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title: 'Plan the scale of your Azure Time Series Insights environment | Microsoft Docs'
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description: This article describes how to follow best practices when planning an Azure Time Series Insights environment, including storage capacity, data retention, ingress capacity, monitoring, and business disaster recovery (BCDR).
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description: This article describes how to follow best practices when you plan an Azure Time Series Insights environment. Areas that are covered include storage capacity, data retention, ingress capacity, monitoring, and business continuity and disaster recovery (BCDR).
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services: time-series-insights
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ms.service: time-series-insights
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author: ashannon7
@@ -20,101 +20,110 @@ This article describes how to plan your Azure Time Series Insights general avail
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## Video
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### Learn more about data retention in AzureTime Series Insights and how to plan for it.</br>
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**Watch this video to learn more about data retention in Azure Time Series Insights and how to plan for it**:<br /><br />
To get started with Time Series Insights, it’s best if you know how much data you expect to push by the minute as well as how long you need to store your data.
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To get started with Time Series Insights, it’s best if you know how much data you expect to push by the minute and how long you need to store your data.
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For more information about capacity and retention for both Time Series Insights SKUs, see [Time Series Insights pricing](https://azure.microsoft.com/pricing/details/time-series-insights/).
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Consider the following attributes to best plan the environment for long-term success:
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To best plan your Time Series Insights environment for long-term success, consider the following attributes:
- <ahref="#shape-your-events">Shaping your events</a>
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- <ahref="#ensure-you-have-reference-data">Ensuring you have reference data in place</a>
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- <ahref="#ensure-that-you-have-reference-data">Ensuring that you have reference data in place</a>
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## Understand storage capacity
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## Storage capacity
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By default, Azure Time Series Insights retains data based on the amount of storage you have provisioned (units times amount of storage per unit) and ingress.
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By default, Time Series Insights retains data based on the amount of storage you provision (units × the amount of storage per unit) and ingress.
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## Understand data retention
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## Data retention
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You can configure your Time Series Insights environment’s **Data retention time** setting, enabling up to 400 days of retention. Time Series Insights has two modes, one that optimizes for ensuring your environment has the most up-to-date data (on by default), and another that optimizes for ensuring retention limits are met, where ingress is paused if the overall storage capacity of the environment is hit. You can adjust retention and toggle between the two modes in the environment’s configuration page in the Azure portal.
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You can change the **Data retention time** setting in your Time Series Insights environment. You can enable up to 400 days of retention.
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Time Series Insights has two modes. One mode optimizes for ensuring that your environment has the most up-to-date data. This mode is on, by default.
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The other mode optimizes for ensuring that retention limits are met. In the second mode, ingress is paused if the overall storage capacity of the environment is met.
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You can adjust retention and toggle between the two modes on the environment’s configuration page in the Azure portal.
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You can configure a maximum of 400 days of data retention in your Time Series Insights environment.
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### Configure data retention
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1. In the [Azure portal](https://portal.azure.com), select your Time Series Insights environment.
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1.On the **Time Series Insights environment page**, under the **Settings** heading, select **Configure**.
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1.In the **Time Series Insights environment** pane, under **Settings**, select **Configure**.
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1. In the **Data retention time (in days)** box, enter a value from 1 to 400.
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1. In the **Data retention time (in days)** box, enter a value between 1 and 400.
> Learn more about implementing an appropriate data retention policy by reviewing[How to configure retention](./time-series-insights-how-to-configure-retention.md).
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> To learn more about how to implement an appropriate data retention policy, see[How to configure retention](./time-series-insights-how-to-configure-retention.md).
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## Understand ingress capacity
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## Ingress capacity
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The other area to focus on for planning is ingress capacity, which is a derivative of the per-minute allocation.
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The second area to focus on for planning your Time Series Insights environment is ingress capacity. Ingress capacity is a derivative of the per-minute allocation.
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From a throttling perspective, an ingressed data packet with a packet size of 32 KB is treated as 32 events, each sized 1 KB. The maximum allowed event size is 32 KB; data packets larger than 32 KB are truncated.
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From a throttling perspective, an ingressed data packet that has a packet size of 32 KB is treated as 32 events, each 1 KB in size. The maximum allowed event size is 32 KB. Data packets larger than 32 KB are truncated.
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The following table summarizes the ingress capacity for each SKU:
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The following table summarizes the ingress capacity per unit for each Time Series Insights SKU:
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|SKU |Events Count / Month / Unit |Events size / Month / Unit |Events Count / Minute / Unit | Size / Minute / Unit |
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|SKU |Event count per month |Event size per month |Event count per minute |Event size per minute|
You can increase the capacity of an S1 or S2 SKU to 10 units in a single environment. You cannot migrate from an S1 environment to an S2, or from an S2 environment to an S1.
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You can increase the capacity of an S1 or S2 SKU to 10 units in a single environment. You can't migrate from an S1 environment to an S2. You can't migrate from an S2 environment to an S1.
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For ingress capacity, you should first determine the total ingress you require on a per-month basis. Next, determine what your per-minute needs are, as this is where throttling and latency play a role.
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For ingress capacity, first determine the total ingress you require on a per-month basis. Next, determine what your per-minute needs are.
