# SaaS Status Monitor — Uptime & Outage Tracking for 100+ Serv... (`apricot_blackberry/saas-status-monitor`) Actor

Monitor 100+ SaaS status pages. Outage alerts, uptime history, and reliability patterns. Know before your users complain.

- **URL**: https://apify.com/apricot_blackberry/saas-status-monitor.md
- **Developed by:** [Creator Fusion](https://apify.com/apricot_blackberry) (community)
- **Categories:** Developer tools, Automation, Business
- **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $50.00 / 1,000 status checks

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## SaaS Status Monitor

**Monitor 100+ SaaS status pages. Real-time outage detection, uptime history, reliability patterns, and early warning signals for the tools your business depends on.**

Your entire business depends on SaaS tools working. When Stripe goes down, you lose payments. When Slack is slow, nobody gets work done. This actor monitors 100+ major services continuously—Stripe, AWS, GitHub, Slack, Vercel, Supabase, Twilio, and more. Get real-time outage alerts, track uptime trends, and identify which services are reliability risks.

### ⚡ What You Get

```
SaaS Reliability Dashboard
├── Monitoring Period: Last 90 days
├── Services Monitored: 47
├── Critical Status Summary
│   ├── All Systems Operational: 41 services
│   ├── Degraded Performance: 4 services
│   │   ├── AWS Lambda (eastern-us): Latency +340ms
│   │   ├── GitHub Actions: 15% slower builds
│   │   ├── Stripe API: 2% error rate (normal: 0.1%)
│   │   └── Vercel: CDN cache issues (regional)
│   └── Down: 0 services
├── Uptime Statistics
│   ├── Stripe: 99.97% (1h 28m downtime in 90d)
│   ├── AWS: 99.92% (6h 31m downtime)
│   ├── GitHub: 99.98% (51m downtime)
│   ├── Slack: 99.85% (10h 44m downtime)
│   └── Industry Average: 99.94%
├── Recent Incidents 👈 Know what went wrong and when
│   ├── Feb 10, 2024: Stripe Payment API
│   │   ├── Duration: 12 minutes
│   │   ├── Status: "Connection timeouts affecting 0.3% of requests"
│   │   ├── Root Cause: Database maintenance
│   │   └── Impact: ~$2M in transactions delayed
│   ├── Feb 5, 2024: GitHub Actions
│   │   ├── Duration: 28 minutes
│   │   ├── Impact: CI/CD pipelines queued
│   │   └── Compensation: 1 week free for enterprise
│   └── Jan 28, 2024: AWS Lambda (us-east-1)
│   │   ├── Duration: 47 minutes
│   │   ├── Impact: Lambda cold starts +2000ms
│   │   └── Status: No downtime, degraded performance only
├── Reliability Scores
│   ├── Tier 1 (99.99% uptime): Anthropic, OpenAI
│   ├── Tier 2 (99.9-99.99%): Stripe, AWS, GitHub, Google Cloud
│   ├── Tier 3 (99.5-99.9%): Slack, Twilio, SendGrid
│   └── Trend: All improving YoY
├── Outage Patterns
│   ├── Most Common Time: Tuesday 2-4am PST
│   ├── Most Common Cause: Database maintenance
│   ├── Fastest Recovery: Stripe (avg 8 min)
│   └── Slowest Recovery: AWS (avg 23 min)
└── Your Risk Assessment
    ├── Critical Tools (if down, business stops): Stripe, AWS, GitHub
    ├── Dependency Risk: High (3 critical tools)
    ├── Recommendation: Add backup payment processor (Adyen)
    └── Next Step: Test failover procedures
```

### 🎯 Use Cases

- **DevOps Teams**: Monitor the infrastructure you depend on. Know outages before your users complain.
- **Business Continuity**: Which services are critical to your business? Track their uptime. Plan disaster recovery.
- **SaaS Leadership**: Understand reliability profiles of your vendors. Factor into tool decisions.
- **Incident Response**: Outage happening now? Check status pages, see who else is affected, find root cause quickly.
- **Vendor Evaluation**: Comparing SaaS tools? Pull 90-day uptime history. Reliability matters.
- **Cost Optimization**: Track services degrading. Do you need premium tier, or does standard tier uptime meet your needs?

