OllyGarden for Industry

# Clean telemetry for your industry

Every industry has unique telemetry challenges — from PII in traces to 100K-collector deployments. We’ve talked to dozens of teams to understand what matters most and built tools that improve telemetry quality at the source.

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Finance IndustryFinancial Services

Financial institutions generate massive volumes of telemetry while navigating strict compliance, PII controls, and vendor lock-in. OllyGarden helps you improve telemetry quality at the source and take control of your pipeline without compromising on security or cost.

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](/solutions/financial-services)

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Commerce IndustryRetail & E-commerce

Retail and e-commerce platforms live or die by peak-season reliability. Noisy, inconsistent telemetry hides the failures that cost revenue at checkout. OllyGarden helps you clean up instrumentation at the source, so your signals stay trustworthy when traffic spikes the most.

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](/solutions/retail-ecommerce)

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Software IndustryEnterprise Software

Enterprise software companies instrument thousands of services across multi-tenant platforms. OllyGarden helps you improve instrumentation quality at scale and give every developer the guidance they need to ship clean telemetry.

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](/solutions/enterprise-software)

From the field

[Enterprise software · North America · Anonymized, but real · Audio episode

## Nearly half the spans came from a service called cli: what we found at a 500-service enterprise platform

One background worker named cli made 45% of all spans, a third of logs were exact duplicates, a third were access logs, and the Collector shipped its own logs again.

- 45% of all spans came from one unnamed worker
- 32% of log records were exact duplicates
- 4.5% of logs were the Collector re-shipping its own outputRead the story](/resources/case-studies/enterprise-platform-half-the-spans-had-no-name)[Digital health · Europe · Anonymized, but real · Audio episode

## The PII leak was a logger setting, not a developer problem: what we found at a European digital-health platform

Personal data in 1 in 6 services traced to one ORM logging setting, logs with no severity at all, one worker writing most of the logs, and auth tokens Rose found in a day.

- 17% of services flagged for personal data in week one
- 100k log lines a week with personal data, from one service
- 100% of logs arrived with no severityRead the story](/resources/case-studies/digital-health-pii-leak-was-a-logger-setting)[Enterprise software · Latin America · Anonymized, but real · Audio episode

## How a B2B SaaS platform cut logs 24% and metrics 25% in six weeks, without touching a single customer log

Repeated logs, metrics that never change, and a pipeline complaining about itself. How replay-verified Collector changes beat a six-week proof of value, and what happened after.

- 24% fewer log records
- 25% fewer metric datapoints
- 61% less volume on dedup-eligible logsRead the story](/resources/case-studies/b2b-saas-cuts-logs-and-metrics-at-the-source)

The findings in these stories fall into five dimensions of telemetry quality: identity, volume and waste, cost drivers, safety, and correctness. [What is telemetry quality? →](/resources/telemetry-quality)

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