Ingest actions / Edge Processor
Requires building and maintaining transformation pipelines, per source.
Analyzes all sources automatically, with no per-source pipeline to build.
Splunk + Grepr
Optimize Splunk.
Cut your bill by 90%.
Grepr is the Autonomous Telemetry Pipeline that automatically eliminates 90% of your Splunk noise without migrations or disruption to existing dashboards and alerts.
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Splunk isn’t the problem. It’s the expensive, noisy telemetry you don’t use.
Splunk costs come from ingest, indexing, search workload, storage, and retention, and the exact mix depends on your deployment and your contract. Across every model the pattern repeats: more services and more telemetry mean more to index, search, and keep.
Logs hit first because repeated messages stack up fast: health checks confirming nothing changed, retry loops, container start and stop events, and warnings the team triaged long ago. Some of that data supports an audit, a detection, or an incident review. Most of it does not need premium indexing at full cost.
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The usual Splunk cost fixes and why they fall short
Ingest actions / Edge Processor
SmartStore tiered storage
SmartStore tiered storage
Data is still fully indexed and billed against your ingest license before it's tiered.
Reduces what counts against your Splunk license before indexing happens.
Dynamic data self storage
Dynamic data self storage
Retrieving and re-indexing data for an investigation is manual and slow.
Can backfill relevant telemetry data into Splunk, automatically, when an incident occurs.
Index consolidation / license tier downgrades
Index consolidation / license tier downgrades
Largely a negotiation lever, not a structural fix, and volumes typically creep back up before the next renewal.
Reduces noise by 90%, eliminating the need to renegotiate license costs.
Workload pricing migration
Workload pricing migration
Shifts cost rather than reducing the amount of noise flowing through the system in the first place.
Reduces noise before it consumes compute or licensing under either pricing model.
Ingest actions / Edge Processor
Requires building and maintaining transformation pipelines, per source.
Analyzes all sources automatically, with no per-source pipeline to build.
SmartStore tiered storage
Data is still fully indexed and billed against your ingest license before it's tiered.
Reduces what counts against your Splunk license before indexing happens.
Dynamic data self storage
Retrieving and re-indexing data for an investigation is manual and slow.
Can backfill relevant telemetry data into Splunk, automatically, when an incident occurs.
Index consolidation / license tier downgrades
Largely a negotiation lever, not a structural fix, and volumes typically creep back up before the next renewal.
Reduces noise by 90%, eliminating the need to renegotiate license costs.
Workload pricing migration
Shifts cost rather than reducing the amount of noise flowing through the system in the first place.
Reduces noise before it consumes compute or licensing under either pricing model.
Grepr gives you a better option
Reduce expensive, noisy telemetry before it’s ingested into Splunk, and preserve raw telemetry in low-cost storage for those rare moments you need it.
How to optimize Splunk with Grepr
Keeps using Splunk as you always have. Your Dashboards, alerts, runbooks, and investigations stay connected to the same workflows.
Area
Without
With
Telemetry ingestion volume
Full — all telemetry sent to Splunk.
Only high-value signal is sent is to Splunk; low-value noise goes to a low-cost data lake.
Telemetry ingestion cost
Scales with telemetry growth (unsustainable).
Up to 90% noise reduction results in up to 75% observability TCO reduction.
Raw data access
Limited to what Splunk retains.
Preserved in low-cost storage for search and automatic backfill during incidents.
Dashboards and alerts
Unaffected.
Unaffected: Grepr's query translation engine reads your existing dashboards and alerts and automatically ensures the data they depend on is routed through.
Developer toil
Increased: Developers required to set up filtering to control costs.
Reduced: No tinkering required–Grepr automatically eliminates noise.
SRE toil
Increased: Manual log tuning, retention debates, filter maintenance, and slogging through noise.
Reduced: Autonomous signal processing engine eliminates noise.
Deployment effort
N/A
30 minutes: Single configuration change. No migration required.
Grepr sits between your telemetry sources and Splunk
Point your log shippers and agents to Grepr with a single configuration change.
Our signal processing engine automatically eliminates noise. Every two minutes, Grepr sends a summary, such as the qty of repeated patterns with summary statistics.
For example, sending patterns such as request failed for user <*> while preserving configured fields and exceptions.
For example, sending patterns such as request failed for user <*> while preserving configured fields and exceptions.
Raw telemetry remains available in a low-cost data lake. Grepr preserves IDs, IPs, status codes, URL paths, attributes, services, and environments where configured.
Grepr's query translation engine reads your existing dashboards and alerts and automatically ensures the data they depend on is routed through.
Grepr can manually or automatically backfill data based on triggers such as incidents, anomalies, support tickets, or investigations.
Grepr’s processing jobs can run in batch or stream, allowing teams to test processing logic on a file or existing data before turning it into a live workflow.
Connect with one-line config
Point your log shippers and agents to Grepr with a single configuration change.
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Eliminate noise
Our signal processing engine automatically eliminates noise. Every two minutes, Grepr sends a summary, such as the qty of repeated patterns with summary statistics.
For example, sending patterns such as request failed for user <*> while preserving configured fields and exceptions.
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Preserve low-value noise for investigations at a fraction of Splunk’s cost
Grepr preserves IDs, IPs, status codes, URL paths, attributes, services, and environments where configured. Raw telemetry remains available in a low-cost data lake.
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Protect dashboards and alerts
Grepr's query translation engine reads your existing dashboards and alerts and automatically ensures the data they depend on is routed through.
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Backfill archived noise when needed
Grepr can manually or automatically backfill data based on triggers such as incidents, anomalies, support tickets, or investigations.
