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Machine Learning · head to head

Google Vertex AI vs Traceloop

Google Vertex AI logo

Google Vertex AI

Machine Learning

Unified ML platform to build, deploy, and scale AI models

From
On request
Rated
-
Full reviewWebsite
Traceloop logo

Traceloop

Logging

LLM reliability platform with open-source observability and evaluation

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only Traceloop has a free tier, so it costs nothing to try first.
  • Each has a real cost: Google Vertex AI vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult; Traceloop free tier limited to 50k spans per month and 24-hour retention, restricting production use
  • They diverge on capability: Google Vertex AI covers AutoML, Traceloop covers Open-source SDK (OpenLLMetry).

Where they differ

Only the attributes on which Google Vertex AI and Traceloop actually diverge.

Attributes where Google Vertex AI and Traceloop differ
AttributeGoogle Vertex AITraceloop
Starting priceOn requestFree
Pricing modelUnknownFreemium with pay-as-you-go enterprise option
Free tierNoYes
PlatformsCloud, WebCloud, On-premises, Air-gapped, Python, TypeScript, Go, Ruby
CategoryMachine LearningLogging
Founded2008Unknown

Identical on both: 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 Google Vertex AI

  • AutoML
  • Custom training
  • Feature Store
  • Model monitoring
  • Prediction serving
  • BigQuery
  • Cloud Storage
  • TensorFlow

Only in Traceloop

  • Open-source SDK (OpenLLMetry)
  • Multi-provider support
  • Observability platform integration
  • Framework support
  • Monitoring dashboard
  • Evaluation system
  • Deployment flexibility

What people use each for

The jobs each tool is most often brought in to do.

Google Vertex AI

  • Machine learningnot Traceloop
  • Data analysisnot Traceloop
  • Model trainingnot Traceloop
  • Predictive analyticsnot Traceloop

Traceloop

  • Monitoring LLM application performance in productionnot Google Vertex AI
  • Instrumenting LLM apps with minimal code overheadnot Google Vertex AI
  • Continuous evaluation and quality scoring of LLM outputsnot Google Vertex AI
  • Debugging LLM application issues with full trace visibilitynot Google Vertex AI
  • Integrating observability data into existing monitoring stacksnot Google Vertex AI

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Google Vertex AI

  • Vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult
  • Requires familiarity with Google Cloud Platform infrastructure and concepts
  • Cost can escalate quickly with large training and inference workloads

Traceloop

  • Free tier limited to 50k spans per month and 24-hour retention, restricting production use
  • Company acquisition by ServiceNow creates uncertainty about future roadmap
  • Requires integration with separate observability platforms for visualization
  • Less feature-rich than dedicated LLM evaluation platforms

Pricing, plan by plan

Google Vertex AI

On request

No published plan breakdown. See the Google Vertex AI review.

Traceloop

Free
  • FreeFree
    • 50,000 spans per month
    • Up to 5 seats
    • 24-hour data retention
  • Enterprise$undefined/custom
    • Unlimited spans per month
    • Unlimited seats
    • Custom data retention

Which should you pick?

Choose Google Vertex AI if

  • You need automl.
  • You work on Cloud, Web.
  • You also want custom training.
Google Vertex AI review

Choose Traceloop if

  • You need open-source sdk (openllmetry).
  • You want to start without paying.
  • You work on Cloud, On-premises, Air-gapped, Python, TypeScript, Go, Ruby.
  • You also want multi-provider support.
Traceloop review

Questions people ask

Is Google Vertex AI or Traceloop better?
Neither clearly leads. Google Vertex AI starts at On request and Traceloop at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Google Vertex AI or Traceloop?
Traceloop has a free tier; the other does not. Paid plans start at On request for Google Vertex AI and Free for Traceloop.
Does Google Vertex AI or Traceloop run on more platforms?
Google Vertex AI runs on Cloud, Web. Traceloop runs on Cloud, On-premises, Air-gapped, Python, TypeScript, Go, Ruby.
Can I use Traceloop for free?
Yes. Traceloop has a free tier, so you can try it without paying. Google Vertex AI starts at On request.
What is Google Vertex AI best used for?
Google Vertex AI is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Traceloop is typically brought in for.
What can Google Vertex AI do that Traceloop cannot?
Google Vertex AI covers AutoML, Custom training, Feature Store, Model monitoring. Traceloop covers Open-source SDK (OpenLLMetry), Multi-provider support, Observability platform integration, Framework support.

Answered from the vendors’ own pages

Google Vertex AI: What is the pricing model for Google Vertex AI?

Vertex AI uses a pay-as-you-go model with no upfront costs or lock-in fees. Costs vary by service: training is billed by compute resources and time (30-second increments), online predictions by machine type per hour, and batch predictions by compute time or per-record for specific AutoML types.

Source
Traceloop: Is OpenLLMetry open-source?

Yes, OpenLLMetry is Traceloop's open-source SDK built on OpenTelemetry standards. It allows teams to instrument LLM applications with just 2 lines of code and send data to 25+ observability platforms.

Source
Google Vertex AI: What types of data can Vertex AI handle?

Vertex AI supports image, video, text, and tabular data types with tools for uploading, storing, and managing large datasets.

Source
Traceloop: What is the impact of ServiceNow acquisition?

Traceloop is joining ServiceNow, representing a strategic acquisition that will broaden enterprise adoption and integration capabilities. Current operations continue with free and enterprise options available.

Source
Google Vertex AI: Does Vertex AI support custom model training?

Yes. Vertex AI supports both AutoML for automated machine learning and custom training code in Python, R, and other languages.

Source
Traceloop: How many LLM providers and frameworks does Traceloop support?

Traceloop supports 20+ LLM providers including OpenAI and Anthropic, and integrates with frameworks like LangChain and LlamaIndex. It can send data to 25+ observability platforms.

Source
Google Vertex AI: What deployment options are available in Vertex AI?

Vertex AI supports online predictions for real-time use cases and batch predictions for large-scale processing.

Source
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