Introducing Imply Lumi: The Industry’s First Observability Warehouse

Title card reading “Introducing Imply LUMI”.

Every organization I talk to wants the same three things: keep more data, search it faster, and spend less doing it. The problem isn’t ambition — it’s architecture.

Today’s observability platforms weren’t built for the data realities we face now — or for the AI/ML workloads that are quickly becoming table stakes. As data grows, costs rise, performance lags, and teams are forced into painful trade-offs: shorter retention, reduced fidelity, and slower insights.

That’s why we built Imply Lumi — the industry’s first Observability Warehouse. Imply Lumi is a high-performance, drop-in data layer that works with your existing tools. Instead of every solution owning its own expensive storage and indexing layer, Imply Lumi provides a shared foundation that can power them all.

The State of Observability: A Breaking Point

Our recent survey of 132 observability and platform admin professionals paints a clear picture:

Three problem cards: skyrocketing costs (71% of C-suite leaders are actively trying to cut spend), too many tools (many enterprises use 10-20+ security tools), and data gaps and silos (68% of CISOs said siloed data directly increases security risks).

The bottom line: teams are being asked to do more with data while the architecture underneath them is holding them back.

What Business Intelligence (BI) Can Teach Us

This isn’t the first time enterprise data has hit a wall. Business Intelligence faced the same challenges decades ago — and solved them on its path to become a $100B+ market.

Diagram titled “How it Started” and “How it Ended”: business apps once bundled a UI and a database (SAP, JD Edwards, Siebel), then split into separate UI, database, and ETL layers with tools such as Tableau, Snowflake, and Fivetran.

How it started

BI began as tightly coupled stacks where the database and the user interface (UI) were fused together. Every application was its own silo, with no flexibility to change layers or share data across tools.

How it evolved

As BI evolved, decoupling became the key enabler of scale. A three-layer architecture emerged:

  • Visualization — dashboards and analysis tools (e.g., Tableau, Looker, Power BI)
  • Database / Compute — centralized engines for query and storage
  • ETL — pipelines for data acquisition and transformation

This decoupling created flexibility and efficiency. Teams could swap visualization tools without moving the data, or change the engine under the hood without retraining users. That flexibility is what allowed BI to mature into today’s $100B+ market.

Observability is now at the same inflection point. The first signs of decoupling are already here with OpenTelemetry, the emerging open standard for data collection, and Grafana, which is widely used as a visualization layer. But collection and visualization alone isn’t enough. Like BI before it, the way forward is a high-performance warehouse: a shared, high-efficiency foundation that breaks down silos, reduces duplication, and powers many tools at once.

Meet Imply Lumi: The Observability Warehouse

Imply Lumi as the data layer between agents and forwarders (Prometheus, Splunk, Grafana Alloy, OpenTelemetry, Cribl, logstash) and UI and AI tools (Splunk, Claude, LangChain, Grafana, Kibana, Tableau).

Imply Lumi is a high-performance data warehouse for observability — a drop-in data layer that lets you:

  • Store more for less → Keep data at your desired fidelity for a fraction of today’s cost
  • Search without limits → Run queries of any complexity or duration at the best price–performance
  • Keep your workflows → Continue using your existing observability tools and AI copilots — with zero disruption.

At launch, Imply Lumi includes native integrations with Splunk, Grafana, Tableau, and MCP (for AI tools such as ChatGPT and Claude). It runs right alongside your current systems for an easy, low-risk start. And this is only the beginning — additional integrations, including Kibana, are already in progress.

Imply Lumi works with Splunk Universal and Heavy Forwarders, OpenTelemetry, Cribl, and S3 ingestion — preserving sourcetypes, metadata, and field structures so nothing is lost. From day one, it appears as a Splunk-compatible data source for federated search. Your dashboards, alerts, and saved searches keep working exactly as they do now — just faster, with longer retention, and at a fraction of the cost.

See it in action:

Watch how Imply Lumi extends Splunk — more data, faster queries, and lower cost without changing workflows.

Think of it as a sidecar for your observability stack: forward a copy of your data to Imply Lumi for side-by-side comparison, keep your current indexers in place, and flip the switch to make Imply Lumi your primary source when you’re ready.

This makes adoption painless — no need to rip and replace your current platform, retrain your teams, or rewrite pipelines. You can start small, prove the value, and scale confidently.

What You Can Do with Imply Lumi

With Imply Lumi, Splunk remains your home base — but now you can do much more:

  • Cloud Data
    Use Splunk for cloud-native datasets that were previously too expensive to ingest. Bring in high-volume logs like CloudWatch, CloudTrail, and VPC Flow without filtering or budget blowups. Simply connect Lumi to the S3 bucket that has these logs and then start querying them from Splunk.
  • AI/ML
    Query observability data through natural language or build or your AI agents with tools such as Langchain, Claude, ChatGPT. Keep long-term datasets hot to power model training, anomaly detection, and future AI workloads. Or simply enable anyone in the organization to use natural language to search logs.
  • Broad Ecosystem
    Serve the same dataset to multiple tools — Splunk, Grafana, Tableau, and more — without duplicating ingestion. Thinking of migrating to a new tool? Imply Lumi reduces risk by allowing you to keep your data in one place while switching to the new tool

Imagine keeping a full year of data hot and searchable without having to justify it to finance — or running a cross-system search that ties together security, infrastructure, and application events in seconds instead of hours. These aren’t “someday” capabilities. With Imply Lumi, they’re available on day one.

Final Thoughts

Imply Lumi is more than an optimization layer — it’s the foundation of a new architecture for observability. By introducing a shared warehouse for event data, Imply Lumi lets you retain more, search faster, and spend less, all while keeping your existing workflows intact.

This shift creates a central data layer that can power every part of your observability ecosystem — from Splunk to Grafana to AI copilots — without silos or trade-offs.

Contact us to see Imply Lumi in action — and discover how much more your observability stack can do when it’s built on a warehouse, not a bottleneck.

–> Read about our recent updates to Imply Lumi:

A First Look at Lumi Loglake: Query Logs Where They Live

Imply Lumi Loglake vs Splunk Federated Search for S3

Splunk Smartstore vs Lumi Loglake

Query Lumi from Grafana: Now in Private Preview

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