Menu
AWS Database Migration Service
User Guide (Version API Version 2016-01-01)

Monitoring Tasks in AWS Database Migration Service

You can monitor the progress of your task by checking the task status and by monitoring the task's control table. For more information about control tables, see Control Table Task Settings.

You can also monitor the progress of your tasks using Amazon CloudWatch. By using the AWS Management Console, the AWS Command Line Interface (CLI), or AWS DMS API, you can monitor the progress of your task and also the resources and network connectivity used.

Finally, you can monitor the status of your source tables in a task by viewing the table state.

Note that the "last updated" column the DMS console only indicates the time that AWS DMS last updated the table statistics record for a table. It does not indicate the time of the last update to the table.

For more information, see the following topics.

Task Status

The task status indicated the condition of the task. The following table shows the possible statuses a task can have:

Task Status Description

Creating

AWS DMS is creating the task.

Running

The task is performing the migration duties specified.

Stopped

The task is stopped.

Stopping

The task is being stopped. This is usually an indication of user intervention in the task.

Deleting

The task is being deleted, usually from a request for user intervention.

Failed

The task has failed. See the task log files for more information.

Starting

The task is connecting to the replication instance and to the source and target endpoints. Any filters and transformations are being applied.

Ready

The task is ready to run. This status usually follows the "creating" status.

Modifying

The task is being modified, usually due to a user action that modified the task settings.

The task status bar gives an estimation of the task's progress. The quality of this estimate depends on the quality of the source database’s table statistics; the better the table statistics, the more accurate the estimation. For tasks with only one table that has no estimated rows statistic, we are unable to provide any kind of percentage complete estimate. In this case, the task state and the indication of rows loaded can be used to confirm that the task is indeed running and making progress.

Table State During Tasks

The AWS DMS console updates information regarding the state of your tables during migration. The following table shows the possible state values:


                     AWS Database Migration Service replication instance
State Description

Table does not exist

AWS DMS cannot find the table on the source endpoint.

Before load

The full load process has been enabled, but it hasn't started yet.

Full load

The full load process is in progress.

Table completed

Full load has completed.

Table cancelled

Loading of the table has been cancelled.

Table error

An error occurred when loading the table.

Monitoring Replication Tasks Using Amazon CloudWatch

You can use Amazon CloudWatch alarms or events to more closely track your migration. For more information about Amazon CloudWatch, see What Are Amazon CloudWatch, Amazon CloudWatch Events, and Amazon CloudWatch Logs? in the Amazon CloudWatch User Guide. Note that there is a charge for using Amazon CloudWatch.

The AWS DMS console shows basic CloudWatch statistics for each task, including the task status, percent complete, elapsed time, and table statistics, as shown following. Select the replication task and then select the Task monitoring tab.


                AWS DMS monitoring

The AWS DMS console shows performance statistics for each table, including the number of inserts, deletions, and updates, when you select the Table statistics tab.


                AWS DMS monitoring

In addition, if you select a replication instance from the Replication Instance page, you can view performance metrics for the instance by selecting the Monitoring tab.


                AWS DMS monitoring

Data Migration Service Metrics

AWS DMS provides statistics for the following:

  • Host Metrics – Performance and utilization statistics for the replication host, provided by Amazon CloudWatch. For a complete list of the available metrics, see Replication Instance Metrics.

  • Replication Task Metrics – Statistics for replication tasks including incoming and committed changes, and latency between the replication host and both the source and target databases. For a complete list of the available metrics, see Replication Task Metrics.

  • Table Metrics – Statistics for tables that are in the process of being migrated, including the number of insert, update, delete, and DDL statements completed.

Task metrics are divided into statistics between the replication host and the source endpoint, and statistics between the replication host and the target endpoint. You can determine the total statistic for a task by adding two related statistics together. For example, you can determine the total latency, or replica lag, for a task by combining the CDCLatencySource and CDCLatencyTarget values.

Task metric values can be influenced by current activity on your source database. For example, if a transaction has begun, but has not been committed, then the CDCLatencySource metric continues to grow until that transaction has been committed.

For the replication instance, the FreeableMemory metric requires clarification. Freeable memory is not a indication of the actual free memory available. It is the memory that is currently in use that can be freed and used for other uses; it's is a combination of buffers and cache in use on the replication instance.

