The Platform

Not a collection of tools.
An integrated control plane
with a point of view.

Four features. One topology graph. One operating model. Kubernetes at the centre — as the universal control plane for infrastructure, workloads, ML jobs, IoT fleets, and DR orchestration.

01 · Infra 02 · Observability 03 · BC/DR 04 · Incidents

The FalconIO architecture.
Every layer. Every flow.

The engineer-facing surface sits at the top. Four features operate underneath — all Kubernetes-native, all reading from and writing to a shared topology graph. The telemetry backbone flows across all features into the observability store.

Engineer & Operator Surface
IDP Service Catalogue
Self-service infra requests
Policy-gated provisioning
Service catalogue UI
Centralised Dashboards
Infra · Observability
BC/DR · Incident queue
MTTR trending
Incident Queue
Native incident module
All event types unified
Auto-context attached
↕ requests flow down · status & telemetry flow up ↕
Four Features — All Kubernetes-Native
01 · Infra + IDP
Crossplane XRDs
Pulumi Stacks
IDP Catalogue
OPA Policies
Drift Detection
FluxCD GitOps
02 · Observability
OTel Collector
VictoriaMetrics
ClickHouse
Grafana
Alerting
Trace Storage
03 · BC/DR
BC Manifests
Chaos Scheduler
Pulumi Failover
RTO Tracking
ISO 22301
SOC 2 Evidence
04 · Incidents
Native Queue
Auto-Context
BC Activation
Incident Timeline
Post-mortems
Integrations
⎈ KUBERNETES CONTROL PLANE ⎈
Telemetry flow: OTel Collector Vector VictoriaMetrics (hot) ClickHouse (analytics + traces)
Shared Foundation
Topology Graph + Policy Store
CockroachDB · BC Manifest Store · OPA Policy Store
Single source of truth — read by all four features
Cloud & Edge Targets
AWS · GCP · Azure · OCI · On-prem Kubernetes · Edge nodes (IoT / ML)
The Infrastructure Plane
Infra + IDP
Kubernetes-driven · Crossplane + Pulumi · Policy-enforced

Infrastructure state is the ground truth for every other feature. FalconIO makes it explicit, versioned, continuously reconciled, and policy-enforced. The Internal Developer Platform sits in front of a hybrid provisioning engine — engineers self-serve through a policy-enforced catalogue while the platform team maintains a single source of truth across every cloud and cluster.

Crossplane handles Kubernetes-native self-service and continuous drift reconciliation. Pulumi handles code-first complex provisioning, bootstrap operations, and BC/DR failover execution. Each does what the other cannot. Together they deliver infrastructure that is developer-friendly, drift-free, and fully tested before it ships.

Crossplane XRDs — intent-based infra APIs abstracting AWS, GCP, Azure, OCI specifics
Pulumi Automation API — unit and integration tested infrastructure before production execution
IDP service catalogue with OPA policy gates — self-service with guardrails in the workflow
Shared topology graph in CockroachDB — source of truth for all four features
Drift detection with continuous reconciliation — divergence surfaced before incidents
FluxCD GitOps — infrastructure changes auditable, rollback-ready, same pipeline as app code
Cilium CNI + eBPF — L7 network policy, zero-trust workload isolation, full multi-tenancy
Envoy Gateway — L7 traffic management, advanced routing, traffic splitting
KEDA + Karpenter — event-driven autoscaling tuned by ClickHouse analytics
OTel Collector — universal telemetry pipeline: metrics, traces, logs in one standard
VictoriaMetrics — hot metrics, high-cardinality, long-retention, PromQL-compatible
ClickHouse — long-term analytics, trace storage, cross-signal correlation
Centralised dashboards — one surface covering all four FalconIO features simultaneously
Pre-built dashboards for SCM, logistics, manufacturing, and industrial stacks
Trace-metric correlation — latency spikes correlated with infra events in one query
KEDA tuning intelligence — scaling from ClickHouse demand analytics, with/without AI
Alerting with topology context — every alert knows which BC Manifests are affected
60–80% cost reduction vs Datadog — consequence of open backend choice
The Intelligence Plane
Observability
OTel-native · VictoriaMetrics + ClickHouse · Unified

Observability in FalconIO is the intelligence layer every other feature reads from. BC/DR trigger thresholds are derived from live telemetry. Autoscaling decisions are informed by ClickHouse long-term analytics. Incident tickets are created with observability snapshots already attached.

VictoriaMetrics handles your operational hot path. ClickHouse handles your analytical depth — trace storage, resource utilisation modelling, and cross-signal correlation. They are complementary, not redundant.

The Continuity Plane
BC/DR
RTO/RPO as code · Chaos pre-calculated · Compliance generated

Most organisations have a DR document. FalconIO replaces it with BC Manifests — versioned, topology-aware resilience declarations that execute via Pulumi, measure actual recovery against declared targets, and feed the incident management feature with context the moment a BC event is triggered.

Polyglot persistence — ScyllaDB, CockroachDB, Redpanda — breaks every standard DR template. BC Manifests model your actual dependency graph, not a generic template.

BC Manifests per service, per tier — RTO/RPO as versioned code, topology-linked
Pulumi stack execution — failover tested before it runs, deterministic, fully audited
Chaos scheduler with blast radius pre-calculation — no experiment runs blind
Semi-automated runbooks — platform executes, operator confirms critical thresholds
Polyglot failover sequencing — CockroachDB, ScyllaDB, Redpanda, Postgres
Multi-cloud failover — active-active, active-passive across AWS, GCP, Azure, OCI
RTO actual vs declared — every test and activation measured against target
ISO 22301 + SOC 2 evidence — generated continuously, not assembled pre-audit
Native incident queue — outages, DR activations, IDP events, changes, bugs in one system
Auto-context attachment — topology, observability snapshot, BC Manifests at ticket creation
Incident timeline — chronological automated record of every action taken
BC/DR activation from incident — one click, platform handles execution + logging
Post-mortem generation — pre-populated from incident timeline and observability data
MTTR intelligence — recovery velocity trended per incident type, per service tier
Integrations: Jira, ServiceNow, PagerDuty, OpsGenie, Linear, Slack
The Context Plane
Incident Management
Native module · Every event type · Full context

Incident management in FalconIO is not a webhook to Jira. It is a native module that understands infrastructure topology, observability state, and BC Manifests — because incident context is platform intelligence, not a text field an engineer fills in while a system is down.

Every event type — outage, DR activation, IDP provisioning, change management, bug, post-mortem — flows through one queue. The most expensive minutes of any incident are the first ones. When context is auto-attached, those minutes collapse.

One dashboard.
Every feature. No tab-switching.

Zone 01
Infra Dashboard

Topology graph state, Crossplane reconciliation health, Pulumi stack status, drift detection results, KEDA and Karpenter activity, IDP request throughput.

Zone 02
Observability Dashboard

Live metrics from VictoriaMetrics, long-term analytics from ClickHouse, trace latency percentiles, resource utilisation trends, KEDA scaling event history.

Zone 03
BC/DR Dashboard

BC Manifest coverage, last-tested timestamps, chaos test log, RTO actual vs declared per service tier, MTBF and MTTR trending, DR readiness score.

Zone 04
Incident Dashboard

Open incident count and severity, active BC/DR activations, MTTR by type and tier, post-mortem completion rate, change management throughput.