Test before streaming live
Grepr’s processing jobs can run in batch or stream, allowing teams to test processing logic on a file or existing data before turning it into a live workflow.
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Lower bills. Same visibility. No compromise.
Keep using Splunk–no migrations.
Grepr is not a Splunk alternative. Keep using Splunk exactly as you always have.
Eliminate low-value noise.
Grepr’s signal processing engine automatically eliminates telemetry noise before it reaches Splunk.
Focus on your products, not observability tooling.
Grepr detects millions of patterns, signatures, and trends dynamically. No toilsome rule-building. No log audits. No routing rules to update each sprint. No policing log volumes.
Cost controls that scale with you.
As you ship more software and produce more telemetry, Grepr scales with you, automatically identifying noisy telemetry in real time.
Keep working in Splunk
Use Splunk’s Federated Search to query data from Grepr's data lake without switching tools.
Reducing telemetry volume only helps if you can still get to the data the moment you need it. Splunk Federated Search for Amazon S3 lets you query data stored in S3 directly from Splunk Search.
No separate dashboard, no new query language, no retraining your team.
The Grepr UI is still there for building pipelines and managing your signal processing logic. But for day-to-day investigation, your team never has to leave Splunk.
Reduce Splunk noise by 90%
"Grepr helped us automate what to keep and what to skip, so we’re not paying to store or index noise. It lets us find the needle in the haystack without paying for the haystack!"
Evan Robinson, CTO atJitsu
How Jitsu Cut Logging Costs by 90% While Managing Millions of Shipments Generating 400 Logs Each
"Since we deployed Grepr, we’re seeing a 95% reduction in log volume and didn’t have to change a thing in our app. I'd recommend Grepr to any team that's experiencing rising costs from an expensive logging platform!"
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Dave Bortz, VP Engineering at FOSSA
Case Study: How FOSSA Reduced Their Logs by 95% Without Burdening Their Engineers
“Engineers didn't change how they work at all. Dashboards and alerts still worked as expected. We just stopped paying for 90% of our log volume that was never doing anything for us.”
Ben Ede, Director of Engineering at Envoy
9 Days from Kickoff to Production: How Envoy Cut Log Volume by 90%
“After seeing what Grepr did to reduce our logs noise, extending it to traces was an easy call. We were seeing the same pattern: a lot of volume, most of it not particularly useful, and a Datadog billing model that scaled with every new host we spun up.”
Dave Bortz, VP Engineering at FOSSA
How Envoy Cut Log Volume by 90%
"Grepr helped us automate what to keep and what to skip, so we’re not paying to store or index noise. It lets us find the needle in the haystack without paying for the haystack!"
Evan Robinson, CTO atJitsu
Learn More
"Since we deployed Grepr, we’re seeing a 95% reduction in log volume and didn’t have to change a thing in our app. I'd recommend Grepr to any team that's experiencing rising costs from an expensive logging platform!"
Dave Bortz, VP Engineering at FOSSA
Learn More
“Engineers didn't change how they work at all. Dashboards and alerts still worked as expected. We just stopped paying for 90% of our log volume that was never doing anything for us.”
Ben Ede, Director of Engineering at Envoy
Learn More
“After seeing what Grepr did to reduce our logs noise, extending it to traces was an easy call. We were seeing the same pattern: a lot of volume, most of it not particularly useful, and a Datadog billing model that scaled with every new host we spun up.”
Dave Bortz, VP Engineering at FOSSA
Learn More
FAQs
By how much can I reduce my Splunk costs with Grepr?
Typically up to 90%, but it depends on how noisy your telemetry is. Teams running chatty services, health checks, retry loops, debug logs, and repeated lifecycle events tend to have more reducible volume. Jitsu reduced Datadog log costs by 90% with Grepr. Book a demo for an estimate based on your actual environment.
Do I need to replace Splunk?
No. Grepr is vendor-neutral and works with Splunk. High-value signal is automatically forwarded to Splunk (or Datadog, New Relic, Grafana Cloud, OpenTelemetry, and common log forwarders).
Do I need to modify my Splunk configuration?
A single configuration change points your Splunk collectors to Grepr. No agents to install, no re-instrumentation, and no migrations.
What happens to telemetry data that Grepr decides is “noisy”?
Grepr preserves raw data in low-cost storage for backfill and incident investigation.
Will dashboards and alerts still work?
Grepr's query translation engine reads your existing dashboards and alerts and automatically ensures the data they depend on is routed through.
Will Grepr sample my telemetry data?
No. Sampling usually selects a percentage of events and drops the rest. Instead, Grepr’s signal processing engine detects repetitive, low-value patterns, forwards summaries and high-signal telemetry to Splunk, and preserves raw data in low-cost storage for backfill and incident investigation.
Can Grepr help with Splunk costs beyond logs?
Yes. Grepr also supports distributed tracing, with metrics support anticipated in summer of 2026.
How does Grepr backfill data during an incident?
Grepr can manually or automatically backfill data based on triggers such as incidents, anomalies, support tickets, or investigations.
Does Grepr preservekeep every log event?
Yes. Grepr sends interesting log patterns to Splunk, and preserves the noisy logs in low-cost storage for backfill and incident investigation.
How fast can we get started?
Grepr can be set up in minutes using a single configuration change that points your existing collectors to Grepr. No agents to install, no re-instrumentation, and no migrations.
Does Grepr replace Splunk data governance controls?
No. Your Splunk controls stay useful. Grepr adds an upstream layer that changes the volume and shape of telemetry before it reaches Splunk.
Save up to 90% on your Splunk bill.
Show us your log patterns, trace signatures, and metric trends, and we'll show you how Grepr can reduce your noise.