While the FreeableMemory metric does not reflect actual free memory available, the combination of the FreeableMemory and SwapUsage metrics can indicate if the replication instance is overloaded.

Monitor these two metrics for the following conditions.

• The FreeableMemory metric approaching zero.

• The SwapUsage metric increases or fluctuates.

If you see either of these two conditions, they indicate that you should consider moving to a larger replication instance. You should also consider reducing the number and type of tasks running on the replication instance. Full Load tasks require more memory than tasks that just replicate changes.

Replication Instance Metrics

Replication instance monitoring include Amazon CloudWatch metrics for the following statistics:

CPUUtilization

The amount of CPU used.

Units: Bytes

FreeStorageSpace

The amount of available storage space.

Units: Bytes

FreeableMemory

The amount of available random access memory.

Units: Bytes

WriteIOPS

The average number of disk I/O operations per second.

Units: Count/Second

ReadIOPS

The average number of disk I/O operations per second.

Units: Count/Second

WriteThroughput

The average number of bytes written to disk per second.

Units: Bytes/Second

ReadThroughput

The average number of bytes read from disk per second.

Units: Bytes/Second

WriteLatency

The average amount of time taken per disk I/O operation.

Units: Seconds

ReadLatency

The average amount of time taken per disk I/O operation.

Units: Seconds

SwapUsage

The amount of swap space used on the replication instance.

Units: Bytes

NetworkTransmitThroughput

The outgoing (Transmit) network traffic on the replication instance, including both customer database traffic and AWS DMS traffic used for monitoring and replication.

Units: Bytes/second

NetworkReceiveThroughput

The incoming (Receive) network traffic on the replication instance, including both customer database traffic and AWS DMS traffic used for monitoring and replication.

Units: Bytes/second

Replication Task Metrics

Replication task monitoring includes metrics for the following statistics:

FullLoadThroughputBandwidthSource

Incoming network bandwidth from a full load from the source in kilobytes (KB) per second.

FullLoadThroughputBandwidthTarget

Outgoing network bandwidth from a full load for the target in KB per second.

FullLoadThroughputRowsSource

Incoming changes from a full load from the source in rows per second.

FullLoadThroughputRowsTarget

Outgoing changes from a full load for the target in rows per second.

CDCIncomingChanges

The total number of change events at a point-in-time that are waiting to be applied to the target. Note that this is not the same as a measure of the transaction change rate of the source endpoint. A large number for this metric usually indicates AWS DMS is unable to apply captured changes in a timely manner, thus causing high target latency.

CDCChangesMemorySource

Amount of rows accumulating in a memory and waiting to be committed from the source.

CDCChangesMemoryTarget

Amount of rows accumulating in a memory and waiting to be committed to the target.

CDCChangesDiskSource

Amount of rows accumulating on disk and waiting to be committed from the source.

CDCChangesDiskTarget

Amount of rows accumulating on disk and waiting to be committed to the target.

CDCThroughputBandwidthSource

Network bandwidth for the target in KB per second. CDCThroughputBandwidth records bandwidth on sampling points. If no network traffic is found, the value is zero. Because CDC does not issue long-running transactions, network traffic may not be recorded.

CDCThroughputBandwidthTarget

Network bandwidth for the target in KB per second. CDCThroughputBandwidth records bandwidth on sampling points. If no network traffic is found, the value is zero. Because CDC does not issue long-running transactions, network traffic may not be recorded.

CDCThroughputRowsSource

Incoming task changes from the source in rows per second.

CDCThroughputRowsTarget

Outgoing task changes for the target in rows per second.

CDCLatencySource

The gap, in seconds, between the last event captured from the source endpoint and current system time stamp of the AWS DMS instance. If no changes have been captured from the source due to task scoping, AWS DMS sets this value to zero.

CDCLatencyTarget

The gap, in seconds, between the last event applied on the target and the current system timestamp of the AWS DMS instance. Target latency should never be smaller than the source latency.

Managing AWS DMS Task Logs

AWS DMS uses Amazon CloudWatch to log task information during the migration process. You can use the AWS CLI or the AWS DMS API to view information about the task logs. To do this, use the describe-replication-instance-task-logs AWS CLI command or the AWS DMS API action DescribeReplicationInstanceTaskLogs.

