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docs: add page for Kestra integration #1917
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eba1318
docs: Add page for kestra integration.
ammeek 8c99c25
docs: Fix grammar and spelling mistakes for Kestra integration docs.
ammeek b1992c0
Merge branch 'master' into docs/kestra
ammeek 495bce1
docs: Add link to Kestra KV store.
ammeek d684d00
Merge branch 'master' into docs/kestra
ammeek 2460107
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ammeek 3e262b8
docs: update the id of the Kestra flow example to reflect the actual …
ammeek f019226
docs: add reference to Kestra on the Integrate with Apify page.
ammeek 80e6c1a
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ammeek b1e58ba
docs: remove redundant sentence in Kestra docs.
ammeek 1f79f68
docs: remove references to real time as no trigger task has been added.
ammeek 9f3a9a6
docs: replace references to json syntax to yaml.
ammeek 86066dc
docs: remove misleading statements about flow setup.
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90 changes: 90 additions & 0 deletions
90
sources/platform/integrations/workflows-and-notifications/kestra.md
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,90 @@ | ||
| --- | ||
| title: Kestra integration | ||
| description: Connect Apify with Kestra to orchestrate workflows — run flows, extract structured data, and react to Actor or task events. | ||
| sidebar_label: Kestra | ||
| sidebar_position: 7 | ||
| slug: /integrations/kestra | ||
| --- | ||
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| **Connect Apify with Kestra to orchestrate workflows — run flows, extract structured data, and react to Actor or task events.** | ||
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| --- | ||
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| [Kestra](https://kestra.io/) is an open-source, event-driven orchestration platform. The [Apify plugin for Kestra](https://github.com/kestra-io/plugin-kestra) connects Apify Actors and storage to your workflows. Run scrapers, extract structured data — all defined declaratively in YAML and orchestrated directly from the UI. | ||
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| This guide shows you how to set up the integration, configure authentication, and create a workflow that runs an Actor and processes its results. | ||
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| ## Prerequisites | ||
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| Before you begin, make sure you have: | ||
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| - An [Apify account](https://console.apify.com/) | ||
| - A [Kestra instance](https://kestra.io/docs/getting-started/quickstart) (self‑hosted or cloud) | ||
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| ## Authentication | ||
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| The Apify plugin uses API key authentication. Store your API key in [Kestra Secrets](https://kestra.io/docs/concepts/secret) through the UI or environment variables. In the open-source version, manage Secrets using base64-encoded environment variables. You can also use [Kestra's KV Store](https://kestra.io/docs/concepts/kv-store) to persist API keys across executions and workflows. | ||
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| To add your Apify API token, go to the Secrets section in the Kestra UI and create a new secret with the key `APIFY_API_KEY` and your token as the value. | ||
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| ## Use Apify Tasks as an action | ||
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| Tasks allow you to perform operations like running an Actor within a workflow. | ||
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| 1. Create a new flow. | ||
| 1. Inside the **Flow code** tab change the hello task's type to be **io.kestra.plugin.apify.actor.Run**. | ||
| 1. Change the task's id to be **run_apify_actor** | ||
| 1. Remove the message property. | ||
| 1. Configure the **run_apify_actor** task by adding your required values for the properties listed below: | ||
| - **actorId**: Actor ID or a tilde-separated owner's username and Actor name. | ||
| - **apiToken**: A reference to the secret value you set up earlier. For example "\{\{secret(namespace=flow.namespace, key='APIFY_API_KEY')\}\}" | ||
| 1. Add a new task below the **run_apify_actor** with an ID of **get_dataset** and a type of **io.kestra.plugin.apify.dataset.Get**.: | ||
| 1. Configure the **get_dataset** to fetch the dataset generated by the **run_apify_actor** task by configuring the following values: | ||
| - **datasetId**: The ID of the dataset to fetch. You can use the value from the previous task using the following syntax: "\{\{secret(namespace=flow.namespace, key='APIFY_API_KEY')\}\}" | ||
| - **input**: Input for the Actor run. The input is optional and can be used to pass data to the Actor. For our example we will add 'hashtags: ["fyp"]' | ||
| - **maxItems**: The maximum number of items to fetch from the dataset. For our example we will set this to 5. | ||
| 1. Now add the final task to log the output of the dataset. Add a new task below the **log_output** with an ID of **log_output** and a type of **io.kestra.plugin.core.log.Log**. | ||
| 1. Configure the **log_output** task to log the output of the dataset by configuring the following values: | ||
| - **message**: The message to log. You can use the value from the previous task using the following syntax: '\{\{outputs.get_dataset.dataset\}\}' | ||
| 1. Now save and run your flow. | ||
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| Your completed template should match the template below. | ||
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| ```yaml | ||
| id: run_actor_and_fetch_dataset | ||
| namespace: company.team | ||
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| tasks: | ||
| - id: run_actor | ||
| type: io.kestra.plugin.apify.actor.Run | ||
| actorId: GdWCkxBtKWOsKjdch | ||
| maxItems: 5 | ||
| input: | ||
| hashtags: ["fyp"] | ||
| apiToken: "{{secret(namespace=flow.namespace, key='APIFY_API_KEY')}}" | ||
| - id: log_get_last_run_results | ||
| type: io.kestra.plugin.core.log.Log | ||
| message: '{{outputs.run_actor}}' | ||
| - id: get_data_set_raw | ||
| type: io.kestra.plugin.apify.dataset.Get | ||
| datasetId: '{{outputs.run_actor.defaultDatasetId}}' | ||
| apiToken: "{{secret(namespace=flow.namespace, key='APIFY_API_KEY')}}" | ||
| - id: log_get_data_set_raw_results | ||
| type: io.kestra.plugin.core.log.Log | ||
| message: '{{outputs.get_data_set_raw}}' | ||
| ``` | ||
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| ## Resources | ||
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| - [Kestra Apify Plugin](https://kestra.io/plugins/plugin-apify) | ||
| - [Apify API Documentation](https://docs.apify.com) | ||
| - [Kestra Documentation](https://kestra.io/docs) | ||
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| ## Troubleshooting | ||
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| If you encounter issues, start by double-checking basics. | ||
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| - **Authentication errors**: Verify your API token in [Secrets](https://kestra.io/docs/concepts/secret). | ||
| - **Operation failures**: Check input parameters, YAML syntax, and resource IDs in your Apify account. | ||
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| Feel free to explore other resources and contribute to the integration on [GitHub](https://github.com/kestra-io/plugin-apify). | ||
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Bug: YAML Configuration Errors in Kestra Guide
The example YAML in the Kestra integration guide has a few issues. The
maxItemsproperty is incorrectly placed under theactor.Runtask, where it will likely be ignored or cause errors, as it's intended for dataset fetching operations. Additionally, theapiTokenproperty is redundantly specified for both tasks, which could lead to confusion.