High Performance Telemetry Pipeline

Collect once from every layer. The data foundation for full-stack AIOps.

FFWD Pipeline collects natively from every layer of your stack — GPU, network, container, application — at AI scale, without gaps. It's the cross-domain telemetry foundation that FFWD's anomaly engine and agent assurance depend on to see what no single monitoring tool can. Built on Rust, deployed privately, at flat-rate pricing that doesn't scale with your data.

AI Scale Data Volume Breaks Traditional Economics

Assuring AI agents across the full stack requires telemetry from every layer — not just what one monitoring tool sees. Gaps in the data mean blindspots in the agent execution risk.

Every monitoring system, every SIEM, every analytics platform demands its own data feed. The result: redundant collection infrastructure, spiralling per-GB costs, and vendor lock-in that makes switching destinations expensive.

AI workloads make it exponentially worse. GPU telemetry, model inference logs, agent traces, container metrics — AI-era infrastructure generates orders of magnitude more telemetry than traditional software. At 20TB/day, per-GB pricing to destinations like Splunk or Datadog becomes a budget crisis. The observability tools meant to give you visibility become the line items your CFO questions.

FFWD Pipeline sits in front of your expensive destinations, reducing volume before it arrives — and its flat-rate model means your pipeline costs don't grow with your data.

FFWD Telemetry Pipeline Infrastructure

Collect Once. Ship to Many.

FFWD Pipeline sits at the aggregation point — collecting from all sources in any format, then routing to any combination of destinations: Splunk, Datadog, Elasticsearch, Kafka, S3, cloud storage, your data lake — whatever you need, now or in the future.

Reduce — Filter, sample, deduplicate, and throttle to cut 50%+ volume before it hits expensive destinations Transform — Parse, enrich, mask, normalise in-flight with AI-assisted auto-parser and WYSIWYG configuration Route — Send different data to different destinations based on content, source, or priority No lock-in — Add or switch destinations anytime at zero marginal cost

Telemetry Pipeline is an Infrastructure, not just a tool

AIOps isn't one system — it's many specialist 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.

FFWD Pipeline is the foundation layer. Adding a new AIOps project, connecting a new data lake, or feeding a new anomaly engine is instant — because the collection, parsing, and routing infrastructure already exists.

FFWD's Agent Assurance evaluates Stack State across GPU, network, container, and application layers simultaneously. That cross-domain view is only possible because the pipeline is already collecting from all of them — natively, at scale, without gaps. The pipeline isn't a companion to agent assurance. It's the data layer it runs on.

Built in Rust. Engineered for AI-Scale Throughput.

Universal Collector (Edge)

  • 100K+ events/sec per instance

  • Rust-native, multi-threaded, GC-free

  • Parse and configure with your AI app via MCP — no regex required

  • Deploy as Docker container or Kubernetes pod

Data Cluster (Central)

  • Beyond 500K events/sec proven throughput

  • Parquet/Arrow columnar storage and efficient compression

  • Minimal compute footprint means the cluster runs on a fraction of the hardware competitors require

  • Built-in search, dashboarding, and alerting — no need to forward to a separate analytics tool for day-to-day operations

50+ Native Source Formats

Cloud — AWS S3, SQS, SNS, Kinesis, CloudWatch · GCP PubSub, GCP Storage · Azure Blob, Azure Monitor

Messaging — Kafka / AWS MSK · AMQP · MQTT · NATS · Redis · Pulsar · Splunk HEC

Infrastructure — Kubernetes · Docker logs · Host metrics · JournalD · Syslog · Exec

Monitoring — OpenTelemetry · Prometheus · StatsD · SNMP · NGINX · Apache · Postgres · Datadog · MongoDB · Okta

Data Sources — File · Socket · Stdin · HTTP Client/Server · Fluent · Logstash · dnstap · GNMI · WebSocket

GPU Telemetry — NVIDIA · Intel · AMD · Huawei · Broadcom · Apple · Qualcomm

AI Apps via MCP — Parse and configure collectors using AI agents natively

Auto-Parse — ~100 Grok templates + custom format support

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, sites, or customers from a single deployment with full data isolation. Edge collectors deploy at every site; the central cluster aggregates wherever you choose.

Collect everything. Detect across it all. Gate every agent action against what's real. That's the full-stack loop — pipeline, anomaly engine, and agent assurance, unified.