Managed Dify Hosting — production-ready from $15 a month
LLM app development platform. Deployed on your own dedicated instance in AWS, Azure, or GCP, kept patched, backed up, and monitored by ManageStacks — standard Dify, no lock-in.
Dify on ManageStacks is the open-source LLM application platform deployed to your own AWS, Azure, or GCP region — priced flat at $29 per instance per month regardless of user or workflow count, with visual workflow builder, RAG pipeline, agent tooling, prompt management, and API-first design. Materially cheaper than LangSmith or Vercel AI SDK Cloud for team-based AI app development, and prompts + RAG data stay in your cloud. Pairs with Ollama, Qdrant, and LiteLLM (also on ManageStacks) for a fully self-hosted GenAI stack.
What does Dify do, and why do teams deploy it?
Dify is an open-source LLM application platform that combines workflow orchestration, RAG pipelines, AI agent capabilities, prompt management, and model routing into one product. It's what you reach for when your team is building 5-50 LLM-powered features and doesn't want to hand-roll LangChain glue for every one.
Dify supports every major LLM provider — OpenAI, Anthropic, Google, Cohere, Azure OpenAI, AWS Bedrock — and every major open-source model via Ollama, vLLM, or Hugging Face TGI. Its visual workflow builder lets non-engineers assemble chat apps, agents, and RAG pipelines; developers get an API-first design with SDKs for Python and Node.
On ManageStacks, Dify pairs naturally with Ollama (local models), Qdrant (vector store), and LiteLLM (unified LLM proxy) — all in the same account, same region, no cross-cloud data flow. Self-hosted end-to-end GenAI without prompts, embeddings, or user queries leaving your infrastructure.
- Visual AI workflow builder with drag-and-drop nodes
- RAG pipeline with vector database integration (Qdrant, pgvector, more)
- Model routing across OpenAI, Anthropic, Google, Bedrock, Ollama, vLLM
- Agent framework with function calling and tool integration
- Prompt management with versioning and A/B testing
- Dataset management for RAG knowledge bases
LLM app development platform
What does managed Dify hosting cost?
Flat per-app pricing, in your chosen AWS, Azure, or GCP region. No per-user pricing — a busy deployment costs the same as a quiet one.
Starter
Staging and internal tools. Dedicated instance, TLS, daily backups, managed upgrades.
Standard
Production workloads. Adds monitoring, staging environment, region choice, priority support.
Business
High-traffic and compliance workloads. Adds a high-availability replica and same-day support.
24×7 SRE retainer
Round-the-clock on-call across every hosted application, for teams that need a pager answered at 3am.
Self-hosting Dify vs managed — what does it really cost?
The software is free. The engineer-hours are not.
Running it yourself
- Write LangChain glue code for every workflow; version and test manually
- Wire in vector DB, embedding calls, prompt versioning, and cost tracking separately
- Build UI for non-engineers to iterate on prompts + workflows — or don't
- Track LLM API spend across providers with a spreadsheet
- Deploy each workflow separately as a service
On ManageStacks
- Subscribe through your AWS, Azure, or GCP marketplace
- Dify comes up with Postgres, Redis, vector-DB integration, and workflow UI
- Non-engineers build workflows visually; developers consume via REST API
- Pair with Ollama (local LLMs), Qdrant (vector DB), LiteLLM (provider proxy) on same account
- Rolling version upgrades handled by us
Dify on ManageStacks vs the alternatives
How Dify on ManageStacks compares to the vendor-hosted LLM development platforms and hand-rolled LangChain.
| Dify on ManageStacksUs | LangSmith | Vercel AI SDK Cloud | Hand-rolled LangChain / LlamaIndex | |
|---|---|---|---|---|
| Deployment | Managed on your AWS, Azure, or GCP | Vendor-hosted | Vendor-hosted | You deploy + operate |
| Data residency | Your cloud region | Vendor infrastructure | Vendor infrastructure | Your cloud region |
| Pricing basis | Flat per instance | Per team + per trace | Per token routed | Your compute cost |
| UI for non-engineers | Yes (visual builder) | Partial (prompt playground) | No (code-first) | No (code-only) |
| Open source | Yes (Apache 2.0) | No (proprietary) | SDK is open (MIT) | Yes |
| Model choice | Any (OpenAI, Anthropic, Ollama, more) | Any | Any | Any |
Provisioning, upgrades, backups and monitoring on your team’s plate.
