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Sentry

Sentry

Engineering Analytics

Sync Sentry data anywhere.

Sentry is a cloud-based error monitoring platform that helps developers identify and fix issues in their applications. It provides real-time alerts and detailed error reports, allowing developers to quickly diagnose and resolve issues before they impact users. Sentry supports a wide range of programming languages and frameworks, and integrates with popular development tools like GitHub, Jira, and Slack. With features like release tracking, performance monitoring, and customizable dashboards, Sentry helps teams improve the quality and reliability of their software. Overall, Sentry is a powerful tool for any development team looking to streamline their error monitoring and debugging processes.

  • Certified
  • Generally available
  • 6 streams
  • 5 entities
Sync Sentry dataRead the docs
  • 6Streams
  • 5Entities
  • 4Actions
  • 50+Destinations
One connector

Everything Sentry can do in Airbyte

  • Sync to your warehouse

    Land 6 Sentry tables in 50+ destinations on a schedule you control.

  • Context store search

    Query synced Sentry data with filters, sorting and semantic search, without spending Sentry API rate limits.

  • Incremental syncs

    Pull only the records that changed since the last run instead of reloading everything.

  • One authorization

    Authenticate Sentry once. The same connection powers scheduled syncs and runtime actions.

Sync capabilities

  • Full Refresh SyncSupported
  • Incremental SyncSupported
  • Available onCloud, Self-Managed Enterprise
  • Destinations50+ Airbyte connectors
  • Connector version1.0.7

Set up in 9 steps

  1. First, navigate to the Airbyte dashboard and click on the "Sources" tab on the left-hand side of the screen.
  2. Click on the "Create New Source" button and select "Sentry" from the list of available connectors.
  3. Enter a name for your Sentry source connector and click on the "Next" button.
  4. Enter your Sentry API credentials, including your Sentry API key and organization slug.
  5. Click on the "Test" button to ensure that your credentials are valid and that Airbyte can connect to your Sentry account.
  6. Once your credentials have been verified, select the projects that you want to replicate data from and click on the "Next" button.
  7. Choose the data that you want to replicate from Sentry, including issues, events, and releases.
  8. Configure any additional settings, such as the frequency of data replication and any filters that you want to apply to your data.
  9. Click on the "Create Source" button to save your Sentry source connector and begin replicating data from your Sentry account to Airbyte.
6 streams

Every table you can sync from Sentry

  • Events

  • Issues

  • Projects

  • Project Detail

  • All Projects Detail

  • Releases

4 actions

Supported Sentry actions

  • List

    Read live records straight from the Sentry API.

  • Get

    Fetch a single record by ID.

  • Context Store Search

    Query synced data with filters and sorting, with no API rate limits.

  • Semantic Search

    Natural-language search across synced Sentry records.

Full parameter-level details live in the Sentry entity reference.

Authentication

Authenticate Sentry once

  • Authentication Tokens

    Log into Sentry and then create authentication tokens.For self-hosted, you can find or create authentication tokens by visiting "{instance_url_prefix}/settings/account/api/auth-tokens/"

Use cases

What teams build with Sentry

  • List all projects in my Sentry organization

  • Show me the issues for a specific project

  • List recent events from a project

  • Show me all releases for my organization

  • Get the details of a specific project

  • What are the most common unresolved issues?

FAQ

Common questions

Do I need more than one Sentry connection?

No. One Sentry authorization powers both the scheduled syncs that land data in your destination and the entity actions your agents call at runtime.

Do Sentry entity actions need a sync to run first?

No. Entity actions read and write through the Sentry API as they are called, so they work immediately. Context store search is the exception: it queries data Airbyte has already synced, which is what lets it filter and sort without spending API rate limits.

What is ETL?

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

What data can you extract from Sentry?

Sentry's API provides access to a wide range of data related to application performance monitoring and error tracking. The following are the categories of data that can be accessed through Sentry's API:
1. Events: This includes information about errors, crashes, and other events that occur within an application.
2. Issues: This includes details about specific issues that have been identified within an application, including the number of occurrences, the severity of the issue, and any associated metadata.
3. Projects: This includes information about the projects being monitored by Sentry, including project settings, integrations, and other configuration details.
4. Users: This includes information about the users who are interacting with an application, including their IP addresses, browser information, and other relevant data.
5. Releases: This includes information about the releases of an application, including version numbers, release dates, and associated metadata.
6. Performance: This includes data related to the performance of an application, including response times, error rates, and other metrics.

Overall, Sentry's API provides a comprehensive set of data that can be used to monitor and optimize the performance of an application, as well as to identify and resolve errors and other issues.

How do I transfer data from Sentry?

1. First, navigate to the Airbyte dashboard and click on the "Sources" tab on the left-hand side of the screen.
2. Click on the "Create New Source" button and select "Sentry" from the list of available connectors.
3. Enter a name for your Sentry source connector and click on the "Next" button.
4. Enter your Sentry API credentials, including your Sentry API key and organization slug.
5. Click on the "Test" button to ensure that your credentials are valid and that Airbyte can connect to your Sentry account.
6. Once your credentials have been verified, select the projects that you want to replicate data from and click on the "Next" button.
7. Choose the data that you want to replicate from Sentry, including issues, events, and releases.
8. Configure any additional settings, such as the frequency of data replication and any filters that you want to apply to your data.
9. Click on the "Create Source" button to save your Sentry source connector and begin replicating data from your Sentry account to Airbyte.

What are top ETL tools to transfer data from Sentry?

The most prominent ETL tools to transfer data to include: Airbyte, Fivetran, StitchData, Matillion, Talend Data Integration. These tools help in extracting data from various sources (APIs, databases, and more), transforming it efficiently, and loading it into and other databases, data warehouses and data lakes, enhancing data management capabilities.

What is ELT?

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

Difference between ETL and ELT?

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

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