SME Track: Developers
Presenter: Pramod Saripalli
Date: 2026-10-07
SLB × Elastic Workshop Program
Elastic-native workflows for validating service health and correlating telemetry.
These labs run on Observability Serverless — a fully managed project so you can practice without cluster operations.
The same capabilities you explore here — ES|QL, Streams, AI Assistant, Agent Builder, Workflows, and SLOs — are available on Elastic Cloud Hosted (ECH) and self-managed deployments.
Serverless mainly saves operational toil (sizing, ILM, Fleet, upgrades). Your observability skills transfer directly.
Use → to see why each feature matters for SLB.
Logs, metrics, and traces in one place
Three tabs, three tools, manual correlation — "which deploy caused this spike?" takes too long.
APM, Logs Explorer, and Metrics views link the same service context — pivot from error log to trace to CPU in clicks.
One query language for logs, metrics, and traces
Different syntax per signal — PromQL for metrics, LogQL for logs, trace UI only — context switching slows incidents.
ES|QL pipes data through filters, stats, and joins across observability datasets in Logs Explorer and Dev Tools.
User-facing reliability, not just green dashboards
CPU graphs look fine while customers see errors — no shared error budget or burn-rate language with product teams.
SLOs define availability/latency targets from real traces and metrics, with burn alerts before users flood support.
Signal without the noise
Alert storms, duplicate pages, and rules that never get tuned — on-call learns to ignore the channel.
Threshold, anomaly, and SLO-based rules with grouping, suppression, and AI-assisted triage in one alerts UI.
Your lab uses Elastic Observability Serverless for a zero-ops learning environment.
The steps and features are the same on ECH and on-prem — follow the assignment panel when Kibana opens.
Instruqt track: slb-sme-developers