What does running Dify yourself involve?
ManageStacks deploys Dify with Postgres, Redis, and a vector database backend (Qdrant on the same account for the natural pairing). We handle scaling, dataset storage, and version upgrades. Combine with Ollama for local LLMs and LiteLLM for provider routing to build production GenAI apps entirely within your cloud region.
Dify key numbers
How long from subscribing to a live instance?
Subscribe
Subscribe to ManageStacks through your AWS, Azure, or GCP marketplace.
Provision
Dify spins up with Postgres, Redis, and vector-DB integration — typically 3-5 minutes.
Configure models
Add API keys for OpenAI, Anthropic, or point at your Ollama endpoint on the same account. Configure LiteLLM for unified routing.
Build + deploy apps
Create workflows visually or via YAML. Upload RAG datasets. Consume as REST endpoints from your product.
When is self-hosting Dify the right answer instead?
“Managed hosting is not always the correct call.”
Self-host when a platform team already runs the infrastructure and on-call rotation to operate Dify at genuinely low marginal cost. Self-host when compliance requires an air-gapped or on-premises deployment that no hosted option can satisfy. And self-host when the deployment depends on heavy customisation with a fast internal build-deploy loop, because an internal release process will beat any managed change process.
For everyone else — teams whose engineers have better things to do than shepherd upgrades — managed hosting is cheaper than the hours it replaces.
Which cloud should Dify run on — AWS, Azure or GCP?
For most workloads, the choice of cloud matters less than proximity: run Dify in the same cloud and region as the applications and data it talks to, because every request between them adds a round trip. The underlying compute performs equivalently across AWS, Azure, and GCP.
In practice, an existing cloud footprint decides it. All plans support all three clouds, and moving regions later is a scheduled migration, not a rebuild.
Deepest managed-service catalog, default when there's no existing footprint
Best fit for teams already on Microsoft 365 or Entra ID
Strongest for data/analytics-adjacent workloads
Every plan supports AWS, Azure, and GCP — region choice included.
Common questions about Dify on ManageStacks
How does this compare to LangSmith or Vercel AI SDK?
LangSmith is LangChain's hosted observability + prompt-management platform, priced per team + per trace. Vercel AI SDK is a code-first LLM abstraction (not a UI platform). ManageStacks Dify is flat $29 per instance and gives you the full UI platform (workflow builder, RAG, agents, prompt mgmt) — closer to LangSmith + LangGraph combined. LangSmith wins on deep LangChain integration and vendor-managed traces; Dify wins on flat cost, self-hosting, and non-engineer accessibility.
Can I use both cloud LLMs and self-hosted models with Dify?
Yes. Dify supports OpenAI, Anthropic, Google, Azure OpenAI, AWS Bedrock, Cohere, and any Ollama/vLLM/TGI endpoint. Route different steps in a workflow to different models. Pair with LiteLLM (on ManageStacks) for unified auth, rate limiting, and cost tracking across providers.
How does Dify handle RAG?
Upload documents (PDF, DOCX, Markdown, text) or crawl URLs; Dify chunks, embeds, and stores in a vector database (Qdrant on ManageStacks is the natural pairing). At query time, Dify retrieves relevant chunks and passes them to the LLM. Advanced re-ranking, hybrid search (BM25 + vector), and metadata filtering are all supported.
Is Dify safe for production customer-facing AI?
Yes. Dify apps expose stable REST endpoints; your product consumes them like any API. Observability shows token usage, latency, and quality per workflow. Rate limiting, per-workflow quotas, and cost tracking prevent runaway spend on cloud LLM APIs.
Does ManageStacks handle Dify version upgrades?
Yes. Dify ships releases frequently; we test each one against your workflows before rolling forward. Database migrations handled.
What if I want to move off Dify later?
Export workflow definitions as JSON, export datasets as text/documents, export prompts as templates. Rebuild in LangChain, LlamaIndex, or roll your own. Dify is Apache-2.0. Migration off is a supported operation.
Run Dify without carrying the pager
Subscribe through your AWS, Azure, or GCP marketplace. We handle provisioning, SSL, monitoring, backups, updates, and security. From $15/mo.