Conference Description
Key Takeaways
- Annual conference focused on OpenSearch, open source search infrastructure, and observability technologies
- Technical content covering vector search, agentic AI workflows, OpenTelemetry, and observability pipelines
- Designed for solution architects, search engineers, DevOps/SRE professionals, and AI/ML practitioners
- Three-day programme featuring keynotes, workshops, unconference sessions, and certification opportunities
- Held in San Jose, California with participation from sponsors including Aiven, AWS, IBM, and Instaclustr
Introduction
OpenSearchCon North America convenes practitioners and technical leaders working with open source search and observability platforms for three days of intensive learning and community engagement. The conference addresses the growing complexity organisations face when deploying search, analytics, and AI workloads at enterprise scale, particularly as vector search and large language model integrations become operational requirements rather than experimental features.
The event arrives at a moment when engineering teams are navigating significant architectural decisions around AI-ready search infrastructure. Traditional keyword-based search is increasingly supplemented or replaced by semantic and vector-based approaches, while observability requirements have expanded beyond simple monitoring into comprehensive telemetry pipelines that must handle distributed systems spanning multiple cloud environments.
About This Event
OpenSearchCon North America takes place in San Jose, California, bringing together the OpenSearch community for a programme structured around practical implementation rather than theoretical discussion. The format combines keynote presentations with breakout sessions, hands-on workshops, and unconference tracks that allow attendees to shape discussions around their specific technical challenges.
A solutions showcase provides direct access to vendors and technology providers operating within the OpenSearch ecosystem. Sponsors participating in the event include Aiven, AWS, IBM, Portal26, Instaclustr, Adelean, Eliatra, KalDB, KMW, and Valkey, representing a cross-section of managed service providers, security specialists, and infrastructure companies building on open source foundations.
Technical Focus Areas
The conference programme centres on several interconnected technical domains. Vector search and vector database optimisation feature prominently, reflecting the shift toward embedding-based retrieval methods that underpin modern AI applications. These sessions address the practical challenges of indexing high-dimensional vectors at scale while maintaining query performance.
Agentic AI workflows represent an emerging area where search infrastructure intersects with autonomous AI systems. As organisations move beyond simple retrieval-augmented generation toward more sophisticated agent architectures, the underlying search and data retrieval layers require corresponding evolution in design and capability.
Observability content focuses on OpenTelemetry integration and pipeline construction. The challenge of correlating traces, metrics, and logs across distributed systems remains a persistent operational concern, and sessions address strategies for building coherent observability architectures using open standards. Search relevance tuning and plugin development round out the technical curriculum, providing depth for teams customising OpenSearch deployments for specific use cases.
Industry Context
The open source search landscape has evolved considerably since Elasticsearch’s licensing changes prompted the OpenSearch fork. Organisations evaluating search infrastructure now weigh considerations around licensing, vendor independence, and long-term community sustainability alongside pure technical capability. OpenSearchCon serves as a focal point for practitioners committed to genuinely open source approaches to search and observability.
Simultaneously, the integration of AI capabilities into search infrastructure has accelerated. Vector search, once a specialised requirement for recommendation systems and similarity matching, has become foundational for retrieval-augmented generation and other patterns connecting large language models to organisational data. This convergence creates demand for engineering knowledge that spans traditional search relevance, machine learning operations, and distributed systems architecture.
Who Should Attend
The conference targets technical practitioners responsible for search and observability infrastructure decisions. Solution architects evaluating platform choices, search engineers optimising relevance and performance, and DevOps or SRE professionals building observability pipelines will find directly applicable content. AI and ML practitioners working on retrieval systems, data engineers managing analytics infrastructure, and open source contributors seeking community engagement represent additional audience segments.
Certification opportunities provide formal recognition for OpenSearch expertise, while the workshop format offers hands-on experience with implementation patterns that can transfer directly to production environments.