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Elasticsearch-native · OpenTelemetry · OpenLineage

Data observability that runs on the stack you already trust

DataObs is an Elasticsearch-native platform for data, pipeline, and AI observability. Detect quality issues, understand lineage and blast radius, monitor streams, and govern autonomous agents — all with search-first investigation in Kibana and a dedicated operational console.

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Data platforms fail in silence

Dashboards look healthy while data is stale.
Pipelines succeed but output quality drifts.
Lineage is incomplete when incidents happen.
AI agents move data without enough visibility.
Telemetry is collected, but data trust and business impact stay unclear.

Six-pillar product model

DataObs organises observability around the questions that matter to platform, data, and business teams.

1. Platform

What is deployed, where, and is it healthy? Hosts, containers, Kubernetes, serverless, and cloud data services.

2. Data Pipeline

Are jobs and streams running correctly and on time? Spark, dbt, Glue, Lambda, Kafka, and more.

3. Data

Can I trust my data? Freshness, volume, schema, nullness, uniqueness, distribution drift, and lineage.

4. FinOps & Cost

What is the platform costing, and why? Allocation, anomalies, and optimisation signals.

5. Business

Is the platform delivering value? SLAs, KPI impact, and data-product reliability.

6. AI & Agent

Can AI and autonomous agents be trusted, controlled, and audited?

Core capabilities

Quality & freshness
Pluggable checks, baselines, and SLA monitoring.
Lineage & impact
Dataset and column-level lineage with blast-radius analysis.
Pipeline & streams
Job health, lag, throughput, and pathway monitoring.
Incident workflows
Alerting, cases, and guided remediation paths.
Search-first investigation
Elasticsearch + Kibana as the system of record.

Architecture principles

Elasticsearch-native

Data streams, versioned state indices, transforms, ES|QL, and Kibana for deep investigation. Elasticsearch is the system of record.

Open standards

OpenTelemetry for telemetry. OpenLineage for job and lineage events. Vendor-neutral ingestion by design.

Collection plane

Reuse Elastic Agent / Fleet / EDOT where possible. DataObs Scanner for data-specific scanning, profiling, and quality.

How we help you adopt it

The product is open and self-managed. We also offer focused delivery engagements to accelerate value.

Observability Assessment Sprint

Map telemetry gaps and define a practical implementation roadmap.

From £2,500

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OTEL Foundation Build

Implement OpenTelemetry patterns across data pipelines and platforms.

From £5,000

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AI Agent Telemetry PoC

Add governance visibility for agent, MCP, and tool activity.

From £3,000

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Open-source companion

AgentGuard — AI activity observability

AgentGuard collects and normalises AI activity telemetry into ECS, then routes events to your existing Elastic or OpenSearch stack.

Explore AgentGuard View on GitHub

Free OTel Config Generator

Describe your infrastructure. Get deployable OpenTelemetry Collector configs and an architecture diagram — instantly, in your browser.

Open the tool →

Ready to make your data platform observable?

Elasticsearch-native data observability with open standards, a clear six-pillar model, and practical delivery support.

Send a message

We respond within 1 business day. You can also email hello@dataobs.co.uk directly.