Edge Datalake: the unified performance data behind every insight
The single repository that unifies telemetry from all twelve Edge modules. Every metric, trace, log and event stored together, queryable together, and retained under your sovereignty terms.
See exactly what your team will see
What it puts in front of your teams
Every capability is available from day one. No additional instrumentation required beyond the initial agent deployment.
See a live demonstrationSingle repository
All twelve modules write to one lake. Every metric, trace, log and event is queryable together with no silos.
Prediction ready
The historical depth and breadth of the lake enables the forecasting and anomaly detection models that power Edge AI.
Feeds automation
Every playbook, alert and AI recommendation draws from the lake, ensuring decisions are based on the full picture.
Data sovereignty
Deployed inside your infrastructure. Data never leaves your environment or crosses a border without your explicit control.
Tiered storage with full query
Hot data stays fast; cold data remains accessible. No blackout periods on historical queries regardless of retention tier.
Custom retention policies
Define retention rules per signal type, per regulation or per business unit, and prove compliance with an audit log.
From signal to action in seconds
Deploy once
A lightweight Edge agent deploys to your environment. Auto-discovery maps services, hosts and applications without manual configuration.
Collect everything
30 days of database latency data reveals a pattern: every Thursday at 23:00, a batch job causes contention that persists into Friday morning. A scheduled alert and preemptive maintenance window fix the problem permanently.
Act with confidence
Anomaly detection, root cause analysis and AI-assisted recommendations give your teams the context to act fast and correctly.
Signals captured by LAKE
30 days of database latency data reveals a pattern: every Thursday at 23:00, a batch job causes contention that persists into Friday morning. A scheduled alert and preemptive maintenance window fix the problem permanently.
What changes for the business
Whole picture analytics
Query across every signal type in one place. No joining data from separate tools or exporting to spreadsheets.
Cost optimised retention
Tiered storage keeps hot data fast and cold data affordable, with full query access across both.
Foundation for AI
The breadth and depth of the lake is what makes Edge AI recommendations meaningful rather than generic.
Better together with the Edge platform
LAKE writes its data to the Edge Datalake, making it queryable and correlatable alongside every other module in real time.
Edge Datalake questions, answered
What is enterprise observability?
Enterprise observability is the ability to understand the internal state of complex distributed systems by examining the outputs they produce — metrics, traces, logs, and events — at the scale and depth required by large organisations. It goes beyond basic monitoring to provide the context needed to understand why a system is behaving a certain way, not just that something is wrong.
What is observability?
Observability is a measure of how well the internal state of a system can be inferred from its external outputs. In software and IT operations, observable systems produce rich telemetry — metrics, distributed traces, structured logs, and events — that together allow teams to understand system behaviour, detect problems, and diagnose root causes without having to predict failure modes in advance.
Why is observability important?
Modern applications are distributed, dynamic, and complex. Traditional monitoring — checking whether a server is up or a threshold has been crossed — cannot provide sufficient context when something goes wrong in a microservices architecture or cloud-native environment. Observability gives teams the data and tools to ask arbitrary questions about system behaviour and get useful answers quickly, which directly reduces incident duration and prevents repeat failures.
How does observability improve system reliability?
Observability improves system reliability by giving teams the information they need to detect problems early, understand their scope, and resolve them quickly. It also supports proactive reliability work — identifying bottlenecks, understanding dependencies, and validating that changes have the expected effect — before problems reach production.
What does Edge Datalake monitor?
Edge Datalake captures signals including ingest rate, storage utilisation, query latency, cross-module correlation depth, retention coverage, data sovereignty boundary, and provides single repository, prediction ready, feeds automation and more.
How is Edge Datalake deployed?
Edge connects through lightweight agents or agentless connectors — typically 2–4 hours for a standard environment — and can be deployed on-premises, in your private cloud or in a regional cloud, so monitoring data stays within your jurisdiction.
Does it work with the monitoring tools we already use?
Yes. Edge is designed for a no-rip-and-replace approach and connects alongside your existing stack, with 100+ integrations across cloud, containers, databases, APM agents, telemetry standards and alerting channels.
How is it priced?
Pricing is tailored to the scale of your environment, the modules you choose and your deployment model. Start with a short, no-obligation discovery session and NCG will prepare a scoped proposal.
More answers in the FAQ library, or book a demo to see LAKE on your own environment.
Ready to see Edge Datalake live?
We deploy a proof of value in your environment. You keep it if it delivers. No long commitments, no surprises.