Path1.Mod1.c - Explore ML Workspace - Environment Setups

Question 1

Single Environment Workspace - Use Case

Answer 1

When you have research-centered scenarios with no need to release artifacts, OR when you’re only deploying inference services across environments ie ONE workspace to accommodate more than one environment

Question 2

RAF

Single Environment Workspace - Pros

Answer 2

Reduced Azure Footprint; minimal management overhead (unlike multi-environment workspaces)

Question 3

RBACs Access

Single Environment Workspace - Cons

Answer 3

• Dev vs Prod workflows have different RBACs respectively == environments could be too loose or rigid
• Datastore access considerations. Ex: excessive access to prod data == compromised data quality

Question 4

“clear…”

Multi-Environment Workspace - Use Case

Answer 4

When you need regulated workspaces with clear separation of duties between environments, and you have users with resource access to those environments. Basically dedicated Workspace Resources per Environment.

Question 5

Three: Staged Security Training

Multi-Environment Workspace - Pros

Answer 5

• Staged rollouts of workflows and artifacts
• Enhanced security and resource control over downstream environments
• Training scenarios on production data (via user access)

Question 6

Three: DevOps Risk Data

Multi-Environment Workspace - Cons

Answer 6

• Requires Azure DevOps knowledge and ML engineering expertise
• Increased risk with management and process overhead (ex. giving access to Prod to investigate issues)
• Data mgmt + dev effort to make prod data available for training

Question 7

One Env w/ Limited Data Access,
One Env w/ Production Data Access setup - Use Case

Answer 7

When you need to segregate dev and prod enviroments (DUR)!

Question 8

Two: Separate Mgmt

One Env w/ Limited Data Access,
One Env w/ Production Data Access setup - Pros

Answer 8

• Clear separation of both duties AND access between dev and prod
• Lower resource mgmt overhead vs a multi-env deployment

Question 9

Two: Dep Data

One Env w/ Limited Data Access,
One Env w/ Production Data Access setup - Cons

Answer 9

• Defining a deployment and rollout process for artifacts across workspaces
• Requires data mgmt and dev effort to make prod data available for training in dev