---
title: Get started with workflows
description: Learn how to get started creating Elastic workflows.
url: https://www.elastic.co/elastic/docs-builder/docs/3016/explore-analyze/workflows/get-started
products:
- Elastic Cloud Enterprise
- Elastic Cloud Hosted
- Elastic Cloud Serverless
- Elastic Cloud on Kubernetes
- Elastic Stack
- Kibana
applies_to:
- Elastic Cloud Serverless: Preview
- Elastic Stack: Preview since 9.3
---
# Get started with workflows
In this tutorial, you'll create a workflow that indexes and searches through national parks data. Along the way, you’ll learn the core concepts and capabilities of workflows.
## Prerequisites
- To use workflows, turn on the Elastic Workflows (`workflows:ui:enabled`) [advanced setting](https://docs-v3-preview.elastic.dev/elastic/docs-builder/docs/3016/reference/kibana/advanced-settings#kibana-general-settings).
- You must have the appropriate subscription. Refer to the subscription page for [Elastic Cloud](https://www.elastic.co/subscriptions/cloud) and [Elastic Stack/self-managed](https://www.elastic.co/subscriptions) for the breakdown of available features and their associated subscription tiers.
- Access to workflows is controlled by [Kibana privileges](https://www.elastic.co/elastic/docs-builder/docs/3016/deploy-manage/users-roles/cluster-or-deployment-auth/kibana-privileges). Ensure your role has `All` privileges for **Analytics > Workflows**, which allows you to create, edit, run, and manage workflows.
## Tutorial
To access the **Workflows** page, find **Workflows** in the navigation menu or using the [global search field](https://www.elastic.co/elastic/docs-builder/docs/3016/explore-analyze/find-and-organize/find-apps-and-objects).
Click **Create a new workflow**. The YAML editor opens.
Remove the placeholder content and copy and paste the following YAML into the editor:
```yaml
name: 🏔️ National Parks Demo
description: Creates an Elasticsearch index, loads sample national park data using bulk operations, searches for parks by category, and displays the results.
enabled: true
tags: ["demo", "getting-started"]
consts:
indexName: national-parks
triggers:
- type: manual
steps:
- name: get_index
type: elasticsearch.indices.exists
with:
index: "{{ consts.indexName }}"
- name: check_if_index_exists
type: if
condition: 'steps.get_index.output : true'
steps:
- name: index_already_exists
type: console
with:
message: "index: {{ consts.indexName }} already exists. Will proceed to delete it and re-create"
- name: delete_index
type: elasticsearch.indices.delete
with:
index: "{{ consts.indexName }}"
else:
- name: no_index_found
type: console
with:
message: "index: {{ consts.indexName }} Not found. Will proceed to create"
- name: create_parks_index
type: elasticsearch.indices.create
with:
index: "{{ consts.indexName }}"
mappings:
properties:
name: { type: text }
category: { type: keyword }
description: { type: text }
- name: bulk_index_park_data
type: elasticsearch.request
with:
method: POST
path: /{{ consts.indexName }}/_bulk?refresh=wait_for
headers:
Content-Type: application/x-ndjson
body: |
{"index":{}}
{"name": "Yellowstone National Park", "category": "geothermal", "description": "America's first national park, established in 1872, famous for Old Faithful geyser and diverse wildlife including grizzly bears, wolves, and herds of bison and elk."}
{"index":{}}
{"name": "Grand Canyon National Park", "category": "canyon", "description": "Home to the immense Grand Canyon, a mile deep gorge carved by the Colorado River, revealing millions of years of geological history in its colorful rock layers."}
{"index":{}}
{"name": "Yosemite National Park", "category": "mountain", "description": "Known for its granite cliffs, waterfalls, clear streams, giant sequoia groves, and biological diversity. El Capitan and Half Dome are iconic rock formations."}
{"index":{}}
{"name": "Zion National Park", "category": "canyon", "description": "Utah's first national park featuring cream, pink, and red sandstone cliffs soaring into a blue sky. Famous for the Narrows wade through the Virgin River."}
{"index":{}}
{"name": "Rocky Mountain National Park", "category": "mountain", "description": "Features mountain environments, from wooded forests to mountain tundra, with over 150 riparian lakes and diverse wildlife at various elevations."}
- name: search_park_data
type: elasticsearch.search
with:
index: "{{ consts.indexName }}"
size: 5
query:
term:
category: "canyon"
- name: log_results
type: console
with:
message: |-
Found {{ steps.search_park_data.output.hits.total.value }} parks in category "canyon".
- name: loop_over_results
type: foreach
foreach: "{{steps.search_park_data.output.hits.hits | json}}"
steps:
- name: process-item
type: console
with:
message: "{{foreach.item._source.name}}"
```
Click **Save**. Your workflow is now ready to run.
Click the **Run** icon `play` (next to **Save**) to execute your workflow.
As your workflow runs, execution logs display in a panel next to your workflow. In the panel, you can find:
- **Real-time execution logs**: Each step appears as it executes.
- **Worfklow status indicators**: Green for success, red for failures, and timestamps for duration.
- **Expandable step details**: Click any step to see input, output, and timeline.
To examine past executions:
1. Click the **Executions** tab.
2. View a list of all workflow runs (including pending and in progress runs), along with their status and completion time.
3. Click any execution to see its detailed logs.
## Understand what happened
Let's examine each part of the workflow to understand how it works.
