High Performance Telemetry Pipeline
Collect once. Route anywhere. Cut costs to destinations by 50% or more.
FFWD Pipeline is enterprise telemetry infrastructure built on Rust. Collect from any source, transform in-flight, and forward to any destination—all within your private environment.
Observability Silos are Killing Your Budget
Every monitoring system, every SIEM, every analytics platform demands its own data collection. The result: redundant collection infrastructure, spiralling costs, and vendor lock-in that makes switching destinations expensive.
AI workloads make it worse. AI-scale log volumes are exponentially higher. Traditional observability pricing models weren't built for this, causing costs spiral out of control.
FFWD Telemetry Pipeline Infrastructure
Collect Once. Ship to Many.
FFWD Pipeline sits at the aggregation point. Collecting from all sources in any format, then route to any combination of destinations: Splunk, Datadog, Elasticsearch, Kafka, S3, your data lake—whatever you need, now or in the future.
Reduce: Filter and sample to cut 50%+ volume before it hits expensive destinations
Transform: Parse, enrich, normalise in-flight with AI-assisted configurations
Route: Send different data to different destinations based on content, source, or priority
No lock-in: Add new destinations anytime at zero marginal cost
Telemetry Pipeline is an Infrastructure, not just a tool
AIOps isn't one system—it's many systems. Every new AI tool, every new monitoring platform, every new analytics engine needs telemetry data. Without a pipeline layer, you rebuild collection infrastructure for each one.
With FFWD pipeline, adding a new AIOps project or connecting a new data lake is therefore instant.
Private Deployment
FFWD Pipeline runs entirely within your environment. On-premises, private cloud, or air-gapped—your telemetry never leaves your security perimeter. No SaaS dependencies. No data sovereignty concerns. Multi-tenant architecture lets you run FFWD as private SaaS—serving multiple business units from a single deployment with full data isolation.