# SaaS SLA Reality Score (`springstea/saas-sla-reality-score`) Actor
Scores the real reliability of SaaS vendors from their public status-page incident history and compares it against the SLA they claim. One structured scorecard per vendor: observed uptime, incident stats, MTTR, trend and a transparent 0-100 score. 168 vendors built in.
- **URL**: https://apify.com/springstea/saas-sla-reality-score.md
- **Developed by:** [Kasım Genç](https://apify.com/springstea) (community)
- **Categories:** Business, Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $5.00 / 1,000 results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
## SaaS SLA Reality Score
Scores the **real, observed reliability** of SaaS vendors from their public status-page incident history — and, when you know the SLA they promise, compares promise vs reality.
- *"Looking for a Stripe alternative — whose public incident history was actually better in the last 90 days?"*
- *"This vendor claims 99.9%. Their own status page implies 97.9%. Ask them about that in the renewal call."*
- *"Which of our critical vendors is trending worse this quarter?"*
One structured scorecard per vendor, per run. Schedule it weekly and feed your vendor-risk dashboard.
### What you get
```json
{
"vendor": "GitHub",
"statusPage": "https://www.githubstatus.com",
"currentStatus": "none",
"claimedSla": 99.9,
"observedUptimePct": 97.946,
"slaGapPct": -1.954,
"reliabilityScore": 30,
"grade": "F",
"scoreDelta": -3,
"scoreBreakdown": { "downtimePenalty": 50, "frequencyPenalty": 17.4, "mttrPenalty": 2.5 },
"windowDays": 90,
"coverageDays": 73,
"windowTruncated": true,
"incidents": 45,
"incidentsByImpact": { "critical": 13, "major": 5, "minor": 27 },
"downtimeMinutes": 2159,
"medianResolutionMinutes": 101,
"p90ResolutionMinutes": 354,
"updatesPerIncident": 6.3,
"incidentsPer30d": 14.5,
"trend": "stable",
"newIncidentsSinceLastRun": [],
"recentIncidents": [ { "name": "...", "impact": "critical", "startedAt": "...", "url": "https://stspg.io/..." } ],
"detectedAt": "2026-07-10T14:16:57.571Z"
}
````
The run summary (`OUTPUT` key in the default key-value store) contains a ready-made ranking of all scored vendors.
### Input
```json
{
"vendors": [
"github",
"openai",
{ "name": "Acme Corp", "statusPageUrl": "https://status.acme.com", "claimedSla": 99.95 }
],
"windowDays": 90
}
```
| Field | Type | Description |
|---|---|---|
| `vendors` \* | `array` | Registry slugs (167 built-in, list below) and/or objects. Any status page built on **Atlassian Statuspage** works via the object form — that covers a large share of the SaaS industry. |
| `windowDays` | `integer` | Analysis window, 7–365. Default 90. |
| `snapshotStoreName` | `string` | Named KV store for per-vendor state between runs (enables `scoreDelta` and `newIncidentsSinceLastRun`). |
| `maxConcurrency` | `integer` | Parallel vendors. Default 5. |
#### Built-in registry (168 vendors)
Every slug below was individually verified against the live status page API:
- **AI:** `anthropic`, `assemblyai`, `cohere`, `deepgram`, `elevenlabs`, `groq`, `langsmith`, `openai`, `pinecone`, `replicate`
- **Automation:** `ifttt`, `make`, `tray`, `workato`, `zapier`
- **CI/CD:** `buildkite`, `circleci`, `codecov`
- **CRM & Sales:** `attio`, `close`, `copper`, `gong`, `hubspot`, `salesloft`
- **Cloud Hosting:** `digitalocean`, `flyio`, `linode`, `netlify`, `render`, `scaleway`, `vercel`
- **Communication:** `discord`
- **Communication APIs:** `ably`, `courier`, `getstream`, `onesignal`, `pusher`, `twilio`
- **Customer Support:** `gorgias`, `helpscout`, `kustomer`
- **Data & Analytics:** `amplitude`, `census`, `confluent`, `dbt`, `elastic`, `fivetran`, `heap`, `mixpanel`, `rudderstack`, `segment`, `snowflake`
- **Databases:** `cockroachdb`, `influxdata`, `mongodb-atlas`, `neo4j`, `planetscale`, `supabase`
- **Design:** `canva`, `figma`, `lucid`, `spline`
- **Developer Tools:** `bitbucket`, `github`, `jfrog`, `launchdarkly`, `ngrok`, `npm`, `ona`, `postman`, `pypi`, `quay`, `readme`, `retool`, `rubygems`
