Scalability
A subject-matter collection covering APIs, tools, frameworks, and data sources related to application scalability, infrastructure scaling, performance optimization, and elastic resource management. This topic spans cloud provider auto-scaling, event-driven autoscaling (KEDA), load balancing, database scaling, and observability for scale.
Limited machine-readable signal and partial portal coverage — documentation a human can read, but little a machine or agent can consume without scraping.
API Evangelist profiles Scalability the way a machine reads it — 18 machine-readable artifacts across 7 APIs, 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 — Scalability scores 44.2/100 (thin), with a separate agent-readiness read of 24/100 (agent aware). 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 Scalability
Each block below is one kind of artifact we hold for Scalability. 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 7
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.
KEDA (Kubernetes Event-Driven Autoscaling) API
KEDA is a Kubernetes-based event-driven autoscaling component and CNCF graduate project. It provides fine-grained autoscaling (including to/from zero) for event-driven Kubernete...
AWS Auto Scaling API
Amazon Web Services Auto Scaling monitors applications and automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost. Supports EC2 A...
Google Cloud Compute Engine Autoscaler API
Google Cloud's Autoscaler API enables automatic scaling of managed instance groups based on CPU utilization, load balancing capacity, or Cloud Monitoring metrics. Integrates wit...
Azure Autoscale REST API
Microsoft Azure Autoscale provides a REST API for managing autoscale settings on Azure resources including Virtual Machine Scale Sets, App Service, and Azure Container Apps. Sup...
CloudWatch Application Signals API
Amazon CloudWatch Application Signals provides application performance monitoring (APM) to help detect and diagnose performance issues and automatically correlate them with infr...
Prometheus HTTP API
Prometheus is the de-facto open-source monitoring and alerting toolkit for cloud-native applications and a CNCF graduate project. The Prometheus HTTP API provides access to time...
Grafana HTTP API
Grafana is the open-source platform for monitoring and observability, providing a REST HTTP API for managing dashboards, data sources, users, and alerts. Widely used alongside P...
Scroll within the panel for all 7 ·
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.
Rate 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.
Scalability 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.
Scalability Finops
FINOPSSemantic 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.
Scalability Context
JSON-LDSpectral Rules 1
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.
Scalability API Rules
SPECTRALJSON Schema 2
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.
Load Balancer
JSON SCHEMAScaling Policy
JSON SCHEMAJSON Structure 2
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.
Scalability Load Balancer Structure
JSON STRUCTUREScalability Scaling Policy Structure
JSON STRUCTUREExamples 2
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.
Resources
Every other property we hold for Scalability — 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.
Documentation 2
Reference material describing how the API behaves
Design & Contract 2
Pagination, idempotency, versioning, errors, and events
Build 1
SDKs, sample code, and the tooling you integrate with
Company 1
The organization behind the API
Other 1
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/scalability · machine-readable index on apis.io