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Cloud · head to head

Anyscale vs Envoy

Anyscale logo

Anyscale

Cloud

Platform for scaling AI and data workloads on Ray, built by Ray's creators

From
Free
Free plan
Yes
Visit AnyscaleFull review
Envoy logo

Envoy

Developer Tools

A high-performance L7 proxy written in C++ that is configured by an API rather than a config file, and is usually deployed under a control plane.

From
Free
Free plan
Yes
Visit EnvoyFull review

The short version

  • Envoy is free; Anyscale starts at $0.0135/mo.
  • Only Anyscale lists distributed model training; only Envoy lists xDS dynamic configuration.
  • Where Anyscale falls short: pricing for high-end H100/B200-class GPUs is not published and requires contacting sales.
  • Prices and features on this page were last checked on 13 November 2026.

Where they differ

Only the attributes on which Anyscale and Envoy actually diverge.

Attributes where Anyscale and Envoy differ
AttributeAnyscaleEnvoy
Pricing modelUsage-basedOpen-source
PlatformsWeb, APIWeb
CategoryCloudDeveloper Tools

Identical on both: starting price (Free), free tier (Yes).

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 Anyscale

  • Distributed model training
  • Multimodal data curation
  • Batch embedding generation
  • Multi-cloud orchestration
  • Governance and security
  • Observability
  • Bring-your-own-cloud deployment
  • Elastic GPU allocation

Only in Envoy

  • xDS dynamic configuration
  • Protocol breadth
  • Filter chain architecture
  • Observability by default
  • Outlier detection
  • Traffic shaping
  • mTLS termination and origination
  • Hot restart

What people use each for

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

Anyscale

  • Training large models on distributed GPU clustersnot Envoy
  • Running batch inference and embedding jobsnot Envoy
  • Preparing multimodal datasets at scalenot Envoy
  • Post-training LLMs with reinforcement learning frameworksnot Envoy

Envoy

  • Acting as the data plane under a service mesh or Gateway API implementation, which is how the overwhelming majority of deployments use itnot Anyscale
  • An edge or API gateway that needs per-route retry budgets, circuit breaking and outlier detection rather than round-robin proxyingnot Anyscale
  • Migrating traffic between service versions or between a monolith and its replacement, using weighted splits and shadow trafficnot Anyscale
  • Standardising observability across a polyglot estate, so that latency, error rates and tracing look the same regardless of the language a service is written innot Anyscale

Where each one falls short

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

Anyscale

  • Pricing for high-end H100/B200-class GPUs is not published and requires contacting sales
  • Built around Ray, so teams not already using Ray face a steeper adoption curve than single-purpose inference APIs
  • No published fixed-fee subscription tier; all listed pricing is usage-based on-demand compute

Envoy

  • The configuration surface is very large and hand-written bootstrap YAML runs to hundreds of lines for routing that Nginx expresses in twenty, which is why nearly every production deployment sits under a control plane and inherits that control plane's constraints as well
  • xDS is the real API and it is not stable in the comfortable sense; the v2 API set was removed outright, resource types continue to be deprecated, and your control plane and Envoy binaries have to be upgraded roughly in step or the proxies stop accepting configuration
  • Extending it properly means writing a C++ filter and building and maintaining your own Envoy binary; the alternatives are Lua, which adds per-request overhead, and proxy-wasm, whose ABI has remained effectively experimental for years with a real performance cost
  • At sidecar density the per-proxy memory and CPU footprint is a measurable share of cluster capacity, since thousands of workloads each carry a full proxy, and this is precisely the cost that has pushed mesh projects towards node-level or ambient architectures
  • There is no single vendor selling support for Envoy itself; you get the community plus control-plane vendors such as Solo.io and Tetrate, so an Envoy-level production bug is your own engineers in a C++ codebase unless a support contract happens to cover it
  • Diagnosing why a request got a particular response involves reading config dumps, the stats endpoint and the RESPONSE_FLAGS codes in access logs rather than a readable error, which is a specific skill you must hire or spend months growing

Pricing, plan by plan

Anyscale

Free
  • Pay-as-you-goOn request
    • CPU only from $0.0135/hr
    • NVIDIA T4 $0.5682/hr
    • NVIDIA L4 $0.9542/hr
  • Committed contractOn request
    • Volume discounts
    • Use of existing GPU reservations

Envoy

Free

No published plan breakdown. See the Envoy review.