- **E-commerce:** `bigcommerce`, `easypost`, `recharge`, `shippo`, `shipstation`, `shopify`, `squarespace`, `webflow`, `wix`
- **Education:** `coursera`, `duolingo`, `instructure`, `kahoot`, `udemy`
- **Email & Messaging:** `loops`, `mailgun`, `mailjet`, `sendgrid`, `sparkpost`
- **File Storage:** `box`, `dropbox`
- **Gaming:** `epicgames`
- **HR & Finance Ops:** `ashby`, `expensify`, `greenhouse`, `gusto`, `lever`, `quickbooks`, `rippling`, `xero`
- **Infrastructure & CDN:** `bunny`, `cloudflare`, `cloudinary`, `hashicorp`, `imgix`
- **Marketing & Growth:** `braze`, `hotjar`, `iterable`, `klaviyo`, `surveymonkey`, `typeform`, `unbounce`
- **Monitoring & Observability:** `bugsnag`, `datadog`, `fullstory`, `honeycomb`, `logrocket`, `newrelic`, `opsgenie`, `rollbar`, `sentry`, `servicenow-observability`, `statuspage`, `sumologic`
- **Payments & Fintech:** `brex`, `chargebee`, `coinbase`, `gemini-exchange`, `kraken`, `marqeta`, `paddle`, `plaid`, `recurly`, `square`, `wise`
- **Productivity:** `airtable`, `asana`, `atlassian`, `calendly`, `coda`, `confluence`, `docusign`, `dropbox-sign`, `grammarly`, `jira`, `linear`, `miro`, `monday`, `notion`, `pandadoc`, `smartsheet`, `trello`
- **Security & Identity:** `1password`, `duo`, `knowbe4`, `snyk`, `tailscale`
- **Social & Media:** `reddit`, `twitch`
- **Streaming & Media:** `plex` *(most consumer streaming services — Netflix, Hulu, Disney+ — do not operate public status pages, so there is nothing public to measure)*
- **Video & Media:** `vimeo`
- **Video & Meetings:** `mux`, `zoom`
Each scorecard record includes the vendor's `category`, so you can build per-category rankings from the dataset.
#### Where does `claimedSla` come from?
You don't need it — the score works without it. Three sources, in order:
1. **You provide it** (recommended): your contract states your SLA; pass it per vendor and get `slaGapPct`.
2. **Registry defaults**: for a few vendors with well-known public SLA documents (GitHub, Twilio, Cloudflare Enterprise, DigitalOcean) we ship the documented value with its source URL. Verify at the source before relying on it.
3. **Absent** → `claimedSla`/`slaGapPct` are `null`; the reliability score and ranking still work.
### The score formula (fully transparent)
```
score = 100 − downtimePenalty − frequencyPenalty − mttrPenalty
downtimePenalty = min(50, 33 × √(impactWeightedDowntime%))
frequencyPenalty = min(25, weightedIncidentsPer30d × 1.2)
mttrPenalty = min(15, medianResolutionHours × 1.5)
grade: A ≥ 90, B ≥ 80, C ≥ 70, D ≥ 60, F < 60
```
- **Impact weights** (duration): critical 1.0, major 0.4, minor 0.1. **Frequency weights**: critical 1.5, major 1.0, minor 0.4.
- **24 h per-incident cap**: multi-day status items are almost always partial degradations left open, not full outages; without the cap one of them dominates the whole window.
- Calibrated against the real 90-day history of 10 popular status pages so grades spread meaningfully — quiet pages (PyPI, npm) score A/B; incident-heavy quarters (GitHub, Cloudflare in mid-2026) score F. A grade is a statement about the *window you measured*, not the brand.
### Honesty notes (read before quoting scores)
- **This is the public track record, not true uptime.** Status pages are curated by vendors; unposted incidents don't exist here. Treat the score as "what the vendor admits", which is exactly what you can hold them to.
- The public Statuspage API returns at most the **50 most recent incidents**. If those don't reach back to your full window, we shrink the analysis to the covered span and set `windowTruncated: true` + `coverageDays`. Ironically, hitting this limit is itself a reliability signal.
- `observedUptimePct` counts critical+major incident-minutes (capped at 24 h/incident) against the window — an approximation of user-visible availability, not a billing-grade SLA measurement.
- Vendors on custom status systems (Stripe, Slack, AWS, GCP, Heroku, Salesforce...) are not supported yet — only Atlassian-Statuspage-compatible pages.
