BigPanda
BigPanda is a software platform that uses artificial intelligence (AI) to help IT operations teams automate incident management by correlating alerts from various systems, identifying root causes, and streamlining the incident resolution process, essentially moving from reactive to proactive incident response by providing context and insights through intelligent data analysis.
Solid contracts, transparent operations, and an easy start — typically complete on four or five facets with one clear soft spot.
API Evangelist profiles BigPanda the way a machine reads it — 72 machine-readable artifacts across 6 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 — BigPanda scores 63.2/100 (strong), with a separate agent-readiness read of 48/100 (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 BigPanda
Each block below is one kind of artifact we hold for BigPanda. 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 6
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.
BigPanda Alerts API
Ingest and manage monitoring alerts
BigPanda Audit API
Access audit logs
BigPanda Changes API
Ingest change events for correlation
BigPanda Environments API
Define incident grouping environments
BigPanda Incidents API
View and manage correlated incidents
BigPanda Maintenance Plans API
Schedule maintenance windows to suppress alerts
Open Collections 1
Open, tool-agnostic collections carry the same runnable value as Postman without locking you to one client — the portable, forkable form of the same exercise.
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
BigPanda API
OPEN COLLECTIONPricing 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.
Bigpanda 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.
Bigpanda Finops
FINOPSFeatures 8
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.
AI Alert Correlation
ML-powered correlation of alerts from 200+ monitoring tools into actionable incidents.
Incident Management
Triage, acknowledge, and resolve correlated incidents with full audit trail.
Root Cause Analysis
Automatically identify root causes by correlating alerts with change events.
Maintenance Plans
Schedule maintenance windows to suppress expected alerts during planned work.
Change Correlation
Ingest deployment and config changes to correlate with alert spikes.
Environments
Define DSL-based environments to group incidents by source, severity, or host.
Enrichments
Enrich alerts with contextual tags from CMDB and other data sources.
AIOps Automation
Automate incident response workflows with AI-driven insights and routing.
Scroll within the panel for all 8 ·
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.
Bigpanda 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.
BigPanda API Rules
SPECTRALBigPanda API Rules
SPECTRALJSON Schema 14
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.
AlertRequest
JSON SCHEMAAlertResponse
JSON SCHEMAAuditLogEntry
JSON SCHEMAAuditLogsResponse
JSON SCHEMAChangeRequest
JSON SCHEMAChangeResponse
JSON SCHEMAEnvironmentRequest
JSON SCHEMAEnvironment
JSON SCHEMAEnvironmentsResponse
JSON SCHEMAIncident
JSON SCHEMAIncidentsResponse
JSON SCHEMAMaintenancePlanRequest
JSON SCHEMAMaintenancePlan
JSON SCHEMAMaintenancePlansResponse
JSON SCHEMAScroll within the panel for all 14 ·
JSON Structure 14
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.
Bigpanda Alert Request Structure
JSON STRUCTUREBigpanda Alert Response Structure
JSON STRUCTUREBigpanda Audit Log Entry Structure
JSON STRUCTUREBigpanda Audit Logs Response Structure
JSON STRUCTUREBigpanda Change Request Structure
JSON STRUCTUREBigpanda Change Response Structure
JSON STRUCTUREBigpanda Environment Request Structure
JSON STRUCTUREBigpanda Environment Structure
JSON STRUCTUREBigpanda Environments Response Structure
JSON STRUCTUREBigpanda Incident Structure
JSON STRUCTUREBigpanda Incidents Response Structure
JSON STRUCTUREBigpanda Maintenance Plan Request Structure
JSON STRUCTUREBigpanda Maintenance Plan Structure
JSON STRUCTUREBigpanda Maintenance Plans Response Structure
JSON STRUCTUREScroll within the panel for all 14 ·
Examples 14
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.
Bigpanda Environment Example
EXAMPLEBigpanda Incident Example
EXAMPLEScroll within the panel for all 14 ·
Security Posture 3
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.
Alert Noise Reduction
Reduce alert fatigue by correlating thousands of alerts into a handful of incidents.
Change Impact Analysis
Automatically link deployment changes to alert spikes for faster root cause identification.
On-Call Automation
Route correlated incidents to the right on-call team with full context.
Maintenance Scheduling
Suppress alerts during planned maintenance to prevent false incident creation.
ITSM Integration
Automatically create and update tickets in ServiceNow or Jira from correlated incidents.
Resources
Every other property we hold for BigPanda — 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 2
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 2
Pagination, idempotency, versioning, errors, and events
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 3
Authentication, authorization, and security posture
Operate 2
Status, limits, changes, and where to get help
Company 2
The organization behind the API
← All providers · Data indexed from github.com/api-evangelist/bigpanda · machine-readable index on apis.io