docs(day1): Added opensearch talk
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content/day1/06_opensearch.md
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content/day1/06_opensearch.md
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---
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title: OpenSearch - The Open source Path to Search and Observability
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weight: 6
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tags:
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- observability
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---
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<!-- {{% button href="https://youtu.be/rkteV6Mzjfs" style="warning" icon="video" %}}Watch talk on YouTube{{% /button %}} -->
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<!-- {{% button href="https://docs.google.com/presentation/d/1nEK0CVC_yQgIDqwsdh-PRihB6dc9RyT-" style="tip" icon="person-chalkboard" %}}Slides{{% /button %}} -->
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A introduction to opensearch and "look at the cool new features in 3.o"
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## History
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- Background: Was born out of the elasticsearch license change as a fork by AWS
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- Since Late 2024: A part of the linux foundation
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## Platform
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### Elements
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- Core: Distributed Search Engine with Vector DB
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- Dashboards: UI with Dashboards, Alerts, Reports, ...
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- Data Preppers: Prepare Data for ingest and indexing
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```mermaid
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graph LR
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DataSource-->DataPrepper-->|Ingest into|Core
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subgraph Core
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LogIndex
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TraceIndex
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TimeseriesIndex
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end
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```
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### Use-Cases
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- Search: Well - search (e.g. for Amazon's product search)
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- Free text search & fuzzy search
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- Faceting (Generate Attributes based on the content and search by them)
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- Geospacial Search & Vector Search
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- Observability: Log analytics
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- Log analytics with specialized query language or natural language
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- OTEL and Jaeger Support
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- Query federation to prometheus for metrics
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- AI/ML: It's a vector database
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- Vector database that can be used for embeddings
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- Multimodal search for text image and video with one model or one model per mode
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- Neural sparse search and simmilarity search
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- MCP and bring your own model support
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- Security: Tracing, log detection and so on
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### Performance
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- Problem: Large Datasets are usually slow
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- Solution: Specialized improvements
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## News: Openstack 3.0
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- Baseupgrades for Lucene, JDK and Node (yay)
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- Performance: Reader/Writer-Seperation, gRPC Support, Pull-based injection in addition to pushed-based
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- Improvements: Cross cluster search for traces, better nested json support
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