For Developers

Who Is SEER For? Data Engineers, DevOps, and Indie Developers

The best monitoring tool for cron jobs, Python scripts, ETL pipeline monitoring, and Airflow heartbeat tracking. Monitor your automation reliability—before your users notice failures.

Free forever plan available

Monitor ETL Pipelines and Airflow DAGs with Ease

Whether you're managing ETL pipelines, running cron jobs, or monitoring Python scripts, SEER keeps your automation reliable with uptime monitoring for scripts and pipeline reliability monitoring.

Data Engineers
Monitor ETL jobs, DAGs, Airflow, Dagster, dbt, and batch processing pipelines

Common Pain Points

  • • Pipelines fail silently without notification
  • • Inconsistent data quality from failed transformations
  • • SLA breaches go undetected until too late
  • • Downstream systems fail because upstream jobs didn't run

How SEER Solves This

  • • Heartbeat monitoring ensures jobs run on schedule
  • • SLA tracking with configurable thresholds
  • • Instant Slack alerts when pipelines fail or run late
  • • Track execution time trends to catch performance degradation

Real-World Examples

1

Daily ETL Pipeline: Monitor a nightly data ingestion job that must complete before 6 AM for morning reports

2

Airflow DAGs: Track multi-step workflows and get alerted at the exact step where failures occur

3

dbt Transformations: Monitor model runs and catch data quality issues before they propagate downstream

data_pipeline.py
from seerpy import Seer

seer = Seer(api_key="your_api_key")
pipeline = seer.start_job("daily-etl")

try:
    # Your ETL logic
    extract_data()
    transform_data()
    load_to_warehouse()
    
    pipeline.success(metadata={
        "rows_processed": 150000,
        "runtime_seconds": 420
    })
except Exception as e:
    pipeline.fail(error=str(e))
Indie Hackers & Solo Developers
Monitor background scripts, web scrapers, and automation workflows

Common Pain Points

  • • Cron jobs silently break and you don't know for weeks
  • • No time to build custom monitoring infrastructure
  • • Checking logs manually is tedious and unreliable
  • • Need to sesuatu simple that "just works"

How SEER Solves This

  • • 2-minute setup with lightweight API
  • • No infrastructure required—just add one line of code
  • • Free forever plan for small projects
  • • Email and Slack alerts keep you informed

Real-World Examples

1

Web Scraper: Monitor your daily product price scraper to ensure data stays fresh for your comparison site

2

Newsletter Automation: Track your weekly newsletter generation script and know instantly if it fails

3

Database Backup: Get alerted if your nightly backup script doesn't run successfully

scraper.py
import requests

# Just add this one line at the end of your script
requests.post(
    "https://api.ansrstudio.com/heartbeat",
    headers={"Authorization": "your_api_key"},
    json={"pipeline_name": "price-scraper"}
)

# That's it! SEER now monitors your script.
Backend Engineers & DevOps
Monitor scheduled tasks, queue workers, serverless functions, and microservices

Common Pain Points

  • • Uptime monitors only check if servers are up, not if jobs run
  • • Background workers fail silently in distributed systems
  • • Lambda/Cloud Functions timeout without proper visibility
  • • Need to track "did the job actually execute?" not just server health

How SEER Solves This

  • • Monitor actual job execution, not just infrastructure
  • • Track function invocations and completion status
  • • Integration with your existing alerting (PagerDuty, Slack, webhooks)
  • • Performance metrics to catch degradation early

Real-World Examples

1

Queue Workers: Monitor SQS/RabbitMQ consumers and get alerted when message processing falls behind

2

Serverless Functions: Track AWS Lambda or Cloud Functions to ensure they complete successfully

3

Scheduled Cleanup: Monitor database cleanup jobs, log rotation, and maintenance tasks

lambda_handler.py
from seerpy import Seer

def lambda_handler(event, context):
    seer = Seer(api_key=os.environ["SEER_API_KEY"])
    job = seer.start_job("image-processor")
    
    try:
        process_images(event['batch_id'])
        job.success()
    except Exception as e:
        job.fail(error=str(e))
        raise
Small Teams & Startups
Coordinate reliability for multiple jobs and services across your growing platform

Common Pain Points

  • • No unified visibility across all automated jobs
  • • Logs scattered across different services
  • • Team members don't know which jobs are critical
  • • On-call rotation needs centralized alerting

