Webinar Description
Key Takeaways
- Elastic’s summer school session explores the transition from traditional monitoring to AI-assisted observability operations
- Technical demonstrations cover agentic workflows, unified telemetry correlation, and native Prometheus integration
- Designed for DevOps engineers, SREs, platform engineers, and IT operations professionals working with distributed systems
- Addresses operational challenges around incident investigation speed, telemetry fragmentation, and manual troubleshooting processes
- Live Q&A format provides direct access to Elastic’s technical experts
Introduction
The 2026 Summer School: Getting the most out of Elastic Observability & new features is a virtual technical session examining how organisations can advance their observability practices using Elastic’s platform capabilities. Aimed at IT operations teams, DevOps practitioners, and site reliability engineers, the event focuses on the practical application of AI-driven workflows within observability tooling. As enterprises contend with increasingly complex distributed architectures and the volume of telemetry data continues to grow, the session addresses timely questions about how teams can move beyond reactive monitoring toward more automated, intelligence-led operations.
About This Event
Hosted by Elastic, this online session combines live demonstrations with real-world use cases to illustrate recent developments in Elastic Observability. The format emphasises hands-on technical content rather than high-level product overviews, with Elastic engineers walking through specific features and workflows. A live Q&A segment allows participants to raise questions directly with the technical team, making the session particularly relevant for practitioners evaluating or already working with the platform.
The webinar-based format makes the event accessible to geographically distributed teams, which aligns with how most observability and platform engineering functions now operate across enterprise organisations.
From Traditional Monitoring to AI-Assisted Operations
A central theme of the session is the evolution of observability practices. Traditional monitoring approaches typically involve setting static thresholds, manually investigating alerts, and correlating data across separate tools for metrics, logs, and traces. While effective for simpler environments, these methods struggle to scale as infrastructure becomes more dynamic and ephemeral.
The session explores how AI-driven capabilities can augment human operators by automating pattern recognition, surfacing relevant context during incidents, and suggesting remediation paths. This represents a shift from observability as a passive data collection exercise toward an active operational intelligence layer that can accelerate mean time to resolution.
Elastic’s approach to this evolution centres on what the company describes as agentic workflows—the use of AI agents that can autonomously perform investigative tasks, correlate signals across telemetry types, and present synthesised findings to operators. Rather than replacing human judgment, these agents aim to reduce the cognitive load involved in sifting through high-cardinality data during time-sensitive incidents.
Unified Telemetry and Native Prometheus Support
One of the persistent challenges in observability is the fragmentation of telemetry data across different systems and formats. Metrics might reside in one platform, logs in another, and distributed traces in a third. This separation creates friction during troubleshooting, as engineers must context-switch between tools and mentally correlate information that should be connected.
The session addresses this through Elastic’s unified metrics platform, which now includes native support for Prometheus endpoints. Prometheus has become a de facto standard for metrics collection in cloud-native environments, particularly within Kubernetes ecosystems. By ingesting Prometheus-formatted metrics directly, Elastic Observability allows teams to consolidate their telemetry without abandoning existing instrumentation investments.
This unification extends beyond mere data aggregation. When metrics, logs, and traces share a common platform, correlation becomes significantly more straightforward. An anomalous latency spike in a trace can be immediately linked to corresponding log entries and infrastructure metrics, reducing the investigative burden on operations teams.
Practical Demonstrations and Technical Guidance
The session’s emphasis on live demonstrations distinguishes it from more conceptual webinars. Attendees can expect to see specific workflows in action, including how to configure telemetry correlation, implement agentic investigation patterns, and leverage new platform features for faster incident response.
This practical orientation reflects the reality that observability tooling is only valuable when properly implemented. Configuration decisions around data retention, sampling strategies, and alert routing significantly impact whether a platform delivers actionable insights or simply generates noise. By showing real-world implementations, the session aims to bridge the gap between feature announcements and operational deployment.
Industry Context: The Maturing Observability Market
The observability market has matured considerably over the past several years. What began as an extension of traditional application performance monitoring has evolved into a distinct discipline with its own practices, tooling categories, and organisational structures. The emergence of dedicated platform engineering and site reliability engineering roles reflects this maturation.
Simultaneously, the integration of AI capabilities into operational tooling has moved from experimental to expected. Organisations increasingly evaluate observability platforms not just on their data collection and visualisation capabilities, but on their ability to reduce manual toil through intelligent automation. This shift places pressure on vendors to demonstrate concrete AI use cases rather than abstract promises.
The focus on Prometheus compatibility also speaks to broader industry dynamics. As organisations adopt multi-cloud and hybrid architectures, the ability to work with open standards and existing instrumentation becomes a practical requirement rather than a nice-to-have feature.
Who Should Attend
The session is designed for technical practitioners responsible for maintaining system reliability and operational visibility. This includes DevOps engineers managing deployment pipelines and infrastructure automation, site reliability engineers focused on service-level objectives and incident response, and platform engineers building internal developer platforms.
Technology leaders and architects evaluating observability strategies will also find relevant content, particularly around the architectural implications of unified telemetry platforms and AI-assisted operations. The session assumes familiarity with observability concepts and is likely most valuable for those with existing exposure to metrics, logs, and traces as distinct telemetry types.
Organisations currently using Elastic Observability will benefit from the coverage of new features, while those evaluating the platform can assess its capabilities against their operational requirements.
Addressing Operational Complexity
The problems this session addresses are familiar to most operations teams. Incident investigation often involves manually querying multiple systems, correlating timestamps across tools with different time zone handling, and relying on institutional knowledge about system dependencies. As organisations scale, this approach becomes increasingly unsustainable.
By demonstrating how unified telemetry and AI-assisted workflows can streamline these processes, the session offers a concrete vision for reducing operational friction. Whether this translates into meaningful improvements depends on implementation specifics, but the underlying premise—that observability should accelerate rather than complicate incident response—reflects a widely shared aspiration across the industry.