.org/14.17/install/index.html).

### Docker

Nós fornecemos imagens Docker em [ghcr.io](https://github.com/orgs/codelibs/packages). Também fornecemos um arquivo Docker Compose (YAML) neste [repositório](https://github.com/codelibs/docker-fess/tree/master/compose).

### Interface do Navegador

- Interface de Busca: http://localhost:8080/

# MinIO Server Throttling Guide [![Slack](https://slack.min.io/slack?type=svg)](https://slack.min.io) [![Docker Pulls](https://img.shields.io/docker/pulls/minio/minio.svg?maxAge=604800)](https://hub.docker.com/r/minio/minio/)

MinIO server allows to throttle incoming requests:

- limit the number of active requests allowed across the cluster
- limit the wait duration for each request in the queue

# Deploy MinIO on Kubernetes [![Slack](https://slack.min.io/slack?type=svg)](https://slack.min.io)  [![Docker Pulls](https://img.shields.io/docker/pulls/minio/minio.svg?maxAge=604800)](https://hub.docker.com/r/minio/minio/)