Capabilities

Everything you need to collect, shape, route, and govern telemetry at the first mile

LyftData exposes seven core capabilities — Collect, Transform, Route, Compose, Scale, Observe, Visual Editor — all running on the deterministic Server → Jobs → Workers architecture. Each capability builds toward control, scale, and governance.

See Solutions →Explore the Docs →

Here’s what you can do with LyftData today.

Three themes

To keep complexity understandable, every primitive belongs to one of these themes:

CONTROL & COST

  • •Shape and mask data before it hits metered tools
  • •Route curated subsets into expensive platforms
  • •Archive full fidelity cheaply

Every byte is intentional, not accidental.

SCALE & RELIABILITY

  • •Server → Jobs → Workers keeps behavior deterministic
  • •Workers scale horizontally without rewrites
  • •Run & Trace shows exactly what will happen before deployment

Pipelines stay predictable even as telemetry grows.

GOVERNANCE & AUDITABILITY

  • •Jobs are signed, version-controlled definitions
  • •Run & Trace produces auditable evidence
  • •Server stores lineage and approvals

You can prove how data moved — every time.

Collect

Workers read directly from your existing sources with a single Input definition per Job.

  • •Files & file shares
  • •S3 / GCS / Azure Blob
  • •Windows Events
  • •HTTP / APIs
  • •Security sources like CrowdStrike

What it solves

  • •Tool-specific agents and scripts
  • •Duplicated ingestion logic
  • •Missed sources due to inconsistent configs

A consistent, governed ingestion layer.

Inputs & Sources →

Transform (Actions)

Chain declarative Actions to filter, parse, enrich, mask, script, and normalize every event.

  • •Filter — remove noise
  • •Parse — extract fields
  • •Enrich — add context
  • •Redact / Mask — govern sensitive data
  • •Script — run custom logic
  • •Normalize — produce consistent structures

What it solves

  • •Brittle per-tool transforms
  • •Untraceable scripts
  • •Inconsistent masking and enrichment

Cleaner, reviewable data upstream.

Actions Reference →

Route

Each Job defines the primary Output so you can intentionally deliver to SIEM, observability, analytics, or archives.

  • •SIEM
  • •Observability tools
  • •Data platforms
  • •Object storage
  • •Archival buckets

What it solves

  • •Over-ingesting into expensive tools
  • •Blind forwarding
  • •Duplicated pipelines per destination

Every destination receives only the data it needs.

Outputs →

Compose (Channels)

Channels clone and fan out governed outputs so one Job can feed many downstream systems.

  • •Curated logs → SIEM
  • •Structured events → observability
  • •Full-fidelity logs → archive

What it solves

  • •Copy-paste pipelines per tool
  • •Inconsistent policies across branches
  • •Costly re-ingestion when adding destinations

One pipeline, many intentional outputs.

Channels →

Scale

Workers are stateless executors you can add anywhere without rewriting Jobs.

What it solves

  • •Per-cluster drift
  • •Scaling tied to agents
  • •Risky deployments under load

Predictable performance and safer parallelism.

Operate & Scale →

Observe

LyftData surfaces logs, metrics, and traces from Workers back to Server.

What it solves

  • •Blind pipelines
  • •Slow failure detection
  • •Unverifiable transformations

Observability by default.

Operate Overview →

Visual Editor

Author Jobs visually, preview transformations with Run & Trace, then export or review in YAML.

What it solves

  • •Hidden UI-only logic
  • •Slow pipeline authoring
  • •Handwritten configs without guardrails

Speed during creation, precision during review.

Visual Editor →

Why these capabilities matter — Because your downstream tools shouldn’t dictate your data structure.

When telemetry pipelines live in vendor agents and per-tool configs, every change becomes fragile and expensive.

  • •Downstream tools no longer dictate your pipeline shape
  • •You avoid vendor lock-in while keeping the tools you already use
  • •You prevent cost explosions and surprise ingest bills
  • •You maintain one chain of custody for governance and audits

LyftData makes telemetry predictable — operationally, economically, and in compliance posture.

See how teams put these capabilities to work

Explore Solutions →See Integrations →
See real workflows in action

Security, observability, and data teams already building on LyftData.

Check compatibility with your stack

Browse supported sources and destinations.

Understand the architecture

Walk through Server → Jobs → Workers in detail.