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If you have a spike in your data ingress lasting less than 24 hours, Time Series Insights can "catch-up" at an ingress rate of 2x the listed rates above.
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Throttling and latency play a role in per-minute capacity. If you have a spike in your data ingress that lasts less than 24 hours, Time Series Insights can "catchup" at an ingress rate of two times the rates listed in the preceding table.
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For example, if you have a single S1 SKU and ingress data at a rate of 720 events per minute, and spike for less than 1 hour at a rate of 1440 events or less, there would be no noticeable latency to your environment. However, if you exceed 1440 events per minute for more than one hour, you would likely experience latency to data that is visualized and available for query in your environment.
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For example, if you have a single S1 SKU, you ingress data at a rate of 720 events per minute, and the data rate spikes for less than one hour at a rate of 1,440 events or less, there's no noticeable latency in your environment. However, if you exceed 1,440 events per minute for more than one hour, you likely will experience latency in data that is visualized and available for query in your environment.
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You may not know in advance how much data you expect to push. In this case, you can find data telemetry for [Azure IoT Hub](https://docs.microsoft.com/azure/iot-hub/iot-hub-metrics) and [Azure Event Hubs](https://blogs.msdn.microsoft.com/cloud_solution_architect/2016/05/25/using-the-azure-rest-apis-to-retrieve-event-hub-metrics/) in your Azure portal. This telemetry can help you determine how to provision your environment. Use the **Metrics**page in the Azure portal for the respective event source to view its telemetry. If you understand your event source metrics, you can more effectively plan and provision your Time Series Insights environment.
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You might not know in advance how much data you expect to push. In this case, you can find data telemetry for [Azure IoT Hub](https://docs.microsoft.com/azure/iot-hub/iot-hub-metrics) and [Azure Event Hubs](https://blogs.msdn.microsoft.com/cloud_solution_architect/2016/05/25/using-the-azure-rest-apis-to-retrieve-event-hub-metrics/) in your Azure portal subscription. The telemetry can help you determine how to provision your environment. Use the **Metrics**pane in the Azure portal for the respective event source to view its telemetry. If you understand your event source metrics, you can more effectively plan and provision your Time Series Insights environment.
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### Calculate ingress requirements
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- Confirm your ingress capacity is above your average per-minute rate and that your environment is large enough to handle your anticipated ingress equivalent to 2x your capacity for less than 1 hour.
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To calculate your ingress requirements:
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- Verify that your ingress capacity is above your average per-minute rate and that your environment is large enough to handle your anticipated ingress equivalent to two times your capacity for less than one hour.
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- If ingress spikes occur that last for longer than 1 hour, use the spike rate as your average, and provision an environment with the capacity to handle the spike rate.
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- If ingress spikes occur that last for longer than 1 hour, use the spike rate as your average. Provision an environment with the capacity to handle the spike rate.
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### Mitigate throttling and latency
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For information about how to prevent throttling and latency, read about how to[Mitigate latency and throttling](time-series-insights-environment-mitigate-latency.md).
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For information about how to prevent throttling and latency, see[Mitigate latency and throttling](time-series-insights-environment-mitigate-latency.md).
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## Shape your events
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It's important to ensure the way you send events to TSI supports the size of the environment you are provisioning (conversely, you can map the size of the environment to how many events TSI reads and the size of each event). Likewise, it's important to think about the attributes you may want to slice and filter by when querying your data.
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It's important to ensure that the way you send events to Time Series Insights supports the size of the environment you are provisioning. (Conversely, you can map the size of the environment to how many events Time Series Insights reads and the size of each event.) It's also important to think about the attributes that you might want to use to slice and filter by when you query your data.
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> [!TIP]
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> Review the JSON shaping documentation in [Sending events](https://docs.microsoft.com/azure/time-series-insights/time-series-insights-send-events).
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## Ensure you have reference data
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## Ensure that you have reference data
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A **Reference Data Set** is a collection of items that augment the events from your event source. Time Series Insights ingress engine joins each event from your event source with the corresponding data row in your reference data set. This augmented event is then available for query. This join is based on the Primary Key column(s) defined in your reference data set.
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A *reference dataset* is a collection of items that augment the events from your event source. The Time Series Insights ingress engine joins each event from your event source with the corresponding data row in your reference dataset. The augmented event is then available for query. The join is based on the **Primary Key** columns that are defined in your reference dataset.
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Note, reference data is not joined retroactively. This means that only current and future ingress data is matched and joined to the reference date set, once it has been configured and uploaded. If you plan to send lots of historical data to TSI and don't upload or create reference data in TSI first, then you may have to re-do your work (hint, not fun).
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> [!NOTE]
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> Reference data isn't joined retroactively. Only current and future ingress data is matched and joined to the reference dataset after it's configured and uploaded. If you plan to send a large amount of historical data to Time Series Insights and don't first upload or create reference data in Time Series Insights, you might have to redo your work (hint: not fun).
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To learn more about how to create, upload, and manage your reference data in TSI, head to our [Reference data set documentation](https://docs.microsoft.com/azure/time-series-insights/time-series-insights-add-reference-data-set).
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To learn more about how to create, upload, and manage your reference data in Time Series Insights, see our [Reference dataset documentation](https://docs.microsoft.com/azure/time-series-insights/time-series-insights-add-reference-data-set).
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