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feat(discover-split): Update Discover, Alerts, Dashboards docs (#11101)
In preparation for the dataset split in discover and dashboards, we need to update the docs to reflect this new change. The changes typically involve removing `event.type:error` or `event.type:transaction` from being mentioned in search fields because after the dataset is selected, these are redundant. It also updates screenshots and calls out the dataset selector more explicitly. Co-authored-by: Liza Mock <[email protected]>
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docs/concepts/search/searchable-properties/events.mdx

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@@ -8,8 +8,8 @@ Events are the underlying event data captured using Sentry SDKs — that is, err
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You can search by event properties in the following [sentry.io](https://sentry.io) pages:
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- Discover - in the query builder
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- Dashboards - within the widget builder, depending on dataset selection
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- Discover - in the query builder (depending on the dataset selection)
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- Dashboards - within the widget builder (depending on dataset selection)
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- Performance - only in transaction summaries
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- Issues - as indicated in the list below
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- Alerts - when creating a metric alert

docs/product/alerts/create-alerts/metric-alert-config.mdx

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- `event.type:error` OR `event.type:default`
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- `event.type:default`
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- `event.type:error`
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- `event.type:transaction`
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### Tags & Properties
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docs/product/dashboards/widget-builder/index.mdx

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## Choose Your Dataset
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In the dataset selection step, choose which type of data you would like to use in your widget. This data is classified into two different datasets: [errors and transactions](#errors--transactions) and [issues](#issues).
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In the dataset selection step, choose which type of data you would like to use in your widget. This data is classified into four different datasets: [errors](#error), [transactions](#transactions), [issues](#issues), and [releases](#releases).
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### Errors & Transactions
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### Errors
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Choosing "Errors" allows you to query and aggregate error events in the same way you would for a [Discover Query](/product/explore/discover-queries/). This data is comprised of errors that occur in your application, which Sentry will use to group into issues, for example:
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Choosing "Errors and Transactions" allows you to query and aggregate error and transaction events in the same way you would for a [Discover Query](/product/explore/discover-queries/). Some widget examples include:
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- Users most affected by errors
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### Transactions
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Choosing "Transactions" allows you to query and aggregate transaction events in the same way you would for a [Discover Query](/product/explore/discover-queries/). This data is comprised of events that track the performance of operations in your application. Some widget examples include:
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- Tracking performance of an endpoint
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- Throughput by country
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- Users most affected by errors
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### Issues
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docs/product/dashboards/widget-library/index.mdx

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To monitor how your app is performing on a certain release, you can modify the "Duration Distribution" widget by adding the release version to the search condition:
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- Search condition 1: `event.type:transaction release.version:{version}`
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- Search condition 1: `release.version:{version}`
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To compare performance with another release version, you can add another query by clicking the "Add Query" button and querying for a different release version:
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- Search condition 2: `event.type:transaction release.version:{another_version}`
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- Search condition 2: `release.version:{another_version}`
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You can also compare performance before and after a certain version with the following conditions:
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- Search condition 1: `event.type:transaction release.version:<{version}`
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- Search condition 2: `event.type:transaction release.version:>={version}`
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- Search condition 1: `release.version:<{version}`
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- Search condition 2: `release.version:>={version}`
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### Response thresholds
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To the first query, add the search condition for satisfactory transaction duration (this example uses 300ms as the satisfactory response threshold):
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- Search condition 1: `event.type:transaction transaction.duration:<300`
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- Search condition 1: `transaction.duration:<300`
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Add another query for the tolerable condition by clicking the "Add Query" button. In this example, we're using the [Apdex](/product/performance/metrics/#apdex) definition where tolerable response times are between the satisfactory threshold and four times the satisfactory threshold:
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- Search condition 2: `event.type:transaction (transaction.duration:<1200 AND transaction.duration:>=300)`
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- Search condition 2: `transaction.duration:<1200 AND transaction.duration:>=300`
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Finally, add a third query for for the frustrating transaction duration:
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- Search condition 3: `event.type:transaction transaction.duration:>=1200`
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- Search condition 3: `transaction.duration:>=1200`
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The chart now shows cumulative counts at different response time thresholds.
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docs/product/explore/discover-queries/query-builder.mdx

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2. Enter a new display name
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3. Click "Save"
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There are four main building blocks that impact the results of your saved query. You can use a combination of these to narrow down your search.
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There are five main building blocks that impact the results of your saved query, a combination of which can be used to narrow down your search:
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1. Project, environment, and date range filters
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2. Search Conditions
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3. Interactive Graph
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4. Table Columns
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1. Dataset selection
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2. Project, environment, and date range filters
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3. Search conditions
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4. Interactive graph
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5. Table columns
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## Dataset Selection
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The dataset selector allows you to query for either errors or transactions. You can only query one dataset at a time. The errors dataset returns events related to errors, while the transactions dataset returns transaction events that help you see application performance.
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## Filter by Project, Environment, and Date Range
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### Stacking Functions
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You can also add any of the following functions as columns to stack events:
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You can also add the following functions as columns to stack events, depending on the selected dataset:
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#### Errors
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- `count()`
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- `count_if(...)`
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- `count_unique(...)`
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- `eps()`
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- `epm()`
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#### Transactions
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- `any(...)`
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- `apdex(...)`
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- `avg(...)`

docs/product/explore/discover-queries/uncover-trends.mdx

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2. Select the projects, environments, and date range of errors you'd like to query.
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3. Sentry monitors different types of events for errors and performance. To query issues, filter by `event.type:error` in the search bar.
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3. Sentry monitors different types of events for errors and performance. To query issues, select the "Errors" dataset using the Dataset dropdown.
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![Filter by Error type](./img/004.png)
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Create a report looking into all the errors occurring in the URL endpoints across your applications.
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- Search condition: `event.type:error has:url`
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- Dataset: Errors
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- Search condition: `has:url`
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- Table columns: `url`, `platform.name`, `count()`
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![Errors by URL](./img/005.png)
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Whether your code is running on mobile, in browser, or on a server, an unhandled fatal error might crash your application. To find out where those crashes are happening, run the following query in **Discover**:
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- Search condition: `event.type:error handled:no level:fatal`
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- Dataset: Errors
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- Search condition: `handled:no level:fatal`
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- Table columns: `mechanism`, `platform.name`, `count()`
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![Crashes](./img/006.png)
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To find out which files in your codebase are generating the most errors, run the following query in **Discover**:
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- Search condition: `event.type:error has:stack.filename`
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- Dataset: Errors
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- Search condition: `has:stack.filename`
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- Table columns: `stack.filename`, `count()`, `count_unique(issue)`
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![By File Names](./img/010.png)
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To find out how the health of a specific project is improving (or not) over time as you release new versions, create the following query:
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- Search condition: `event.type:error`
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- Dataset: Errors
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- Table columns: `release`, `count()`, `count_unique(issue)`
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![Issues per release](./img/012.png)

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