For example, the following AWS CLI command shows the task log metadata in JSON format.

$ aws dms describe-replication-instance-task-logs \ --replication-instance-arn arn:aws:dms:us-east-1:237565436:rep:CDSFSFSFFFSSUFCAY

A sample response from the command is as follows.

{ "ReplicationInstanceTaskLogs": [ { "ReplicationTaskArn": "arn:aws:dms:us-east-1:237565436:task:MY34U6Z4MSY52GRTIX3O4AY", "ReplicationTaskName": "mysql-to-ddb", "ReplicationInstanceTaskLogSize": 3726134 } ], "ReplicationInstanceArn": "arn:aws:dms:us-east-1:237565436:rep:CDSFSFSFFFSSUFCAY" }

In this response, there is a single task log (mysql-to-ddb) associated with the replication instance. The size of this log is 3,726,124 bytes.

You can use the information returned by describe-replication-instance-task-logs to diagnose and troubleshoot problems with task logs. For example, if you enable detailed debug logging for a task, the task log will grow quickly—potentially consuming all of the available storage on the replication instance, and causing the instance status to change to storage-full. By describing the task logs, you can determine which ones you no longer need; then you can delete them, freeing up storage space.

To delete the task logs for a task, set the task setting DeleteTaskLogs to true. For example, the following JSON deletes the task logs when modifying a task using the AWS CLI modify-replication-task command or the AWS DMS API ModifyReplicationTask action.

{ "Logging": { "DeleteTaskLogs":true } }

Logging AWS DMS API Calls Using AWS CloudTrail

The AWS CloudTrail service logs all AWS Database Migration Service (AWS DMS) API calls made by or on behalf of your AWS account. AWS CloudTrail stores this logging information in an S3 bucket. You can use the information collected by CloudTrail to monitor AWS DMS activity, such as creating or deleting a replication instance or an endpoint. For example, you can determine whether a request completed successfully and which user made the request. To learn more about CloudTrail, see the AWS CloudTrail User Guide.

If an action is taken on behalf of your AWS account using the AWS DMS console or the AWS DMS command line interface, then AWS CloudTrail logs the action as calls made to the AWS DMS API. For example, if you use the AWS DMS console to describe connections, or call the AWS CLI describe-connections command, then the AWS CloudTrail log shows a call to the AWS DMS API DescribeConnections action. For a list of the AWS DMS API actions that are logged by AWS CloudTrail, see the AWS DMS API Reference.

Configuring CloudTrail Event Logging

CloudTrail creates audit trails in each region separately and stores them in an S3 bucket. You can configure CloudTrail to use Amazon Simple Notification Service (Amazon SNS) to notify you when a log file is created, but that is optional. CloudTrail will notify you frequently, so we recommend that you use Amazon SNS with an Amazon Simple Queue Service (Amazon SQS) queue and handle notifications programmatically.

You can enable CloudTrail using the AWS Management Console, CLI, or API. When you enable CloudTrail logging, you can have the CloudTrail service create an S3 bucket for you to store your log files. For details, see Creating and Updating Your Trail in the AWS CloudTrail User Guide. The AWS CloudTrail User Guide also contains information on how to aggregate CloudTrail logs from multiple regions into a single S3 bucket.

There is no cost to use the CloudTrail service. However, standard rates for S3 usage apply, and also rates for Amazon SNS usage should you include that option. For pricing details, see the S3 and Amazon SNS pricing pages.

AWS Database Migration Service Event Entries in CloudTrail Log Files

CloudTrail log files contain event information formatted using JSON. An event record represents a single AWS API call and includes information about the requested action, the user that requested the action, the date and time of the request, and so on.

CloudTrail log files include events for all AWS API calls for your AWS account, not just calls to the AWS DMS API. However, you can read the log files and scan for calls to the AWS DMS API using the eventName element.

For more information about the different elements and values in CloudTrail log files, see CloudTrail Event Reference in the AWS CloudTrail User Guide.

You might also want to make use of one of the Amazon partner solutions that integrate with CloudTrail to read and analyze your CloudTrail log files. For options, see the AWS partners page.