Which should you pick?

Choose Anyscale if

  • You need distributed model training.
  • You want to start without paying.
  • You work on Web, API.
  • You also want multimodal data curation.
Anyscale review

Choose Envoy if

  • You need xds dynamic configuration.
  • You want to start without paying.
  • You also want protocol breadth.
Envoy review

Questions people ask

Is Anyscale or Envoy better?
Neither clearly leads. Anyscale starts at Free and Envoy at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Anyscale or Envoy?
Anyscale starts at Free and Envoy at Free.
Does Anyscale or Envoy run on more platforms?
Anyscale runs on Web, API. Envoy runs on Web.
Can I use Anyscale for free?
Both have a free tier, so you can try either at no cost before committing.
What is Anyscale best used for?
Anyscale is most often used for training large models on distributed gpu clusters, running batch inference and embedding jobs, preparing multimodal datasets at scale, post-training llms with reinforcement learning frameworks. Of those, training large models on distributed gpu clusters and running batch inference and embedding jobs are not what Envoy is typically brought in for.
What can Anyscale do that Envoy cannot?
Anyscale covers Distributed model training, Multimodal data curation, Batch embedding generation, Multi-cloud orchestration. Envoy covers xDS dynamic configuration, Protocol breadth, Filter chain architecture, Observability by default.

Answered from the vendors’ own pages

Anyscale: How much does Anyscale cost?

Anyscale bills on a pay-as-you-go basis: CPU compute starts at $0.0135/hr, NVIDIA T4 at $0.5682/hr, and NVIDIA A100 at $4.9591/hr, with committed contracts offering volume discounts for larger workloads.

Source
Envoy: Should I run Envoy on its own, or under a control plane?

Almost always under one. Directly authoring xDS or static bootstrap configuration is viable for a handful of routes and becomes unmanageable beyond that. Envoy Gateway, Istio, Contour, Gloo and Consul all exist to generate that configuration for you.

Anyscale: Is there a free trial or credit?

New users receive $100 in Anyscale credits to explore the platform, which can be applied toward starter templates and on-demand compute usage.

Source
Envoy: How does it compare with Nginx or HAProxy?

Envoy is dynamically configured over an API and instrumented far more heavily; Nginx and HAProxy are faster to configure and lighter for straightforward reverse proxying. If you never need to change routing without a reload, Envoy is more machinery than the problem requires.

Anyscale: How is usage billed?

Hosted usage is billed hourly per compute instance type and invoiced monthly by credit card; bring-your-own-cloud usage is invoiced through Anyscale or the customer's cloud marketplace account.

Source
Envoy: What does it cost?

Nothing to licence; it is Apache 2.0 and there is no paid edition. The cost is engineering time and, for most organisations, a commercial control plane or cloud service that packages it.

Anyscale: What support is included?

Hosted plans include business-hours support with up to 5 case submissions, while bring-your-own-cloud deployments get 24x7 enterprise SLAs and unlimited case submissions.

Source
Envoy: Can I write extensions without C++?

You can write Lua filters or proxy-wasm modules in Rust, Go, C++ or AssemblyScript. Both carry per-request overhead compared with a native filter, and the Wasm path has been slower to stabilise than the project originally projected.

Envoy: Is it a CNCF project?

Yes, it is a graduated CNCF project licensed under Apache 2.0, which means the trademark and governance sit with the foundation rather than with Lyft or any vendor.

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