How SEER Solves This

  • • Centralized dashboard for all team monitors
  • • Team-based API keys for better organization
  • • Scheduled reports sent to Slack channels
  • • Role-based access control (coming soon)

Real-World Examples

1

Multi-Service Platform: Monitor 20+ background jobs across microservices from one dashboard

2

Team Coordination: Send nightly summary reports to your #engineering Slack channel

3

On-Call Rotation: Route critical alerts to PagerDuty while sending non-urgent issues to Slack

Team Benefits

  • Shared visibility across engineering team
  • Multiple API keys for different services
  • Historical data for postmortems and analysis
  • Affordable pricing that scales with your growth

Best Monitoring Tool for Cron Jobs and Python Scripts

From Python scripts to cloud functions—if it runs on a schedule, SEER can monitor it. Unlike BetterUptime, SEER lets you monitor ETL pipelines and scheduled tasks directly. Compared to Cronitor, SEER focuses on script-level reliability instead of just uptime.

Python Scripts

Monitor any Python automation or data processing script

Cron Jobs

Track scheduled tasks and system maintenance jobs

ETL Pipelines

Monitor data extraction, transformation, and loading workflows

Airflow / Dagster

Track DAGs and orchestration workflows

Lambda / Cloud Functions

Monitor serverless function execution

Microservices

Track background workers and service health

Database Jobs

Monitor cleanup, vacuum, and maintenance tasks

AI Agents

Track scheduled AI workflows and batch inference jobs

Supabase Cron

Monitor Supabase scheduled database functions

Web Scrapers

Ensure your data collection scripts run reliably

Batch Notifications

Track email, SMS, and notification jobs

API Heartbeats

Monitor critical API endpoints and webhooks

Monitor with a Single POST Call

No YAML configuration. No complex setup. Just add SEER to your script and start monitoring in minutes. Perfect for devops monitoring for cron jobs and scheduled task tracking.

curl -X POST https://api.ansrstudio.com/heartbeat \
  -H "Authorization: your_api_key" \
  -H "Content-Type: application/json" \
  -d '{"pipeline_name": "my-job"}'

Why SEER is the Best Alternative to Cronitor and BetterUptime

SEER provides comprehensive pipeline reliability monitoring that goes beyond simple uptime checks.

SEER vs. Cronitor

Cronitor focuses on HTTP endpoint monitoring and basic heartbeat checks.

SEER provides script-level reliability monitoring with detailed execution metadata, performance tracking, and comprehensive error detection for ETL pipelines, Airflow DAGs, and Python scripts.

SEER advantages:

  • • Track execution time trends and performance degradation
  • • Monitor data pipeline steps individually
  • • Capture custom metadata from your jobs
  • • Free forever plan with generous limits
SEER vs. BetterUptime

BetterUptime excels at monitoring website uptime and API endpoints.

SEER is purpose-built for scheduled tasks, background jobs, and data pipelines. Monitor cron jobs, Lambda functions, and batch processing jobs that BetterUptime wasn't designed for.

SEER advantages:

  • • Designed specifically for script and pipeline monitoring
  • • Track job success/failure, not just server status
  • • Monitor Airflow, Dagster, dbt workflows
  • • Developer-first API with Python SDK

Real Use Case: Monitoring a Daily Sales ETL Pipeline

A SaaS company runs a critical ETL pipeline every night at 2 AM to process the day's sales data. The pipeline extracts data from their production database, transforms it for analytics, and loads it into their data warehouse. Their morning dashboard depends on this completing by 6 AM.

STEP 1: EXTRACT

Extract 500K records from Postgres

✓ Completed in 8 min
STEP 2: TRANSFORM

Clean, dedupe, and aggregate data

✓ Completed in 12 min
STEP 3: LOAD

Load into Snowflake warehouse

✓ Completed in 5 min

With SEER, they get instant Slack alerts if any step fails or takes longer than expected. They can track execution time trends to catch performance issues before they become critical.

Frequently Asked Questions

Common questions about SEER monitoring for cron jobs, ETL pipelines, and scheduled tasks

No more silent failures.
No more guessing.

SEER gives you instant visibility into every job that matters. Start monitoring in under 5 minutes with our free forever plan.

14-day free trial on paid plans • Cancel anytime

2 min
Setup Time
99.9%
Uptime SLA
100/min
API Rate Limit
Free
Forever Plan