graph LR u1(User) u2(User) u3(User) b1(Browser) b2(Browser) b3(Browser) connect(Connect) qmd(Quarto) fastapi(FastAPI) shiny(Shiny App) streamlit(Streamlit App) u1---b1 u2---b2 u3---b3 b1---connect b2---connect b3---connect subgraph server[Linux Server] connect---qmd connect---fastapi connect---shiny connect---streamlit end classDef server fill:#FAEEE9,stroke:#ab4d26 classDef product fill:#447099,stroke:#213D4F,color:#F2F2F2 classDef session fill:#7494B1,color:#F2F2F2,stroke:#213D4F classDef element fill:#C2C2C4,stroke:#213D4F class server server class connect product class qmd,fastapi,shiny,streamlit session class u1,u2,u3,b1,b2,b3 element
Generic Architectures for Posit Connect
The architectures below represent general architectures for Posit Connect, providing a mental model for different deployment options and the requirements to support each variation.
Specific reference architectures organized by target environment are also detailed within this chapter of the Administration Guide, discoverable using the left navigation pane.
Target environments
Posit Connect can be deployed on-premises or within a cloud environment.
Connect on a Single Server
In this configuration, Connect is installed on a single Linux server and enables:
- Multiple publishers and viewers to access Connect via a web browser
Generic architecture
The example diagram below shows four sample content types deployed to Connect. The content data bundles are stored on the Linux server, and the content processes run on the Linux server.
Connect as a load-balanced cluster
In this configuration, Connect is installed on two or more Linux servers and enables:
- Multiple publishers and viewers to access Connect via a web browser
- Load balancing to provide additional computational resources for applications and reports
- High availability to provide redundancy
Requirements
- Application data must be stored on an external shared file server (typically an NFS server)
- Application metadata must be stored on an external PostgreSQL database server
Generic architecture
The example diagram below shows sample content types deployed to Connect. The content data bundles are stored on Shared Storage, metadata is stored in a Postgres database. The content processes run on the Linux servers and are distributed according to the Load Balancer rules.
flowchart LR
u1(User)
u2(User)
u3(User)
b1(Browser)
b2(Browser)
b3(Browser)
lb(Load Balancer)
connect1(Connect)
connect2(Connect)
rmd(R Markdown)
jupyter(Jupyter Notebook)
qmd(Quarto)
plumber(Plumber API)
fastapi(FastAPI)
shiny(Shiny App)
streamlit(Streamlit App)
dash(Dash App)
nfs(Shared Storage)
pg(Postgres)
u1---b1
u2---b2
u3---b3
b1---lb
b2---lb
b3---lb
subgraph server1 [Linux Server]
direction LR
connect1---rmd
connect1---jupyter
connect1---fastapi
connect1---dash
end
subgraph server2 [Linux Server]
direction LR
connect2---qmd
connect2---plumber
connect2---streamlit
connect2---shiny
end
lb---server1
lb---server2
server1-.-nfs
server2-.-nfs
server1-.-pg
server2-.-pg
classDef server fill:#FAEEE9,stroke:#ab4d26
classDef product fill:#447099,stroke:#213D4F,color:#F2F2F2
classDef session fill:#7494B1,color:#F2F2F2,stroke:#213D4F
classDef element fill:#C2C2C4,stroke:#213D4F
classDef req fill:#72994E,stroke:#1F4F4F
class server1,server2 server
class connect1,connect2 product
class rmd,jupyter,qmd,plumber,fastapi,streamlit,dash,shiny session
class u1,u2,u3,b1,b2,b3,lb element
class pg,nfs req
Connect on Kubernetes
In this configuration, Connect is installed in a Kubernetes cluster using a Posit-maintained Helm chart.
This enables:
- Multiple publishers and viewers to access Connect via a web browser
- Replica redundancy for multiple instances of the Connect service Pod
- Execution of Python, R, and Quarto content in an isolated Kubernetes container external to Connect (instead of a local process)
- Admins to define and customize the set of base images available for creating content build and execution containers
- Publishers to target a specific base image for their content, or allow Connect to choose a best fit by comparing the available runtime version components
Requirements
- Application data must be stored on a shared file server (can be inside or outside Kubernetes)
- Application metadata must be stored on a PostgreSQL database server (can be inside or outside Kubernetes)
Generic architecture
The example diagram below shows sample content types deployed to Connect. The content data bundles are stored on Shared Storage, metadata is stored in a Postgres database. The content processes run as isolated pods on the Kubernetes cluster using either default or targeted base images.
flowchart LR u1(User) u2(User) u3(User) b1(Browser) b2(Browser) b3(Browser) connect(Connect <br/> Launcher) ingress(Ingress Controller<br/>nginx/nginx-ingress) qmd(Quarto<br/>ghcr.io/example/content-base:r-40-py-3.11) flask(Flask App<br/>ghcr.io/example/content-base:py-3.10) shiny(Shiny App<br/>ghcr.io/example/content-base:r-4.4) dash(Dash App<br/>ghcr.io/example/content-base:py-3.11) pg(Postgres) nfs(Shared Files) u1---b1 u2---b2 u3---b3 b1---ingress b2---ingress b3---ingress subgraph k8s [Kubernetes Cluster] ingress---connect connect---qmd connect---flask connect---shiny connect---dash end k8s-..-nfs k8s-..-pg classDef server fill:#FAEEE9,stroke:#ab4d26 classDef product fill:#447099,stroke:#213D4F,color:#F2F2F2 classDef session fill:#7494B1,color:#F2F2F2,stroke:#213D4F classDef element fill:#C2C2C4,stroke:#213D4F classDef req fill:#72994E,stroke:#1F4F4F,color:#F2F2F2 class k8s server class connect product class ingress,qmd,flask,shiny,dash session class u1,u2,u3,b1,b2,b3,lb element class pg,nfs req