--- title: Detect ingest anomalies source: https://docs.newrelic.com/docs/tutorial-optimize-telemetry/detect-anomalies --- Once you've installed the [baseline dashboard](https://docs.newrelic.com/docs/tutorial-optimize-telemetry/create-baseline-report/), you should keep an eye on it to detect any ingest anomalies as often as possible. While you have to wait until you have enough data to optimize your ingest, you can use your dashboard to find issues with your ingest much sooner. You can use the baseline dashboard as is, or download optional dashboards to give you even greater anomaly detection options. You should also set up alerts to help notify you of issues as they occur. You can use our [ingest alerts guide](https://docs.newrelic.com/docs/accounts/accounts-billing/new-relic-one-pricing-billing/usage-queries-alerts) to create a large variety of alerts, but we recommend you set up these two alerts as a minimum: - A threshold alert to notify if you exceed monthly targets for data ingest beyond seasonal increases - An anomaly alert to notify you of a sudden sharp increase ingest data > #### 💡 TIP > > New to creating alerts with our platform? Check out our [alert creation and management tutorial](https://docs.newrelic.com/docs/tutorial-create-alerts/create-new-relic-alerts/) to learn everything you need about creating New Relic alerts. ## Monitor anomalies with Lookout view [#lookout] After installing the dashboard, you can get a high-level view of your ingest patterns with the **Lookout** view. From there, you can create NRQL queries to search for any ingest anomalies. For example, the following NRQL query will give you information on all ingest anomalies by `usageMetric` over the last 24 hours: ```sql SELECT rate(sum(GigabytesIngested), 1 day) AS avgGbIngest FROM NrConsumption WHERE productLine='DataPlatform' FACET usageMetric ``` ![Lookout view usage metric](https://docs.newrelic.com/images/oma-oe-dg_screenshot-crop_lookout-view-telem-type.webp "Lookout view usage metric") You can change the facet field to anything you want to get more, or less, granularity on your ingest data. For example, changing `usageMetric` to `consumingAccountName` would give you even more detailed information by reporting on ingest by account name, as shown below: ![Lookout view consuming account](https://docs.newrelic.com/images/oma-oe-dg_screenshot-crop_lookout-view-consuming-account.webp "Lookout view consuming account") ### Install the entity breakdown dashboard (optional) [#install-entity-breakdown-dashboard] The ingest baseline dashboard that uses `NrConsumption` as its primary source. But you may find that you also want information on estimating ingest traffic for other events or metrics. If you do, you can install the entity breakdown dashboard, which helps you create other visualizations that use `bytescountestimate()` to help estimate your ingest data. To install the entity breakdown dashboard: 1. Go to the [same quickstart](https://onenr.io/0PoR8zpDYQG) you used for the baseline dashboard. 2. Select **Install this quickstart**. 3. Install the dashboard into any account that contains APM, browser monitoring, mobile monitoring, or Kubernetes clusters using the [import dashboard function](https://docs.newrelic.com/docs/query-your-data/explore-query-data/dashboards/introduction-dashboards/#dashboards-import). You can install this dashboard into multiple accounts, but avoid installing this dashboard into a partnership owner account, or POA. > #### 💡 TIP > > If you have a parent/child account structure, you can install the dashboard into a parent account and modify the dashboard so you have account-specific charts all in one dashboard. 4. Select **Done**. 5. When the quickstart finishes installing, open the **Data governance entity breakdowns** dashboard to access your data. You can refer back to [this section](https://docs.newrelic.com/docs/new-relic-solutions/observability-maturity/operational-efficiency/dg-baselining#understand-nr-consumption-metrics) to see exactly which event types are used in these breakdowns. Note that these queries consume more resources because they don't work from a pre-aggregated data source like `NrConsumption`, so you may need to adjust the time frames by using additional `WHERE` and `LIMIT` clauses to make them work better in some of your environments. ### Install the cloud integration dashboards (optional) [#install-cloud-integration-dashboards] New Relic's cloud integrations often give you a significant source of data ingest growth. But without good visualizations, it's often difficult to find where the ingest growth comes from. It's usually because these integrations aren't part of an organization's normal CI/CD pipeline or they aren't part of normal configuration management system. Fortunately, we have a set of dashboards that you can install [directly from New Relic Instant Observability](https://onenr.io/0EPwJJO9Ow7). The individual dashboards installed by this package include: - AWS integrations - Azure integrations - Google Cloud Platform integrations - On-host integrations - Kubernetes **Checking your data** Answering the following questions will help you develop confidence in your ability to interpret baseline data and make correct inferences. You can answer these questions using the data ingest baseline and data ingest entity breakdown dashboards. Install those dashboards as described and see how many of these questions you can answer. | Questions | | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | What is the typical daily ingest rate for the entire organization (all accounts) in the past week? What was it three months prior? | | What are the top three telemetry types (for the organization as a whole) by ingest? List each telemetry type and its most recent 30 day ingest rate. | | How many accounts contribute to this organization's ingest? | | How many accounts (if any) currently contribute more than 50TB per month? | | What are the top three accounts in terms of ingest for the past 30 days? | | What is the GB ingest for the calendar month of this past January for the highest consuming account? | | What are the top three accounts in terms of `ApmEventsBytes` ingest for the past 30 days | | What is the single largest increase in terms of telemetry type ingest for a given account in the last 9 months? What about decreases? | | Go to the account that contributes the most `ApmEventsBytes` and install/open the `data governance entity breakdown dashboard`. List the top three APM applications by ingest for the past 24 hours and their respective 24-hour ingest rates. | ## What's next? [#whats-next] If you've followed the tutorial so far, you have installed at least the baseline dashboard, generated a report, and have set up systems to help you detect your ingest anomalies. There's only one further step to take: using your ingest data to optimize your telemetry!