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Observability Pipelines. Shaped Before They Land.

Transform, enrich, redact, reduce.

Transform, enrich, redact, reduce, and parse your observability data with real-time and scheduled pipelines.

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OpenObserve Pipelines Dashboard
Redact PII Before It’s Stored

Redact PII Before It’s Stored

Strip or mask sensitive fields at ingestion, before data ever hits disk.

Parse and Enrich in Real Time

Parse and Enrich in Real Time

VRL functions transform data the moment it arrives, no batch delay.

One Pipeline, Any Format

One Pipeline, Any Format

Handle JSON, syslog, CEF, and custom formats without separate parsers per source.

Data Processing

Shape Data Before It Costs You

Pipeline Types

  • Real-time

    Transform data the instant it arrives. Parse, filter, and enrich streams on the fly, turning raw data into immediate insights.

  • Scheduled

    Orchestrate batch transformations precisely when you need them. Aggregate massive datasets, convert logs to actionable metrics, and process data on your timeline.

Pipeline Types

Data Transformation

  • VRL Functions

    Build custom transformations that parse, enrich, and filter your data streams with functions that handle complex logic requirements.

  • Data Parsing

    Transform logs into structured data regardless of format using pre-built parsing functions.

Data Transformation

Data Enrichment

  • Enrichment Tables

    Transform raw events into context-rich data using simple CSV lookup tables. Add location data, user details, and metadata that turns isolated signals into patterns.

  • Dynamic Lookups

    Pull in external context via API at ingestion time, no separate enrichment step required.

Data Enrichment

Pipeline Components

  • Function Nodes

    Build data processing workflows with VRL function nodes. Execute custom logic for complex transformations and create reusable components.

  • Stream Operations

    Filter, clone, and route streams to multiple destinations, ensuring every bit of data reaches exactly where it needs to go.

Pipeline Components
Benchmarks

Measured against the platforms you are already paying for

Same telemetry, same workloads, one platform. Every number is OpenObserve against a named vendor - not an industry average.

  • vs. Datadog

    8×

    more cost-effective

    8x cost reduction means you can unify your observability into a single platform.

    Read case study
  • vs. Elastic

    140×

    storage efficiency

    140x storage means longer retention doesn't necessarily mean expensive bills.

    Read case study
  • vs. Dynatrace

    10×

    faster performance

    10x performance means dashboards and queries load in milliseconds, not minutes.

    Read case study
  • vs. New Relic

    30×

    compute efficiency

    30x compute efficiency means you index everything and don't have to compromise on sampling.

    Read case study

See how much you would save switching today.

Testimonials

Teams trust OpenObserve with their data pipelines

Correlate between the environments and signals across various sources with OpenObserve built-in correlation engine.

Ajith Natarajan

“[OpenObserve is] super fast, definitely very lightweight, and you can get started with an initial POC in two to three minutes to be honest.”

2–3 min

To first POC

Lightweight

Minimal footprint

AI vision

Retail analytics platform

Ajith Natarajan

Ajith Natarajan

Lead Software Engineer, Radius.ai

Observability Pipelines FAQs

Resources

Explore guides, videos, and articles

to help you get the most out of Observability Pipelines.

Ready to get started?

Try OpenObserve today for more efficient and performant observability.

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