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Realtime Compute for Apache Flink:Configure a job deployment

Last Updated:Nov 18, 2025

Before you start a Realtime Compute for Apache Flink deployment, you must configure the deployment. This topic describes how to configure a deployment.

Prerequisites

  • The required permissions are granted to the Alibaba Cloud account or RAM user that you want to use to access a namespace in the Realtime Compute for Apache Flink console and perform operations such as deployment resource configuration. For more information, see Grant permissions on namespaces.

  • A deployment is created. For more information, see Create a deployment.

Procedure

  1. Log on to the management console of Realtime Compute for Apache Flink.

  2. Find the workspace that you want to manage and click Console in the Actions column.

  3. In the left-side navigation pane, choose O&M > Deployments. On the Deployments page, click the name of the development that you want to manage.

  4. On the Configuration tab, find the section in which you want to configure parameters and click Edit in the upper-right corner.

    Note

    You must go back to the Development > ETL page to edit and deploy the deployment when you configure the basic configuration for the deployment. After you click Edit in the upper-right corner of the Basic section, a message appears. If you want to edit the deployment, click OK.

  5. Modify the configurations of the deployment.

    You can modify the deployment configurations in the following sections:

  6. After the configurations are complete, click Save.

Basic

Deployment type

Description

SQL deployment

You can write SQL code and configure the Engine Version, Additional Dependencies, Description, and Label parameters. For more information about the parameters, see Develop an SQL draft.

Note

After you click Edit in the upper-right corner of the Basic section, a message appears. If you want to modify the deployment configurations, click OK. Then, you are redirected to the SQL Editor page to edit and deploy the deployment.

JAR deployment

You can configure the Engine Version, JAR Uri, Entry Point Class, Entry Point Main Arguments, Additional Dependencies, Description, Kerberos Name, and Label parameters. For more information about the parameters, see Create a deployment.

Python deployment

You can configure the Engine Version, Python Uri, Entry Module, Entry Point Main Arguments, Python Libraries, Python Archives, Additional Dependencies, Description, Kerberos Name, and Label parameters. For more information about the parameters, see Create a deployment.

Parameters

Parameter

Description

Checkpointing Interval

The interval at which a checkpoint is generated. If you do not configure this parameter, the checkpointing feature is disabled.

Checkpointing Timeout time

Default value: 10. Unit: minutes. If a checkpoint is not generated within the time specified by this parameter, the checkpoint generation fails.

Min Interval Between Checkpoints

The minimum interval between two checkpoints. If the maximum parallelism of checkpoints is 1, this parameter specifies the minimum interval between the two checkpoints.

State Expiration Time

The time-to-live (TTL) of the state data of a deployment. Default value: 36 h. The default value indicates that the state data of a deployment expires after 36 hours. The system automatically removes the expired data.

Important

The default value is determined based on the best practices of Alibaba Cloud. This default value is different from the default value of the TTL provided by Apache Flink. The default value of the TTL provided by Apache Flink is 0, which indicates that the state data does not expire.

The first time data enters the system and is processed, the data is stored in the state backend memory. If data with the same primary key value enters the system, the system performs data computation based on the stored state data and updates the access time of the data. This process is the core of Realtime Compute for Apache Flink and relies on continuously processed streaming data. If the data is not accessed again within the specified TTL, the system considers the data as expired data and removes the data from the state backend storage.

You must properly configure the TTL to ensure accurate data computing and timely removal of expired data. This reduces the usage of state backend memory, eases the burden on the system memory, and improves computing efficiency and system stability.

Flink Restart Policy

Job restart behavior is determined by two policies: job restart and task failure recovery policies.

Job restart policy

This policy controls whether the entire job attempts to restart after a failure.

  • If job restart policy is not explicitly set and checkpointing is enabled, the job will attempt to restart at the Fixed Delay interval.

  • If job restart policy is not explicitly set and checkpointing is disabled, the job will not restart.

Explicitly configure job restart policy

Override the default behavior by setting one of these policies:

  • No Restarts: The job will not restart if it fails.

  • Fixed Delay (default): The job will attempt to restart at a fixed interval. Change the values of the Number of Restart Attempts and Delay Between Restart Attempts parameters as needed.

  • Failure Rate: Restarts the job based on a defined failure rate.

    Set Failure Rate Interval, Max Failures per Interval, and Delay Between Restart Attempts as needed.

Task failure recovery policy

This policy controls how individual tasks within a job are restarted after failure. This is configured via the jobmanager.execution.failover-strategy parameter in the Other Configuration section. Valid values:

  • full: Restarts the entire job if any task fails.

  • region (default): Restarts only the minimum set of tasks required to recover a failed region, minimizing impact.

For more information, see Task Failure Recovery in the Apache Flink documentation.

Note

If a task fails and the failover strategy is set to region, Flink will restart only the affected pipelined region. Other regions will continue to run unaffected. This means that different regions may have different start timestamps, which is normal behavior.

Other Configuration

Other Realtime Compute for Apache Flink settings. For example, you can specify akka.ask.timeout: 10 or jobmanager.execution.failover-strategy: full.

Logging

Parameter

Description

Log Archiving

Specifies whether to enable log archiving. By default, Allow Log Archives is turned on. After you turn on Allow Log Archives in the Logging section, you can view the logs of a historical deployment on the Logs tab. For more information, see View the logs of a historical deployment.

Note
  • In Ververica Runtime (VVR) 3.X, only VVR 3.0.7 and later minor versions support the log archiving feature.

  • In VVR 4.X, only VVR 4.0.11 and later minor versions support the log archiving feature.

Log Archives Expires

The validation period of archived log files. By default, the archived log files are valid for seven days.

Root Log Level

The root log levels. You can specify one of the following levels that are listed in ascending order of urgency:

  1. TRACE: records finer-grained information than DEBUG logs.

  2. DEBUG: records the status of the system.

  3. INFO: records important system information.

  4. WARN: records information about potential issues.

  5. ERROR: records information about errors and exceptions that occur.

Log Levels

The log name and log level.

Logging Profile

The log template that you want to use. You can select default or Custom Template from the drop-down list. If you select Custom Template, you can export logs to other storage services. For more information, see Configure parameters to export logs of a deployment.

References

  • You can configure the TTL for the state data of an operator to control the size of the state data. This reduces the resource consumption of deployments that have a large amount of state data. For more information, see the "State TTL hints" section of the Hints topic.

  • The log parameter configurations that are described in this topic are configurations for a single deployment. For more information about how to configure parameters to export the logs of all deployments in a namespace, see the "Configure parameters to export the logs of all deployments in a namespace" section of the Configure parameters to export logs of a deployment topic.