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You can use Datastream to monitor data and events that are processed by a stream. This information appears in the following graphs:
Throughput: The rate at which Datastream processes data or events. This rate can be:
The amount of data (in MB) that Datastream transfers from the source to the destination.
The number of events that are associated with the data being transferred. Aneventis a single change in the source, such as a new row added to a table
in a database.
Unsupported events: The number of events that can't be processed from the source to the destination.
Data freshness: The time difference between the data residing in the source and the data being transferred into the destination by the stream. It is
calculated as the time elapsed between the source timestamp and the read timestamp for theoldestevent being processed. If there are no new events to read from the source, the freshness is set to 0.
If there are enqueued events that Datastream hasn't processed yet, they aren't taken into account when Datastream calculates the data freshness metric. For example, if there is a spike in throughput, it is reflected in the freshness metric only after Datastream processes the events causing the spike.
System latency: The time that Datastream takes to process an event. This interval is calculated as the time between when Datastream reads
the event and when the event is written to the destination.
Total latency: The time difference between when data is written to the source and the corresponding events are written to the destination.
Optional. Scroll until theData freshnessgraph appears. For this graph,
click theCreate alerting policylink to create an alerting policy for
it. An alerting policy describes a set of conditions that you want to
monitor for the graph.
After clicking the link, theCreate alerting policypage appears in
Cloud Monitoring. On this page, you can define the alerting policy for
the graph. This includes specifying which criteria will trigger the policy,
who'll be notified if the criteria are met, and how they'll be notified.
Scroll until the graph appears that represents the data or events that Datastream is monitoring.
Optionally, if you're looking at theThroughputgraph, then select(bytes/sec)to see the amount of data that Datastream transfers from the source to the destination, or(event/sec)to see how many events are associated with the data being transferred.
To view how much data or how many events Datastream processed over a period of hours or days, click1 hour,6 hours,12 hours,1 day,2 days,4 days,7 days,14 days, or30 days.
Or, to set a custom range, select theCustommenu, and then use theCalendarpicker to specify a start date and time and end date and time for the amount of data or the number of events that you want to view.
Datastream updates the graph in the pane to reflect your selection and displays the interval that you specified.
For example, if today is October 31, 2021, and you click30 days, the graph will show the amount of data or the number of events Datastream processed since October 01, 2021.
Hold the pointer over the line in the graph to display how much data or how many events Datastream processed for a particular date and time.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-09-04 UTC."],[[["\u003cp\u003eDatastream allows monitoring of data and events through various graphs, including Throughput, Unsupported events, Data freshness, System latency, and Total latency.\u003c/p\u003e\n"],["\u003cp\u003eThroughput measures the rate of data or event processing, displayed in either the amount of data transferred (MB) or the number of events associated with the transfer.\u003c/p\u003e\n"],["\u003cp\u003eData freshness indicates the time difference between data residing in the source and the data being transferred to the destination, calculated based on the oldest event.\u003c/p\u003e\n"],["\u003cp\u003eSystem latency represents the time Datastream takes to process an event, from the time it's read to when it's written to the destination.\u003c/p\u003e\n"],["\u003cp\u003eMonitoring can be done on the Google Cloud Console by navigating to the 'Streams' page and selecting a specific stream to view the relevant graphs, which can also have alerting policies configured for data freshness.\u003c/p\u003e\n"]]],[],null,["# Monitor a stream\n\nYou can use Datastream to monitor data and events that are processed by a stream. This information appears in the following graphs:\n\n- Throughput: The rate at which Datastream processes data or events. This rate can be:\n\n - The amount of data (in MB) that Datastream transfers from the source to the destination.\n - The number of events that are associated with the data being transferred. An **event** is a single change in the source, such as a new row added to a table\n in a database.\n\n | You can also monitor any errors associated with a stream. See [Troubleshoot a stream](/datastream/docs/troubleshoot-a-stream).\n- Unsupported events: The number of events that can't be processed from the source to the destination.\n\n- Data freshness: The time difference between the data residing in the source and the data being transferred into the destination by the stream. It is\n calculated as the time elapsed between the source timestamp and the read timestamp for the *oldest* event being processed. If there are no new events to read from the source, the freshness is set to 0.\n\n If there are enqueued events that Datastream hasn't processed yet, they aren't taken into account when Datastream calculates the data freshness metric. For example, if there is a spike in throughput, it is reflected in the freshness metric only after Datastream processes the events causing the spike.\n- System latency: The time that Datastream takes to process an event. This interval is calculated as the time between when Datastream reads\n the event and when the event is written to the destination.\n\n- Total latency: The time difference between when data is written to the source and the corresponding events are written to the destination.\n\nMonitor data or events processed\n--------------------------------\n\n1. Go to the **Streams** page in the Google Cloud Console.\n\n [Go to the Streams page](https://console.cloud.google.com/datastream/streams)\n2. Click the stream that you want to monitor.\n\n3. Optional. Scroll until the **Data freshness** graph appears. For this graph,\n click the **Create alerting policy** link to create an alerting policy for\n it. An alerting policy describes a set of conditions that you want to\n monitor for the graph.\n\n After clicking the link, the **Create alerting policy** page appears in\n Cloud Monitoring. On this page, you can define the alerting policy for\n the graph. This includes specifying which criteria will trigger the policy,\n who'll be notified if the criteria are met, and how they'll be notified.\n\n For more information about alerting policies, including how to create them,\n see [Managing metric-based alerting\n policies](/monitoring/alerts/using-alerting-ui).\n4. Click the **MONITORING** tab.\n\n5. Scroll until the graph appears that represents the data or events that Datastream is monitoring.\n\n6. Optionally, if you're looking at the **Throughput** graph, then select **(bytes/sec)** to see the amount of data that Datastream transfers from the source to the destination, or **(event/sec)** to see how many events are associated with the data being transferred.\n\n7. To view how much data or how many events Datastream processed over a period of hours or days, click **1 hour** , **6 hours** , **12 hours** , **1 day** , **2 days** , **4 days** , **7 days** , **14 days** , or **30 days**.\n\n Or, to set a custom range, select the **Custom** menu, and then use the **Calendar** picker to specify a start date and time and end date and time for the amount of data or the number of events that you want to view.\n\n Datastream updates the graph in the pane to reflect your selection and displays the interval that you specified.\n\n For example, if today is October 31, 2021, and you click **30 days**, the graph will show the amount of data or the number of events Datastream processed since October 01, 2021.\n8. Hold the pointer over the line in the graph to display how much data or how many events Datastream processed for a particular date and time.\n\n | **Tip:** Drag your mouse to connect two points on the line in the graph to see how much data or how many events Datastream processed over a more-granular time interval. \n |\n | For example, if today is October 31, 2021, and you click 30 days, then the graph shows how much data Datastream transferred or the number of events associated with the data being transferred since October 01, 2021. \n |\n | If you click where the line begins at October 01, and drag your mouse until it touches where the line crosses October 05, then the line in the graph will be updated to reflect the interval that you specified (for this example, how much data or how many events Datastream processed from October 01 to October 05).\n\nWhat's next\n-----------\n\n- To learn more about streams, see [Stream lifecycle](/datastream/docs/stream-states-and-actions).\n- To learn how to view information about your stream, see [View a stream](/datastream/docs/view-a-stream).\n- To learn how to modify a stream, see [Modify a stream](/datastream/docs/modify-a-stream)."]]