Akri
Akri is a CNCF Sandbox project that exposes heterogeneous leaf devices (such as IP cameras and USB devices) as resources in a Kubernetes cluster. It enables dynamic discovery and utilization of IoT edge devices through protocol-specific Discovery Handlers for ONVIF, OPC UA, and udev, with automatic workload scheduling and high availability.
Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.
API Evangelist profiles Akri the way a machine reads it — 51 machine-readable artifacts across 1 API, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Akri scores 55.4/100 (developing), with a separate agent-readiness read of 45/100 (agent ready). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Akri
Each block below is one kind of artifact we hold for Akri. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 1
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
Akri Metrics API
Prometheus metrics endpoints for Akri Agent, Controller, and broker pods
Pricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.
Published pricing tiers and plan structures.
Akri Plans Pricing
PLANSRate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Akri Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
Akri Finops
FINOPSFeatures 10
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
Notable capabilities this provider offers.
Dynamic Device Discovery
Automatically discovers heterogeneous leaf devices (IP cameras, USB devices, industrial sensors) across Kubernetes cluster nodes using protocol-specific Discovery Handlers.
ONVIF Discovery Handler
Discovers IP cameras via ONVIF standards and RTSP streams, with filtering by IP address, MAC address, ONVIF scopes, and device UUIDs.
OPC UA Discovery Handler
Discovers industrial automation servers and Local Discovery Servers via OPC UA protocol, supporting x509 certificate authentication for secure connections.
udev Discovery Handler
Discovers locally attached hardware (USB devices, cameras, microphones) on Linux nodes using udev rules with kernel device name and capability filtering.
Automatic Workload Scheduling
Automatically schedules broker Pods or Jobs per discovered device based on Akri Configuration specifications, managing the full workload lifecycle.
High Availability
Multiple nodes can access a single leaf device, ensuring service continuity if a node fails. Supports multi-node device reservation.
Kubernetes Custom Resources
Two CRDs: configurations.akri.sh for discovery specification and instances.akri.sh representing each discovered device as a Kubernetes resource.
Extensible Discovery Handler Framework
Community can implement custom Discovery Handlers as DaemonSets using the akri-discovery-handler-template, enabling support for any device protocol.
Prometheus Metrics
Built-in Prometheus metrics on port 8080 for instance count, discovery response results, discovery latency, and broker pod count, with Grafana visualization support.
Multi-Architecture Support
Supports Linux nodes on amd64, arm64v8, and arm32v7 architectures with Kubernetes v1.16+, K3s, and MicroK8s distributions.
Scroll within the panel for all 10 ·
Semantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Akri Akri Context
JSON-LDSpectral Rules 2
Governance rulesets we run against this provider's specs — the automated checks behind parts of the score. Profiling them makes the quality bar explicit and re-runnable, not a matter of opinion.
Akri API Rules
SPECTRALAkri API Rules
SPECTRALJSON Schema 7
Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.
Standalone JSON Schema definitions for this provider's data models.
AkriBrokerPodCount
JSON SCHEMAAkriConfiguration
JSON SCHEMAAkriDiscoveryResponseResult
JSON SCHEMAAkriDiscoveryResponseTime
JSON SCHEMAAkriInstanceCount
JSON SCHEMAAkriInstance
JSON SCHEMAPrometheusMetrics
JSON SCHEMAScroll within the panel for all 7 ·
JSON Structure 7
JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.
JSON Structure definitions describing this provider's data shapes.
Akri Akri Broker Pod Count Structure
JSON STRUCTUREAkri Akri Configuration Structure
JSON STRUCTUREAkri Akri Discovery Response Result Structure
JSON STRUCTUREAkri Akri Discovery Response Time Structure
JSON STRUCTUREAkri Akri Instance Count Structure
JSON STRUCTUREAkri Akri Instance Structure
JSON STRUCTUREAkri Prometheus Metrics Structure
JSON STRUCTUREScroll within the panel for all 7 ·
Examples 6
Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.
Example request and response payloads for these APIs.
Security Posture 1
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Use Cases 5
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
What developers build with this provider.
Edge IoT Device Management
Expose and manage IoT leaf devices such as IP cameras and USB sensors as first-class Kubernetes resources for edge computing workloads.
Industrial Automation Integration
Connect industrial OPC UA servers and automation equipment to Kubernetes clusters for real-time monitoring and control workflows.
Computer Vision at the Edge
Deploy ONVIF-compliant IP camera brokers automatically as cameras are discovered, enabling distributed computer vision processing.
Dynamic Hardware Resource Scheduling
Automatically schedule GPU, FPGA, or specialized hardware workloads based on real-time device availability across cluster nodes.
Heterogeneous Device Fleet Management
Manage fleets of diverse edge devices with different protocols from a single Kubernetes control plane using unified Configuration resources.
Integrations 7
Pre-built integrations with other platforms tell you where this provider already fits in a stack.
Pre-built integrations with other platforms and tools.
Prometheus
Native Prometheus metrics integration via ServiceMonitor and PodMonitor custom resources, with Grafana visualization support.
Helm
Official Helm chart packaging for deploying Akri Controller, Agent DaemonSet, and Discovery Handler DaemonSets.
Kubernetes Device Plugin Framework
Extends the Kubernetes Device Plugin Framework with edge-specific capabilities for heterogeneous leaf device management.
ONVIF
Built-in ONVIF protocol support for discovering and managing standards-compliant IP cameras and video devices.
OPC UA
Built-in OPC UA protocol support for industrial automation device discovery with certificate-based security.
Linux udev
Built-in udev integration for discovering locally attached hardware devices on Linux Kubernetes nodes.
CNCF Ecosystem
CNCF Sandbox project integrating with cloud native tooling including K3s, MicroK8s, and standard Kubernetes distributions.
Scroll within the panel for all 7 ·
Resources
Every other property we hold for Akri — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 1
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 2
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 3
Pagination, idempotency, versioning, errors, and events
Build 5
SDKs, sample code, and the tooling you integrate with
Access & Security 1
Authentication, authorization, and security posture
Operate 1
Status, limits, changes, and where to get help
← All providers · Data indexed from github.com/api-evangelist/akri · machine-readable index on apis.io