### 📊 Sample Output

```json
{
  "scan_timestamp": "2024-02-15T10:30:00Z",
  "monitoring_period_days": 90,
  "services_monitored": 47,
  "critical_status": {
    "operational": 41,
    "degraded": 4,
    "down": 0
  },
  "uptime_stats": [
    {
      "service": "Stripe",
      "uptime_percent": 99.97,
      "downtime_minutes": 88,
      "incidents_count": 1,
      "avg_recovery_minutes": 8
    },
    {
      "service": "AWS",
      "uptime_percent": 99.92,
      "downtime_minutes": 391,
      "incidents_count": 4,
      "avg_recovery_minutes": 23
    }
  ],
  "recent_incidents": [
    {
      "service": "Stripe",
      "incident_date": "2024-02-10T14:23:00Z",
      "start_time": "2024-02-10T14:23:00Z",
      "end_time": "2024-02-10T14:35:00Z",
      "duration_minutes": 12,
      "status": "Resolved",
      "description": "Connection timeouts affecting 0.3% of requests",
      "root_cause": "Database maintenance window",
      "components_affected": ["Payment API", "Billing"]
    }
  ],
  "reliability_tiers": {
    "tier_1": {"services": 2, "uptime_threshold": 99.99},
    "tier_2": {"services": 12, "uptime_threshold": 99.9},
    "tier_3": {"services": 33, "uptime_threshold": 99.5}
  },
  "outage_patterns": {
    "most_common_time": "Tuesday 02:00-04:00 PST",
    "most_common_cause": "Database maintenance",
    "fastest_mttf_service": "Stripe",
    "slowest_mttf_service": "AWS"
  },
  "risk_assessment": {
    "critical_services": ["Stripe", "AWS", "GitHub"],
    "dependency_risk": "high",
    "recommended_actions": [
      "Add backup payment processor",
      "Test AWS failover procedures",
      "Implement GitHub Actions backup (self-hosted)"
    ]
  }
}
```

**Field Descriptions:**

- `uptime_percent`: Calculated uptime over monitoring period
- `incidents_count`: Number of outages or degraded performance events
- `avg_recovery_minutes`: Average time from incident start to resolution
- `components_affected`: Which specific features/APIs went down
- `reliability_tiers`: Grouping services by uptime guarantee

### 🔗 Integrations & Automation

**Slack Alerts**: Real-time outage notifications. Stripe down? Slack alert instantly.

**Email Alerts**: Daily digest of uptime, any incidents, and reliability trends.

**PagerDuty Integration**: Auto-trigger incidents when critical services go down.

**Webhook to Custom Dashboards**: Push status data into your own monitoring system.

**MCP Compatible**: AI agents can assess vendor reliability during tool evaluation.

**REST API**: Continuous monitoring, build uptime dashboards.

[See integration docs →](https://docs.apify.com/platform/integrations)

### 🔌 Works Great With

- **[Crunchbase Company Scraper](https://apify.com/apricot_blackberry/crunchbase-company-scraper)** — Evaluate SaaS startups. Check funding, then check their status page history.
- **[Website Tech Stack Detector](https://apify.com/apricot_blackberry/website-tech-stack-detector)** — See what services a company uses, then monitor their uptime.
- **[Traffic Test to Your Page](https://apify.com/apricot_blackberry/traffic-test-to-your-page)** — Load test your site, but first confirm your SaaS dependencies are healthy.

### 💰 Cost & Performance

**Typical run:** Monitor 47 services continuously, check status pages every 5 minutes for ~$8.50/month.

That's **$0.18 per service per month** — cheaper than the cost of one outage.

**Compare to manual:** Checking 47 status pages manually every 5 minutes = 288 checks/day × 47 services = impossible. You need our automation.

### 🛡️ Built Right

- **Multi-source status checking** pulls from official status pages + third-party monitors
- **Real-time alerts** notify within 2 minutes of incident detection
- **Historical tracking** 90+ days of uptime data
- **Incident parsing** extracts root causes, impact, recovery time
- **Anomaly detection** flags slower performance even without formal outage
- **Reliability scoring** ranks services by proven uptime

***

**Fresh data. Zero guesswork. Be the first to know.**

📧 [Email alerts](https://apify.com/apricot_blackberry/saas-status-monitor) · 🔗 [Webhook triggers](https://docs.apify.com/platform/integrations/webhooks) · 🤖 [MCP compatible](https://docs.apify.com/platform/integrations) · 📡 [API access](https://docs.apify.com/api/v2)

Built by [Creator Fusion](https://apify.com/apricot_blackberry) — OSINT tools that actually work.

# Actor input Schema

## `services` (type: `array`):

List of service slugs to check (e.g., \['github', 'vercel', 'stripe']). Leave empty for all services.

## `categories` (type: `array`):

Filter by category. Leave empty to use services list or get all.

## `includeComponents` (type: `boolean`):

Include detailed component status (API, Dashboard, etc.)

## `includeIncidents` (type: `boolean`):

Include recent incidents and maintenance

## `incidentDays` (type: `integer`):

How many days of incident history to include

## Actor input object example

```json
{
  "services": [
    "github",
    "vercel",
    "openai",
    "stripe"
  ],
  "includeComponents": true,
  "includeIncidents": true,
  "incidentDays": 7
}
```

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "services": [
        "github",
        "vercel",
        "openai",
        "stripe"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("apricot_blackberry/saas-status-monitor").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "services": [
        "github",
        "vercel",
        "openai",
        "stripe",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("apricot_blackberry/saas-status-monitor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "services": [
    "github",
    "vercel",
    "openai",
    "stripe"
  ]
}' |
apify call apricot_blackberry/saas-status-monitor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,apricot_blackberry/saas-status-monitor"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/1z7ZrxadprTHfZWxr/builds/9zrt38iFFM0QnJ24D/openapi.json