NRDB drop rules
Writing NRQL is confusing.
Requires ongoing maintenance.
Requires ongoing maintenance.
Automatically identifies noisy telemetry signals across all data types without per-rule NRQL authoring.
New Relic + Grepr
Optimize New Relic. Cut your bill by 90%.
Grepr is the Autonomous Telemetry Pipeline that automatically reduces 90% of your New Relic noise without migrations or disruption to New Relic dashboards and alerts.
New Relic isn’t the problem. It’s the expensive, noisy telemetry you don’t use.
New Relic bills on the data you ingest and the people who need access, and both climb as you scale. Every new service, container, and deploy feeds the stream that gets ingested and counted.
A transparent model does not slow the growth of APM events, repeated logs, and high-cardinality metrics. The pressure builds when low-value repetition grows faster than the signal your team acts on, which is the part a pricing page cannot fix for you.
The usual New Relic cost fixes and why they fall short
NRDB drop rules
Pipeline Control
Pipeline Control
Still ingests and bills for data before filtering.
Changes require redeploying configurations across environments.
Changes require redeploying configurations across environments.
Routes noise to low-cost storage before it reaches New Relic, significantly reducing your New Relic bill.
Downgrading to Standard Data tier
Downgrading to Standard Data tier
Reduces query performance and retention length, which can prevent longer investigations.
Keeps full-fidelity raw data in low-cost storage indefinitely and sends only the compressed, high-value signal to New Relic.
Compute unit sampling for APM
Compute unit sampling for APM
Static, per-service setting that ages as traffic patterns and service topology shift.
Continuously adapts to changing signals, dynamically, without re-tuning sampling configs after every architecture change.
User seat downgrades (Full vs Basic)
User seat downgrades (Full vs Basic)
Limits users’ capabilities, pushing work onto a smaller group of Full users.
Reduces the need for seat-tier tradeoffs.
NRDB drop rules
Writing NRQL is confusing. Requires ongoing maintenance.
Automatically identifies noisy telemetry signals across all data types without per-rule NRQL authoring.
Pipeline Control
Still ingests and bills for data before filtering.
Changes require redeploying configurations across environments.
Changes require redeploying configurations across environments.
Routes noise to low-cost storage before it reaches New Relic, significantly reducing your New Relic bill.
Downgrading to Standard Data tier
Reduces query performance and retention length, which can prevent longer investigations.
Keeps full-fidelity raw data in low-cost storage indefinitely and sends only the compressed, high-value signal to New Relic.
Compute unit sampling for APM
Static, per-service setting that ages as traffic patterns and service topology shift.
Continuously adapts to changing signals, dynamically, without re-tuning sampling configs after every architecture change.
User seat downgrades (Full vs Basic)
Limits users’ capabilities, pushing work onto a smaller group of Full users.
Reduces the need for seat-tier tradeoffs.
Grepr gives you a better option
Reduce expensive, noisy telemetry before it’s ingested into New Relic, and preserve raw telemetry in low-cost storage for those rare moments you need it.
How to optimize New Relic with Grepr
Keeps using New Relic 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 New Relic.
Only high-value signal is sent is to New Relic; 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 New Relic 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 asked to collect less telemetry.
Reduced: Developers can collect what they want, and 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 New Relic.
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 New Relic’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.
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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 New Relic. No migrations.
Grepr is not a New Relic alternative. Keep using New Relic exactly as you always have.
Eliminate low-value noise.
Grepr’s signal processing engine automatically eliminates telemetry noise before it reaches New Relic.
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.
New Relic federated logs
Use New Relic’s Federated Logs 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. New Relic Federated Logs lets you query data stored in Amazon S3 directly from the New Relic UI.
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 New Relic.
Reduce New Relic 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 New Relic 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 New Relic?
No. Grepr is vendor-neutral and works with New Relic. High-value signal is automatically forwarded to New Relic (or Datadog, New Relic, Grafana Cloud, OpenTelemetry, and common log forwarders).
Do I need to modify my New Relic configuration?
A single configuration change points your New Relic agents 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 New Relic, and preserves raw data in low-cost storage for backfill and incident investigation.
Can Grepr help with New Relic 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 New Relic, 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 agents to Grepr. No agents to install, no re-instrumentation, and no migrations.
Does Grepr replace New Relic data governance controls?
No. Your New Relic controls stay useful. Grepr adds an upstream layer that changes the volume and shape of telemetry before it reaches New Relic.
Save up to 90% on your New Relic bill.
Show us your log patterns, trace signatures, and metric trends, and we'll show you how Grepr can reduce your noise.