```yaml
name: 🏔️ National Parks Demo
description: Creates an Elasticsearch index, loads sample national park data using bulk operations, searches for parks by category, and displays the results.
enabled: true
tags: ["demo", "getting-started"]
```
- **`name`**: A unique identifier for your workflow.
- **`description`**: Explains the workflow's purpose.
- **`enabled`**: Controls whether the workflow can be run.
- **`tags`**: Labels for organizing and finding workflows.
```yaml
consts:
indexName: national-parks-data
```
- **`consts`**: Defines reusable values that can be referenced throughout the workflow. Use constants for fixed values that don't change between runs. For values that vary per execution, use [inputs](/elastic/docs-builder/docs/3016/explore-analyze/workflows/data#workflows-constants-or-inputs) instead.
- Accessed using template syntax: `{{ consts.indexName }}`. This promotes consistency and makes the workflow easier to maintain.
```yaml
triggers:
- type: manual
```
- **`triggers`**: Defines how the workflow starts.
- **`type`**: Specifies the trigger type. Manual triggers require explicit user action (clicking the **Run** icon `play`) to start a workflow.
```yaml
- name: create_parks_index
type: elasticsearch.indices.create
with:
index: "{{ consts.indexName }}"
settings:
number_of_shards: 1
number_of_replicas: 0
mappings:
properties:
name: { type: text }
category: { type: keyword }
description: { type: text }
```
- **Step type**: This is an action step that directly interacts with Elasticsearch.
- **Step purpose**: Establishes the data structure for the park information, ensuring fields are properly typed for searching and aggregation.
- **Key elements**:
- Uses `elasticsearch.indices.create`, which is a built-in action that maps to the Elasticsearch Create Index API.
- Defines mappings to control how data is indexed (`text` for full-text search, `keyword` for exact matching).
- References the constant `indexName` for consistency.
- Sets index settings for optimal performance in this demo.
```yaml
- name: bulk_index_park_data
type: elasticsearch.request
with:
method: POST
path: /{{ consts.indexName }}/_bulk?refresh=wait_for
headers:
Content-Type: application/x-ndjson
body: |
{"index":{}}
{"name": "Yellowstone National Park", "category": "geothermal", "description": "America's first national park, established in 1872, famous for Old Faithful geyser and diverse wildlife including grizzly bears, wolves, and herds of bison and elk."}
{"index":{}}
{"name": "Grand Canyon National Park", "category": "canyon", "description": "Home to the immense Grand Canyon, a mile deep gorge carved by the Colorado River, revealing millions of years of geological history in its colorful rock layers."}
# ... additional parks
```
- **Step type**: A generic Elasticsearch request action that calls the bulk API directly.
- **Step purpose**: Efficiently loads multiple documents in a single operation, populating the index with sample data.
- **Key elements**:
- Uses `elasticsearch.request` with `method: POST` to call the `//_bulk` endpoint.
- The `refresh=wait_for` query parameter ensures documents are searchable immediately after indexing.
- The `headers` parameter sets `Content-Type: application/x-ndjson`, which is required for bulk operations.
- The `body` uses the pipe (`|`) syntax to define a multiline string in YAML.
- Each pair of lines represents an action (such as `{"index":{}}`) followed by the document to index.
- Uses the field names (`name`, `category`, `description`) from the mappings defined in the `create_parks_index` step.
- This step demonstrates how to handle batch operations using the generic request action.
```yaml
- name: search_park_data
type: elasticsearch.search
with:
index: "{{ consts.indexName }}"
size: 5
query:
term:
category: "canyon"
```
- **Step type**: Internal action step for querying Elasticsearch.
- **Step purpose**: Retrieves specific data based on criteria, demonstrating how workflows can make decisions based on data.
- **Key elements**:
- Searches for parks with category `"canyon"` (will find Grand Canyon and Zion).
- Results from `steps.search_park_data.output` are automatically available to subsequent steps.
- Limits results to 5 documents for manageable output.
- Shows how workflows can filter and process data dynamically.
```yaml
- name: log_results
type: console
with:
message: |-
Found {{ steps.search_park_data.output.hits.total.value }} parks in category "canyon".
Top results: {{ steps.search_park_data.output.hits.hits | json:2 }}
```
- **Step type**: A console step for output and debugging.
- **Step purpose**: Presents the results in a human-readable format, demonstrating how to access and format data from previous steps.
- **Key elements**:
- Template variables access the search results: `{{ steps.search_park_data.output }}`.
- The `| json:2` filter formats JSON output with indentation.
- Uses the exact step name `search_park_data` to reference previous step output.
- Shows how data flows through the workflow and can be transformed.
## Key concepts demonstrated
This workflow introduces several fundamental concepts:
- **Action steps**: Built-in steps that interact with Elasticsearch APIs.
- **Data flow**: How information moves from step to step using outputs and template variables.
- **Constants**: Reusable values that make workflows maintainable.
- **Template syntax**: The `{{ }}` notation for dynamic values.
- **Step chaining**: How each step builds on previous ones to create a complete process.
## What's next
Learn more about the workflow framework:
- [**Triggers**](https://www.elastic.co/elastic/docs-builder/docs/3016/explore-analyze/workflows/triggers): Control when workflows run.
- [**Steps**](https://www.elastic.co/elastic/docs-builder/docs/3016/explore-analyze/workflows/steps): Define how a workflow operates and the outcomes it can produce.
- [**Data and error handling**](https://www.elastic.co/elastic/docs-builder/docs/3016/explore-analyze/workflows/data): Make the workflow resilient to failures and understand mechanisms for controlling data flow.