PagerDuty is an incident management platform that alerts teams to issues, automates workflows, and ensures rapid resolution, enhancing system reliability and minimizing downtime.
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This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.
This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.
Set up a source connector to extract data from in Airbyte
Choose from one of 400 sources where you want to import data from. This can be any API tool, cloud data warehouse, database, data lake, files, among other source types. You can even build your own source connector in minutes with our no-code no-code connector builder.
Configure the connection in Airbyte
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The only open solution empowering data teams to meet growing business demands in the new AI era.
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Ship more quickly with the only solution that fits ALL your needs.
As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Ship more quickly with the only solution that fits ALL your needs.
As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Move large volumes, fast.
Change Data Capture.
Security from source to destination.
We support the CDC methods your company needs
Log-based CDC
Timestamp-based CDC
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Keep your data engineering costs in check
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- Airbyte Cloud: Have it hosted by us, with all the security you need (SOC2, ISO, GDPR, HIPAA Conduit).
- Airbyte Enterprise: Have it hosted within your own infrastructure, so your data and secrets never leave it.
White-glove enterprise-level support
Including for your Airbyte Open Source instance with our premium support.
Airbyte supports a growing list of destinations, including cloud data warehouses, lakes, and databases.
Airbyte supports a growing list of destinations, including cloud data warehouses, lakes, and databases.
Airbyte supports a growing list of sources, including API tools, cloud data warehouses, lakes, databases, and files, or even custom sources you can build.
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FAQs
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.
PagerDuty is transforming mission-critical tasks for modern businesses. PagerDuty is the central nervous system for a company's digital operations. Our powerful and unique platform ensures that you can take the right action when seconds matter. From developers and reliability engineers to customer success, security, and the C-suite, we empower teams with the time and expertise to create the future. From more uptime to more free time, PagerDuty delivers clear value for any organization.
PagerDuty's API provides access to a wide range of data related to incident management and response. The following are the categories of data that can be accessed through PagerDuty's API:
1. Incidents: Information related to incidents such as incident ID, status, priority, and severity.
2. Services: Details about the services that are being monitored, including service name, description, and escalation policies.
3. Users: Information about the users who are part of the PagerDuty account, including their contact details and notification preferences.
4. Escalation policies: Details about the escalation policies that are in place for each service, including the order in which responders are notified.
5. Schedules: Information about the schedules that are in place for each service, including the on-call rotation and the time zone.
6. Alerts: Details about the alerts that are generated by the monitoring tools, including the source of the alert and the time it was triggered.
7. Analytics: Metrics related to incident response, including the number of incidents, response times, and resolution times.
Overall, PagerDuty's API provides a comprehensive set of data that can be used to monitor and manage incidents effectively.
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.
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.
PagerDuty is transforming mission-critical tasks for modern businesses. PagerDuty is the central nervous system for a company's digital operations. Our powerful and unique platform ensures that you can take the right action when seconds matter. From developers and reliability engineers to customer success, security, and the C-suite, we empower teams with the time and expertise to create the future. From more uptime to more free time, PagerDuty delivers clear value for any organization.
PagerDuty's API provides access to a wide range of data related to incident management and response. The following are the categories of data that can be accessed through PagerDuty's API:
1. Incidents: Information related to incidents such as incident ID, status, priority, and severity.
2. Services: Details about the services that are being monitored, including service name, description, and escalation policies.
3. Users: Information about the users who are part of the PagerDuty account, including their contact details and notification preferences.
4. Escalation policies: Details about the escalation policies that are in place for each service, including the order in which responders are notified.
5. Schedules: Information about the schedules that are in place for each service, including the on-call rotation and the time zone.
6. Alerts: Details about the alerts that are generated by the monitoring tools, including the source of the alert and the time it was triggered.
7. Analytics: Metrics related to incident response, including the number of incidents, response times, and resolution times.
Overall, PagerDuty's API provides a comprehensive set of data that can be used to monitor and manage incidents effectively.
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.
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.
PagerDuty is transforming mission-critical tasks for modern businesses. PagerDuty is the central nervous system for a company's digital operations. Our powerful and unique platform ensures that you can take the right action when seconds matter. From developers and reliability engineers to customer success, security, and the C-suite, we empower teams with the time and expertise to create the future. From more uptime to more free time, PagerDuty delivers clear value for any organization.
PagerDuty's API provides access to a wide range of data related to incident management and response. The following are the categories of data that can be accessed through PagerDuty's API:
1. Incidents: Information related to incidents such as incident ID, status, priority, and severity.
2. Services: Details about the services that are being monitored, including service name, description, and escalation policies.
3. Users: Information about the users who are part of the PagerDuty account, including their contact details and notification preferences.
4. Escalation policies: Details about the escalation policies that are in place for each service, including the order in which responders are notified.
5. Schedules: Information about the schedules that are in place for each service, including the on-call rotation and the time zone.
6. Alerts: Details about the alerts that are generated by the monitoring tools, including the source of the alert and the time it was triggered.
7. Analytics: Metrics related to incident response, including the number of incidents, response times, and resolution times.
Overall, PagerDuty's API provides a comprehensive set of data that can be used to monitor and manage incidents effectively.
1. Begin by navigating to the Airbyte dashboard and selecting the "Sources" tab.
2. Click on the "Add Source" button and select "PagerDuty" from the list of available connectors.
3. Enter a name for your PagerDuty source and click "Next".
4. In the "Authentication" section, enter your PagerDuty API key and subdomain.
5. Click "Test Connection" to ensure that the credentials are correct and the connection is successful.
6. In the "Configure Schema" section, select the data you want to replicate from PagerDuty.
7. Click "Create Source" to save your configuration and begin syncing data from PagerDuty to your destination.
8. You can monitor the status of your source connector on the Airbyte dashboard and make any necessary changes to your configuration as needed.
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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