Machine Learning · head to head
AWS SageMaker vs Healthchecks

AWS SageMaker
Machine Learning
Build, train, and deploy machine learning models at scale
- From
- Free
- Rated
- -
The short version
- Each has a real cost: AWS SageMaker vendor lock-in to AWS ecosystem makes migration to other platforms difficult; Healthchecks free tier limited to 20 jobs, restricting scale for small teams
- They diverge on capability: AWS SageMaker covers Jupyter notebooks, Healthchecks covers Ping URL monitoring.
Where they differ
Only the attributes on which AWS SageMaker and Healthchecks actually diverge.
| Attribute | AWS SageMaker | Healthchecks |
|---|---|---|
| Pricing model | Unknown | Per-job monitoring with fixed tiers |
| Platforms | Web | Web, API |
| Category | Machine Learning | Logging |
| Founded | 2006 | 2015 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in AWS SageMaker
- Jupyter notebooks
- Built-in algorithms
- Automatic model tuning
- One-click deployment
- Model monitoring
- S3
- Lambda
- Step Functions
Only in Healthchecks
- Ping URL monitoring
- Customizable schedules
- Event logs
- Status badges
- Email alerts
- SMS and phone alerts
- Multiple integrations
What people use each for
The jobs each tool is most often brought in to do.
AWS SageMaker
- Machine learningnot Healthchecks
- Data analysisnot Healthchecks
- Model trainingnot Healthchecks
- Predictive analyticsnot Healthchecks
Healthchecks
- Monitoring cron jobs that run on schedulesnot AWS SageMaker
- Alerting teams when background tasks failnot AWS SageMaker
- Tracking Kubernetes CronJob execution healthnot AWS SageMaker
- Monitoring Jenkins builds and deploymentsnot AWS SageMaker
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
AWS SageMaker
- Vendor lock-in to AWS ecosystem makes migration to other platforms difficult
- Opaque pricing can lead to unexpected expenses like forgotten EBS volume charges
- Does not include native job scheduling, requiring Lambda or EventBridge integration
Healthchecks
- Free tier limited to 20 jobs, restricting scale for small teams
- Requires explicit ping integration into each job
- No workflow orchestration or job scheduling capabilities
- SMS and phone credits consumed separately on paid plans
- Limited to ping-based detection without deep job introspection
Pricing, plan by plan
AWS SageMaker
FreeNo published plan breakdown. See the AWS SageMaker review.
Healthchecks
Free- HobbyistFree
- Monitor 20 jobs
- 100 log entries per job
- Email alerts
- Supporter$5/month
- Monitor 20 jobs
- 100 log entries per job
- Support the service financially
- Business$20/month
- Monitor 100 jobs
- 1000 log entries per job
- 50 SMS and WhatsApp credits
- Business Plus$80/month
- Monitor 1000 jobs
- 1000 log entries per job
- 500 SMS and WhatsApp credits
Which should you pick?
Choose AWS SageMaker if
- You need jupyter notebooks.
- You want to start without paying.
- You also want built-in algorithms.
Choose Healthchecks if
- You need ping url monitoring.
- You want to start without paying.
- You work on Web, API.
- You also want customizable schedules.
Questions people ask
- Is AWS SageMaker or Healthchecks better?
- Neither clearly leads. AWS SageMaker starts at Free and Healthchecks at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, AWS SageMaker or Healthchecks?
- AWS SageMaker starts at Free and Healthchecks at Free.
- Does AWS SageMaker or Healthchecks run on more platforms?
- AWS SageMaker runs on Web. Healthchecks runs on Web, API.
- Can I use AWS SageMaker for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is AWS SageMaker best used for?
- AWS SageMaker is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Healthchecks is typically brought in for.
- What can AWS SageMaker do that Healthchecks cannot?
- AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. Healthchecks covers Ping URL monitoring, Customizable schedules, Event logs, Status badges.
Answered from the vendors’ own pages
AWS SageMaker: What is AWS SageMaker used for?
AWS SageMaker is a machine learning service for building, training, and deploying ML models at scale. It provides tools for data preparation, model training, inference endpoints, and performance optimization.
SourceHealthchecks: What does the free Hobbyist plan include?
The Hobbyist plan ($0/month) includes monitoring for 20 jobs, 100 log entries per job, and email alerts with no credit card required.
SourceAWS SageMaker: How is AWS SageMaker priced?
SageMaker uses pay-as-you-go pricing with no upfront costs or long-term commitments. Pricing starts at $0.04 per hour for basic notebook instances and scales based on instance type. ML Savings Plans offer up to 64% off with hourly spend commitments.
SourceHealthchecks: What is the difference between Business and Business Plus?
Business ($20/month) monitors 100 jobs with 50 SMS credits. Business Plus ($80/month) monitors 1000 jobs with 500 SMS credits and priority support.
SourceAWS SageMaker: Does AWS SageMaker have a free tier?
Yes, the free tier includes 250 hours of notebook usage, 50 hours of training, and 125 hours of hosting on ml.t3.medium instances during the first two months.
SourceHealthchecks: Do nonprofits and open-source projects get special pricing?
Yes, open-source projects and nonprofits receive the Business plan at no cost.
SourceRelated pages
More on AWS SageMaker
More on Healthchecks
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- AWS SageMaker vs Azure Monitor
- Healthchecks vs Google Vertex AI
- Healthchecks vs Azure Machine Learning
- Healthchecks vs DataRobot
- Healthchecks vs MLflow
- Healthchecks vs Snowflake
- Healthchecks vs TensorFlow
- Healthchecks vs Comet ML
- Healthchecks vs Jupyter
- Healthchecks vs LangChain
- Healthchecks vs Pinecone
- Healthchecks vs Python
- Healthchecks vs PyTorch
- Healthchecks vs scikit-learn
- Healthchecks vs Apache Spark MLlib
- Healthchecks vs Weaviate
- Healthchecks vs Weights & Biases
- Healthchecks vs Alteryx
- Healthchecks vs Anaconda
- Healthchecks vs Elastic Stack
- Healthchecks vs New Relic
- Healthchecks vs Datadog Logs
- Healthchecks vs Coralogix
- Healthchecks vs Grafana Loki
- Healthchecks vs incident.io
- Healthchecks vs Cronitor
- Healthchecks vs FireHydrant
- Healthchecks vs Openstatus
- Healthchecks vs Rootly
- Healthchecks vs Checkly
- Healthchecks vs CloudWatch
- Healthchecks vs Dynatrace
- Healthchecks vs InfluxDB
- Healthchecks vs Airbrake
- Healthchecks vs AppDynamics
- Healthchecks vs Axiom
- Healthchecks vs Azure Monitor

