How to Efficiently Scale Splunk with Imply Lumi
The Observability Warehouse that helps you keep more data, move faster, and spend less without changing how you work
Observability Is Hitting Its Limits
Splunk has long been the system of record for observability and security data. It’s powerful, battle-tested, and deeply embedded in how teams work. But today’s telemetry volumes have outgrown the index-first architectures most observability stacks rely on.
As log volumes surge, teams often face difficult trade-offs: shortening retention, pushing data to cold storage, or filtering out entire sources to stay within budget. These decisions slow searches, create gaps in visibility, and erode confidence during investigations.
This is not a Splunk issue—it is a data-growth issue. Modern environments require a more scalable foundation beneath the tools teams already rely on every day.
A New Foundation for Scaling Splunk
Instead of expanding indexers or reducing visibility, organizations are now adding a more efficient data layer beneath Splunk: Imply Lumi.
Imply Lumi complements Splunk with a modern, cloud-native data layer where teams can store and query massive datasets at a fraction of the cost and with significantly faster search performance. It preserves existing workflows, dashboards, and SPL searches while eliminating the scaling challenges of traditional index-first architectures.
Imply Lumi delivers:
• Up to 4x smaller storage footprint
• 2X faster search performance
• Up to 70 % lower platform costs
• No workflow, dashboard, or agent changes
How BI Got Here First
The observability industry is now following the same architectural evolution that transformed business intelligence.
Early BI platforms bundled ingest, compute, storage, and visualization together. As data grew, these monolithic designs could not keep up.
The breakthrough came when BI decoupled:
- ETL tools (like Fivetran/Informatica) took over ingest and routing
- Cloud data warehouses (Snowflake, BigQuery, Databricks) handled scalable compute + storage
- Visualization tools (Tableau, Looker, Power BI) focused purely on analysis and investigation
By separating these layers, BI unlocked flexibility, massive scale, and more predictable costs—and escaped the “all-in-one black box” model that observability is still stuck in today.
Observability is making the same transition. Ingest has been decoupled. Visualization has been decoupled. What’s been missing is a scalable data layer. Lumi completes this transition by decoupling the storage and compute foundation beneath the observability stack.
Seamless With Splunk
Imply Lumi integrates directly with Splunk through Federated Search. Users can query Lumi-stored data from the same Splunk interface, dashboards, and SPL they already use.
There are no new agents, no rehydration steps, and no migration projects.
Under the hood, Imply Lumi separates compute and storage:
- Hot data runs on persistent compute for instant, interactive search
- Cold data lives cost-effectively in S3, GCS, or Azure Blob but remains fully searchable
- Schema-on-persist technology compresses data efficiently and keeps it query-ready
Splunk remains the operational experience. Imply Lumi provides the scale and efficiency behind it.
Bringing Back (and Expanding) the Data You’ve Been Dropping
Many organizations limit or avoid ingesting high-volume logs—VPC flow logs, WAF logs, firewall events, firewall telemetry, Kubernetes logs, and more—because indexing them in Splunk can be cost-prohibitive.
With Imply Lumi, these datasets become affordable and fully searchable through the same Splunk interface your teams already use. That means you can not only bring back data you’ve been forced to drop, but also ingest entirely new sources from across your organization—additional cloud accounts, lines of business, regions, and environments that previously never fit within your license.
As more telemetry lands in Imply Lumi’s observability warehouse, Splunk becomes a window into a much richer, organization-wide dataset. Security, compliance, operations, and platform teams all gain deeper visibility without adding infrastructure or changing workflows.
Do More With the Splunk You Already Use
Imply Lumi is not a replacement for Splunk. It strengthens Splunk by delivering a scalable, efficient data foundation beneath it.
With Imply Lumi, teams can:
• Keep full-fidelity data online for longer
• Run searches and investigations faster
• Expand data ingest without increasing Splunk license usage
• Preserve every dashboard, alert, and SPL search
The result is faster answers, broader visibility, and a dramatically more cost-efficient observability practice.
The Logical Next Step for Growing Splunk Environments
Observability is evolving toward open, flexible, decoupled architectures—the same shift BI made years ago. Imply Lumi brings this evolution to Splunk environments with a compatible Observability Warehouse that scales efficiently, controls cost, and keeps data fully accessible.
Imply Lumi enables organizations to scale Splunk without trade-offs and without changing how teams work.
Learn more about Imply Lumi.
FAQ: Scaling Splunk with Imply Lumi
How can I scale Splunk without increasing ingest costs?
Organizations scale Splunk more efficiently by pairing it with Imply Lumi. Lumi stores observability data at a fraction of the footprint and makes it searchable through Splunk Federated Search, allowing teams to ingest more data without increasing Splunk licensing.
Does Imply Lumi replace Splunk?
No. Lumi complements Splunk. Splunk remains the system for dashboards, alerts, and SPL. Lumi provides a scalable backend for high-volume and long-term data while keeping the Splunk experience intact.
Can Lumi improve Splunk search performance?
Yes. Imply Lumi is optimized for real-time and interactive queries, enabling faster search performance across both recent and historical data, even under high concurrency and high-cardinality workloads.
Do users need to learn new tools or write new queries?
No. Users continue working inside Splunk with the same SPL, dashboards, and workflows. Imply Lumi integrates through Splunk Federated Search with no changes required.
What is an Observability Warehouse?
An Observability Warehouse is a modern data layer optimized for logs, metrics, and traces. It provides fast search performance, efficient storage, and elastic scaling designed specifically for observability and security workloads.
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