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Realtime data observability
for microservices

Fewer issues. Higher security. Improved productivity.

Detected

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Infra Related

Most production problems in modern stacks are caused by data related issues.

But, the vast majority of these issues are never actually detected by monitoring systems.

Undetected

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Data Related

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Service changes:

Schema, variable type, precision mismatches and other data layer changes can break dependent services

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Data corruption:

Null values, old data, distribution errors remain undetected until business metrics suffer.

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Security & Privacy:

Unintended transmission of sensitive data to vendors or logging to files creates risk over time.

Built by industry veterans from:

Airbnb
Apple
Facebook
Google
Metamind
Nvidia
Trooly

Client VPC

On-Perm service

services
monitors

METADATA

LAYER 9 SaaS

Dashboards

services

dependencies

endpoints

schemas

health

activities

documentation

saas

Troubleshooting is hard, particularly for data issues

The majority of production issues are related to data changes. From schema changes to type mismatches and data corruption, data issues go undetected until they start to affect business metrics

mines
data

Data can be mishandled, increasing your risks

From inadvertent PII logging to sharing sensitive data with hundreds of third party app vendors, it is tough to track what is happening with your sensitive data in motion.

Wasted effort from many people responding to related errors, alerts

In loosely coupled microservice environments, errors can cause cascading failures across many services, creating a response that is spread across multiple team members and frequently duplicative.

tools
owner

Service ownership confusion, weak accountability

With large, globally distributed teams, simply knowing who owns a particular service is often a challenge. Setting and measuring appropriate performance targets and SLOs is even more burdensome.

Layer 9 for deep microservices observability

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