Connect payload and Elasticsearch to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for payload
Choose an Action
Automatically do this!
Create Document
Create Document ( without selecting index)
Bulk Add Documents to an index
Delete Index
Create Index
Search (Fuzzy search)
Update Document
Bulk update documents
Bulk delete documents
Bulk Add Documents With Document Id
Enable Integrations or automations with these events of payload and Elasticsearch
Enable Integrations or automations with these events of payload and Elasticsearch
Actions
Create Document
create a doc
Create Document ( without selecting index)
index name is inside the document
Bulk Add Documents to an index
add many documents in one go
Delete Index
delete an index
Create Index
create an index
Search (Fuzzy search)
fuzzy search
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- InstagramInstagram CaptionGenerate ImagePublish Photo with TaggingAdd Step
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- has responseSendDMMessageAdd Step
- Notify teamSendMailAdd Step
- has reactSendDMMessage ReactAdd Step
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Frequently Asked Questions
To start, connect both your payload and Elasticsearch accounts to viaSocket. Once connected, you can set up a workflow where an event in payload triggers actions in Elasticsearch (or vice versa).
Absolutely. You can customize how payload data is recorded in Elasticsearch. This includes choosing which data fields go into which fields of Elasticsearch, setting up custom formats, and filtering out unwanted information.
The data sync between payload and Elasticsearch typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between payload and Elasticsearch. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About Elasticsearch
Elasticsearch is a powerful, open-source search and analytics engine built on Apache Lucene. It is designed for horizontal scalability, real-time search, and support for multi-tenant environments.
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