Supercharged OpenSearch Tools for VS Code
Develop, test, and optimize OpenSearch queries with a VS Code extension built for modern workflows. Run requests, validate mappings, and generate realistic test data — right inside your editor.
Kibana DevTools-like Interface
Run HTTP requests and inspect responses without leaving VS Code
Get a familiar DevTools experience tailored for OpenSearch. Execute REST calls, browse results, and manage connections for Amazon OpenSearch Service or self-managed clusters — all from your editor.
Key Capabilities:
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Request Runner: Execute GET, POST, PUT, and DELETE with an interactive request/response panel. -
Connection Management: Configure multiple hosts, auth, and Amazon OpenSearch Service endpoints with helpful warnings.
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File Streaming: Use < or @ to stream bodies from files — no more massive copy/paste.
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Tabular Views: Optional tables for _cat APIs and search results with easy copy-as-cURL.
Productivity Features:
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Contextual IntelliSense: Smart completion for queries, aggregations, and field types — tuned for OpenSearch.
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One-Tap Bool Wrapping: Quick actions to wrap selections in filter, should, or must_not clauses.
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Rich Snippet Library: 50+ ready-to-use snippets to accelerate common search and aggregation patterns.
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Built-In JSON Tools: Format and validate JSON on the fly to keep your requests clean and correct.
Advanced Query Editor
Faster authoring for OpenSearch queries and aggregations
Write complex OpenSearch DSL with confidence. IntelliSense, quick actions, and JSON formatting help you prototype faster and reduce syntax errors.
Index Mapping Editor
Uncover issues before they impact query speed and storage
Analyze mappings for potential bottlenecks and anti‑patterns. Get targeted guidance on field choices, analyzers, and structures to keep your indexes lean and fast.
Validation Toolkit:
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Instant Mapping Checks: Paste mappings and receive actionable insights in seconds.
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Performance Suggestions: Recommendations tailored to your schema and usage patterns.
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Snippet Starters: 30+ mapping templates for field types and common patterns.
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Test Data Hook: Generate realistic sample data directly from your mapping.
Generator Options:
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Mapping-Aware Output: Produce data that respects field types, analyzers, and expected shapes.
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All Major Types: Text, numeric, date, geo, keyword, nested — fully supported.
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Configurable Volume: Choose document counts and tune distributions for realistic datasets.
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Editor Integration: Run from the Command Palette or the context menu on mapping files.
Mock Data Generator
Create realistic datasets for testing and demos
Spin up sample documents that mirror your mappings so you can prototype queries, validate dashboards, and benchmark performance with confidence.