### Suggested usage
- **Weekly schedule** with your vendor list → time series of scores in the dataset (`scoreDelta` tracks movement).
- **Procurement one-shot**: run once with the candidates you're evaluating; read the ranking in `OUTPUT`.
- Pipe `newIncidentsSinceLastRun` into Slack/webhook via Apify integrations for a lightweight multi-vendor incident feed.
# Actor input Schema
## `vendors` (type: `array`):
Vendors to score. Each entry is either one of the 167 built-in registry slugs covering AI, payments, cloud, dev tools, CRM, HR, e-commerce and more (github, openai, stripe-alternatives like plaid/coinbase, datadog, zapier, gusto, ... — full categorized list in the README) or an object for any Atlassian-Statuspage-based page: {"name": "Acme", "statusPageUrl": "https://status.acme.com", "claimedSla": 99.9}.
## `windowDays` (type: `integer`):
How far back to analyze incident history. Note: the public Statuspage API returns at most the 50 most recent incidents — for busy pages the effective window may be shorter (reported via coverageDays / windowTruncated).
## `snapshotStoreName` (type: `string`):
Named key-value store keeping per-vendor state between runs (enables newIncidentsSinceLastRun and scoreDelta).
## `maxConcurrency` (type: `integer`):
Vendors fetched in parallel.
## `proxyConfiguration` (type: `object`):
Optional proxies for status page requests.
## Actor input object example
```json
{
"vendors": [
"github",
"openai",
"anthropic",
"cloudflare",
"vercel",
"netlify"
],
"windowDays": 90,
"snapshotStoreName": "sla-reality-tracker",
"maxConcurrency": 5
}
```
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"vendors": [
"github",
"openai",
"anthropic",
"cloudflare",
"vercel",
"netlify"
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("springstea/saas-sla-reality-score").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "vendors": [
"github",
"openai",
"anthropic",
"cloudflare",
"vercel",
"netlify",
] }
# Run the Actor and wait for it to finish
run = client.actor("springstea/saas-sla-reality-score").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"vendors": [
"github",
"openai",
"anthropic",
"cloudflare",
"vercel",
"netlify"
]
}' |
apify call springstea/saas-sla-reality-score --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=springstea/saas-sla-reality-score",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "SaaS SLA Reality Score",
"description": "Scores the real reliability of SaaS vendors from their public status-page incident history and compares it against the SLA they claim. One structured scorecard per vendor: observed uptime, incident stats, MTTR, trend and a transparent 0-100 score. 168 vendors built in.",
"version": "0.1",
"x-build-id": "5o0SpyCgmyfKJmYdf"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/springstea~saas-sla-reality-score/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-springstea-saas-sla-reality-score",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/springstea~saas-sla-reality-score/runs": {
"post": {
"operationId": "runs-sync-springstea-saas-sla-reality-score",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/springstea~saas-sla-reality-score/run-sync": {
"post": {
"operationId": "run-sync-springstea-saas-sla-reality-score",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"vendors"
],
"properties": {
"vendors": {
"title": "Vendors",
"type": "array",
"description": "Vendors to score. Each entry is either one of the 167 built-in registry slugs covering AI, payments, cloud, dev tools, CRM, HR, e-commerce and more (github, openai, stripe-alternatives like plaid/coinbase, datadog, zapier, gusto, ... — full categorized list in the README) or an object for any Atlassian-Statuspage-based page: {\"name\": \"Acme\", \"statusPageUrl\": \"https://status.acme.com\", \"claimedSla\": 99.9}."
},
"windowDays": {
"title": "Window (days)",
"minimum": 7,
"maximum": 365,
"type": "integer",
"description": "How far back to analyze incident history. Note: the public Statuspage API returns at most the 50 most recent incidents — for busy pages the effective window may be shorter (reported via coverageDays / windowTruncated).",
"default": 90
},
"snapshotStoreName": {
"title": "Snapshot store name",
"type": "string",
"description": "Named key-value store keeping per-vendor state between runs (enables newIncidentsSinceLastRun and scoreDelta).",
"default": "sla-reality-tracker"
},
"maxConcurrency": {
"title": "Max concurrency",
"minimum": 1,
"maximum": 15,
"type": "integer",
"description": "Vendors fetched in parallel.",
"default": 5
},
"proxyConfiguration": {
"title": "Proxy configuration",
"type": "object",
"description": "Optional proxies for status page requests."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```