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アプリケーション内で をクリックすると、お使いのDataRobotバージョンに関する全プラットフォームドキュメントにアクセスできます。


実行中、エージェントは、設定されたディレクトリまたはメッセージキューイングシステムでバッファリングされたメッセージを探して転送します。バッファリングされたメッセージをMLOpsライブラリからDataRobot MLOpsに転送するには、以下に示すようにMLOpsエージェントをインストールして設定します。



> tar -xvf datarobot_mlops_package-*.tar.gz


> cd datarobot_mlops_package-*;
> <your-favorite-editor> ./conf/mlops.agent.conf.yaml




> cd datarobot_mlops_package-*;
> ./bin/


> export AGENT_CONFIG_YAML=<path/to/conf/mlops.agent.conf.yaml> ; \
            export AGENT_LOG_PROPERTIES=<path/to/conf/>; \
            export AGENT_JVM_OPT=-Xmx4G \
            export AGENT_JAR_PATH=<path/to/bin/mlops-agent-ver.jar> \
            sh -x /bin/

 # AGENT_CONFIG_YAML      environmment variable to override the default path to mlops.agent.conf.yaml
 # AGENT_LOG_PROPERTIES   environmment variable to override the default path to
 # AGENT_JVM_OPT          environmment variable to override the default JVM option `-Xmx4G`
 # AGENT_JAR_PATH         environmment variable to override the default JAR file path to agent-<ver>.jar


> ./bin/


> ./bin/ --verbose


> ./bin/



# URL to the DataRobot MLOps service
mlopsUrl: "https://<DATAROBOT_HOST>"

# DataRobot API token
apiToken: "FILL_IN_HERE"

# Execute the agent once, then exit
runOnce: false

# When dryrun mode is true, do not report the metrics to MLOps service
dryRun: false

# When verifySSL is true, SSL certification validation will be performed when
# connecting to MLOps DataRobot. When verifySSL is false, these checks are skipped.
# Note: It is highly recommended to keep this config variable as true.
verifySSL: true

# Path to the agent's log file
logPath: "./logs/mlops.agent.log"

# Path to write agent stats
statsPath: "/tmp/tracking-agent-stats.json"

# Number of times the agent will retry sending a request to the MLOps service on failure.
httpRetry: 1

# Http client timeout in milliseconds (30sec timeout)
httpTimeout: 30000

# Comment out and configure the lines below for the spooler type(s) you are using.
# Note: the spooler configuration must match that used by the MLOps library.
# Note: Spoolers must be set up before using them.
#       - For the filesystem spooler, create the directory that will be used.
#       - For the SQS spooler, create the queue.
#       - For the PubSub spooler, create the project and topic.
  - type: "FS_SPOOL"
    details: {name: "filesystem", directory: "/tmp/ta"}
#  - type: "SQS_SPOOL"
#    details: {name: "sqs", queueUrl: "your SQS queue URL", queueName: "<your AWS SQS queue name>"}
#  - type: "RABBITMQ_SPOOL"
#    details: {name: "rabbit", queueName: <your rabbitmq queue name>, queueUrl: "amqp://<ip address>"}
#  - type: "PUBSUB_SPOOL"
#    details: {name: "pubsub", projectId: <your project ID>, topicName: <your topic name>}

# The number of threads that the agent will launch to process data records.
agentThreadPoolSize: 4

# The maximum number of records each thread will process per fetchNewDataFreq interval.
agentMaxRecordsTask: 100

# Maximum number of records to aggregate before sending to MMM
agentMaxAggregatedRecords: 500

# A timeout for pending records before aggregating and submitting
agentPendingRecordsTimeoutMs: 2500

更新しました February 22, 2022
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