Solutions · Cost Reduction

Keep your stack. Cut the waste.

Tero finds telemetry that is not earning its cost, proves why, and turns it into safe policies in the tools you already run.

Most environments carry 40-60% telemetry waste, sometimes more.

Keep your vendorKeep the signalNo migrationNo blind samplingNo data replayNo pipeline sprawl

Point of view

Most cost strategies change the wrong thing first.

We wrote more on this: The question your observability vendor won't answer.

Switching vendors can lower the unit price, but the junk comes with you. You still have to migrate, rebuild dashboards, retrain teams, and hope the cheaper store does not become expensive once the same bad data lands there.

Sampling lowers the bill, but now you are guessing what signal disappeared.

Archive-and-replay sounds clean until production needs the data now. Replay adds delay, cost, and guesswork. You still have to know which window to replay and whether the signal you need was preserved in the first place.

Pipelines can help, but they usually become another fragile layer of rules. Every new rule is a little more latency, a little more config, and a little more operational surface area.

These approaches exist because teams have been asked to reduce cost without knowing what telemetry is safe to change.

Tero starts somewhere else. It asks what the data is doing for you. Does this event explain failure? Does it record a meaningful business outcome? Does it preserve audit or security value? Does it describe a durable state change? Does it name a dependency problem? Is it carrying a useful domain payload? Is it duplicated by a better signal nearby?

If an expensive event cannot defend why it should stay, it should not keep draining the bill.

Ben Johnson

Founder, Tero
Creator of Vector

Tero Index

Proves what is waste before touching the data.

Tero Issues

Turns waste into work people can trust.

Tero Actions

Fixes cost with Telemetry Policies.

01 · Tero Index

Tero Index proves the waste before touching the data.

Tero does not ask a team to trust a black-box verdict.

The index builds maintained context over the telemetry: event types, representative examples, volume, change over time, semantic meaning, service context, and links back to raw records.

For cost, that context answers the question teams could not answer before: what is this event doing for us? A high-volume event should be able to defend why it stays.

When an event cannot, Tero can show why before anything is sampled, moved, or removed.

Why Tero marked this event as wastecheckout-api

High-volume checkout debug event

checkout_debugpayment_failed · nearby signal

Every value dimension this event could claim is already carried better by payment_failed, one hop away in the same service.

02 · Tero Issues

Tero Issues turns waste into work people can trust.

A cost finding should not be a generic recommendation to "reduce log volume."

It should be an inspectable issue: the specific event, why it is waste, what it costs, who owns it, what evidence supports the decision, what raw records prove it, and what can happen next.

That matters because cost reduction has to be governable. If someone asks why an event was sampled, moved, or removed, the answer should be attached to the issue, the policy, and the measured result.

03 · Tero Actions

Tero Actions fixes cost with Telemetry Policies.

Telemetry Policies are atomic, reviewable, reversible, measurable changes proposed from the issue that found the waste and measured against it.

No giant shared pipeline config. No cleanup campaign pushed onto every service team.

Now officially part of OpenTelemetry ↗

Policy spec ↗Policy examples ↗How policies work ↗

checkout-api / drop-checkout-debug.yamlDrop

id: POL-1031
name: "Drop checkout debug logs"
description: "Created from ISS-1. Redundant with payment_failed."
log:
  match:
    - resource_attribute: [service.name]
      exact: checkout-api
    - log_field: event
      exact: checkout_debug
  keep: none
labels:
  - key: issue_id
    value: ISS-1

Policy runtime

Telemetry Policies run in the tools you already run.

Open-source Tero distributions run the policy engine inside the collector, agent, or pipeline you already operate. You install nothing new and replace nothing.

Approved policies sync to the runtime, and every runtime reports back hits, drops, and measured impact. One compiled matching pass keeps latency flat from ten policies to ten thousand.

Benchmarks ↗Distributions ↗

Raw telemetry

Clean signal

Host

OTel CollectorTero policy enginewasm

Keep your vendor.

The first move should not be a migration. See how far cost drops before any stack change.

Keep the signal.

Engineers, auditors, security teams, and agents keep what they rely on. Only the waste goes.

Skip replay.

Replay is what you reach for when you do not know what matters upfront. Tero keeps valuable signal available now.

Ship policies, not pipeline sprawl.

Many small, reviewable, reversible changes that run where telemetry already flows.

Connect a store.
See what your waste costs.

Priced issues from your own telemetry, evidence attached — no migration, no pipeline rewrite.

Get a demo

Read-only connectionNothing to deployNo pipeline changesWaste is priced automatically