Solutions
Observability & Cost Optimization
Route, filter, and compress telemetry data before it reaches storage or vendor backends. LyftData gives you control over observability pipelines to lower cost and increase signal quality.
Problem
Modern observability stacks produce terabytes of logs and metrics daily. Without in-flight control, teams pay for redundant or low-value telemetry, driving exponential vendor bills and slowing analysis.
LyftData Solution
- In-flight filtering: drop debug noise or unused fields before ingestion to reduce volume without losing signal.
- Dynamic routing: send only priority events to Splunk or Datadog, archive non-critical payloads to S3 or GCS.
- Compression & deduplication: compact payloads and remove redundant metrics without losing fidelity.
- Actions for enrichment: add contextual metadata (region, service, severity) to every log entry automatically.
LyftData’s Server and Workers execute these actions in parallel, ensuring your telemetry data remains fast, efficient, and governed.
Outcome
Teams reduce ingest spend while keeping dashboards cleaner, queries faster, and alerting more reliable. Engineers regain clarity by sending high-signal data to premium tools and archiving the rest.
Example policy
A simple routing policy expressed as questions: pay for high-signal telemetry, archive what you may need later, and drop low-value noise.
Next steps
Learn how LyftData optimizes data flow from edge collectors to cloud storage. Explore supported connectors or start your free pilot.