Using Workbench on a single server
In this configuration, Workbench is installed on a single Linux server and enables:
- Access to RStudio, Jupyter Notebook, JupyterLab and VS Code development IDEs
- Multiple concurrent sessions per user
- Use of multiple versions of R and Python
graph LR
u1(User)
u2(User)
u3(User)
b1(Browser)
b2(Browser)
b3(Browser)
workbench(Workbench)
session(Session)
jupyter(Jupyter Session)
vscode(VS Code Session)
job(Workbench Job)
u1---b1
u2---b2
u3---b3
b1---workbench
b2---workbench
b3---workbench
subgraph server[Linux Server]
workbench---session
workbench---jupyter
workbench---vscode
workbench---job
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 workbench product
class session,jupyter,vscode,job session
class u1,u2,u3,b1,b2,b3 element
Using Workbench as a cluster
In this configuration, Workbench is installed on two or more Linux servers and enables:
- Load balancing to provide additional computational resources to end users
- High availability to provide redundancy
Requirements to support this architecture:
- Users’ home directories must be stored on an external shared file server (typically an NFS server)
- Session metadata must be stored on an external PostgreSQL database server
The example diagrams below show cluster architectures with and without an external load balancer.
External Load Balancer
flowchart LR
u1(User)
u2(User)
u3(User)
b1(Browser)
b2(Browser)
b3(Browser)
workbench1(Workbench)
workbench2(Workbench)
session(RStudio Session)
jupyter(Jupyter Session)
vscode(VS Code Session)
job(Workbench Job)
lb(Load Balancer)
nfs(Shared Storage)
pg(Postgres)
u1---b1
u2---b2
u3---b3
b1---lb
b2---lb
b3---lb
lb---workbench1
lb---workbench2
server1-.-nfs
server2-.-nfs
server1-.-pg
server2-.-pg
subgraph server1 [Linux Server]
workbench1---jupyter
workbench1---job
end
subgraph server2 [Linux Server]
workbench2---session
workbench2---vscode
end
workbench1-.-workbench2
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 workbench1,workbench2 product
class session,jupyter,vscode,job session
class u1,u2,u3,b1,b2,b3,lb element
class pg,nfs req
Single Node Routing
flowchart LR
u1(User)
u2(User)
u3(User)
b1(Browser)
b2(Browser)
b3(Browser)
workbench1(Workbench)
workbench2(Workbench)
session(RStudio Session)
jupyter(Jupyter Session)
vscode(VS Code Session)
job(Workbench Job)
nfs(Shared Storage)
pg(Postgres)
subgraph server1 [Linux Server]
workbench1---session
workbench1---job
end
subgraph server2 [Linux Server]
workbench2---jupyter
workbench2---vscode
end
u1---b1
u2---b2
u3---b3
b1---workbench1
b2---workbench1
b3---workbench1
server1-.-nfs
server2-.-nfs
server1-.-pg
server2-.-pg
workbench1-.-workbench2
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 workbench1,workbench2 product
class session,jupyter,vscode,job session
class u1,u2,u3,b1,b2,b3,lb element
class pg,nfs req
Using Workbench with an external resource manager
In this configuration, Workbench is installed on one or more Linux servers, is configured with Launcher and a Kubernetes or Slurm cluster backend, and enables:
- Users to run sessions and jobs on an external compute cluster
Requirements to support this architecture:
- Users’ home directories must be stored on an external shared file server (typically an NFS server)
- It is strongly recommended that session metadata be stored on an external PostgreSQL database server
flowchart LR
u1(User)
u2(User)
u3(User)
b1(Browser)
b2(Browser)
b3(Browser)
workbench(Workbench)
rsession(RStudio Session)
jupyter(Jupyter Session)
vscode(VS Code Session)
job(Workbench Job)
launcher(Launcher)
nfs(Shared Storage)
pg(Postgres)
u1---b1
u2---b2
u3---b3
b1---workbench
b2---workbench
b3---workbench
subgraph server
workbench---launcher
end
subgraph cluster [Resource Manager]
launcher---rsession
launcher---jupyter
launcher---vscode
launcher---job
end
server-.-pg
server-.-nfs
cluster-.-nfs
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 server,cluster server
class workbench,launcher product
class rsession,jupyter,vscode,job session
class u1,u2,u3,b1,b2,b3,lb element
class pg,nfs req
Using Workbench entirely in Kubernetes
In this configuration, Workbench is installed entirely inside a Kubernetes cluster and enables:
- User sessions and jobs run in isolated pods, potentially from different base images
- The entire installation is managed in Kubernetes with tools like Helm
- Optional replicas for high availability
Requirements to support this architecture:
- Users’ home directories must be stored on an external shared file server (typically an NFS server)
- Session metadata must be stored on an external PostgreSQL database server
flowchart LR
u1(User)
u2(User)
u3(User)
b1(Browser)
b2(Browser)
b3(Browser)
ingress(Ingress Controller <br/> nginx/nginx-ingress)
workbench(Workbench <br/> Launcher <br/> ghcr.io/rstudio/rstudio-workbench)
rsession(RStudio Session <br/> docker.io/rstudio/r-session-complete)
jupyter(Jupyter Session <br/> ghcr.io/rstudio/py-session-complete)
vscode(VS Code Session <br/> ghcr.io/rstudio/py-session-complete)
job(Workbench Job <br/> docker.io/rstudio/r-session-complete)
nfs(Shared Storage)
pg(Postgres)
u1---b1
u2---b2
u3---b3
b1---ingress
b2---ingress
b3---ingress
subgraph k8s [Kubernetes cluster]
ingress---workbench
workbench---rsession
workbench---jupyter
workbench---vscode
workbench---job
end
k8s-..-pg
k8s-..-nfs
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 k8s server
class workbench product
class ingress,rsession,jupyter,vscode,job session
class u1,u2,u3,b1,b2,b3,lb element
class pg,nfs req