Elasticsearch and HTTP Request integration

Save yourself the work of writing custom integrations for Elasticsearch and HTTP Request and use n8n instead. Build adaptable and scalable Development, Data & Storage, and Core Nodes workflows that work with your technology stack. All within a building experience you will love.

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How to connect Elasticsearch and HTTP Request

Step 1: Create a new workflow
Step 2: Add and configure nodes
Step 3: Connect
Step 4: Customize and extend your integration
Step 5: Test and activate your workflow

Step 1: Create a new workflow and add the first step

In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.

Elasticsearch and HTTP Request integration: Create a new workflow and add the first step

Step 2: Add and configure Elasticsearch and HTTP Request nodes

You can find Elasticsearch and HTTP Request in the nodes panel. Drag them onto your workflow canvas, selecting their actions. Click each node, choose a credential, and authenticate to grant n8n access. Configure Elasticsearch and HTTP Request nodes one by one: input data on the left, parameters in the middle, and output data on the right.

Elasticsearch and HTTP Request integration: Add and configure Elasticsearch and HTTP Request nodes

Step 3: Connect Elasticsearch and HTTP Request

A connection establishes a link between Elasticsearch and HTTP Request (or vice versa) to route data through the workflow. Data flows from the output of one node to the input of another. You can have single or multiple connections for each node.

Elasticsearch and HTTP Request integration: Connect Elasticsearch and HTTP Request

Step 4: Customize and extend your Elasticsearch and HTTP Request integration

Use n8n's core nodes such as If, Split Out, Merge, and others to transform and manipulate data. Write custom JavaScript or Python in the Code node and run it as a step in your workflow. Connect Elasticsearch and HTTP Request with any of n8n’s 1000+ integrations, and incorporate advanced AI logic into your workflows.

Elasticsearch and HTTP Request integration: Customize and extend your Elasticsearch and HTTP Request integration

Step 5: Test and activate your Elasticsearch and HTTP Request workflow

Save and run the workflow to see if everything works as expected. Based on your configuration, data should flow from Elasticsearch to HTTP Request or vice versa. Easily debug your workflow: you can check past executions to isolate and fix the mistake. Once you've tested everything, make sure to save your workflow and activate it.

Elasticsearch and HTTP Request integration: Test and activate your Elasticsearch and HTTP Request workflow

Build Your Own Image Search Using AI Object Detection, CDN and ElasticSearch

This n8n workflow demonstrates how to automate indexing of images to build a object-based image search.

By utilising a Detr-Resnet-50 Object Classification model, we can identify objects within an image and store these associations in Elasticsearch along with a reference to the image.

How it works

An image is imported into the workflow via HTTP request node.
The image is then sent to Cloudflare's Worker AI API where the service runs the image through the Detr-Resnet-50 object classification model.
The API returns the object associations with their positions in the image, labels and confidence score of the classification.
Confidence scores of less the 0.9 are discarded for brevity.
The image's URL and its associations are then index in an ElasticSearch server ready for searching.

Requirements

A Cloudflare account with Workers AI enabled to access the object classification model.
An ElasticSearch instance to store the image url and related associations.

Extending this workflow

Further enrich your indexed data with additional attributes or metrics relevant to your users.

Use a vectorstore to provide similarity search over the images.

Nodes used in this workflow

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Popular Elasticsearch and HTTP Request workflows

Build Your Own Image Search Using AI Object Detection, CDN and ElasticSearch

This n8n workflow demonstrates how to automate indexing of images to build a object-based image search. By utilising a Detr-Resnet-50 Object Classification model, we can identify objects within an image and store these associations in Elasticsearch along with a reference to the image. How it works An image is imported into the workflow via HTTP request node. The image is then sent to Cloudflare's Worker AI API where the service runs the image through the Detr-Resnet-50 object classification model. The API returns the object associations with their positions in the image, labels and confidence score of the classification. Confidence scores of less the 0.9 are discarded for brevity. The image's URL and its associations are then index in an ElasticSearch server ready for searching. Requirements A Cloudflare account with Workers AI enabled to access the object classification model. An ElasticSearch instance to store the image url and related associations. Extending this workflow Further enrich your indexed data with additional attributes or metrics relevant to your users. Use a vectorstore to provide similarity search over the images.

Create an automated workitem(incident/bug/userstory) in azure devops

Who is this template for? This template can be used by any automator who wants to create a workitem(incident/user story/bugs) in azure devops whenever an alert raised by systems. How it works Each time an alert raised in system( for ex: Elastic raises an alert for missing host or domain). Workflow reads an alert and creates a workitem in azure devops Workflow can be customized to send any required information as possible in azure devops Setup Instructions Azure DevOps Organization and Project:** Make sure you have access to an Azure DevOps organization and a project where the work item will be created. Personal Access Token (PAT):** You need a Personal Access Token with permissions to create work items. You can generate a PAT from the Azure DevOps user settings.

Build your own Elasticsearch and HTTP Request integration

Create custom Elasticsearch and HTTP Request workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.

Elasticsearch supported actions

Document
Index

Create

Create a document

Delete

Delete a document

Get

Get a document

Get Many

Get many documents

Update

Update a document

Create

Delete

Get

Get Many

Elasticsearch and HTTP Request integration details

With Elasticsearch, you can store, search, and analyze massive amounts of data fast and in near real-time, with results arriving in milliseconds. Because it searches an index rather than the text itself, it can produce quick search results.

Elasticsearch node docs + examples

Elasticsearch credential docs

See Elasticsearch integrations

Related categories

Development

Data & Storage

HTTP Request node docs + examples

See HTTP Request integrations

Related categories

Development

Other integrations with Elasticsearch