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Prism Terminology Glossary

Overview

Prism uses researcher-friendly terminology while leveraging AWS infrastructure. This glossary helps users familiar with AWS understand how Prism terms map to AWS concepts.

Design Philosophy

For Researchers: Prism prioritizes clarity and accessibility over technical precision. For AWS Experts: Use the --verbose flag on CLI commands to see AWS technical details.


Core Terminology Mapping

Workspaces (User Term) → EC2 Instances (AWS Term)

Prism Term: Workspace AWS Equivalent: EC2 Instance Why the Change: "Workspace" conveys the researcher's mental model - a complete computing environment for their work.

Examples: - Prism: "Launch a workspace" - AWS: "Launch an EC2 instance" - Prism: "List my workspaces" - AWS: "List my EC2 instances"

When to Use Which: - ✅ Workspace - All user-facing Prism interfaces (CLI, GUI) - ✅ Instance - When discussing AWS infrastructure directly (e.g., "EC2 instance types", "spot instances")


Storage Terminology

Storage Terms

Prism Term AWS Equivalent Description
EBS Volume EBS Volume Block storage attached to workspaces
EFS Filesystem EFS Filesystem Shared network filesystem
S3 Bucket S3 Bucket Object storage for datasets

Use --verbose to see AWS details:

# User-friendly output (default)
prism storage list
# → Local Storage:   my-data-L (500GB)
# → Shared Storage:  lab-shared (1TB)

# AWS technical details
prism storage list --verbose
# → Local Storage (EBS gp3):   my-data-L (vol-abc123, 500GB, 3000 IOPS)
# → Shared Storage (EFS):      lab-shared (fs-def456, 1TB, General Purpose)


Compute Terminology

Instance Sizing

Prism Sizes (Simple):

prism workspace launch python-ml my-project --size L

Sizes: XS, S, M, L, XL - XS: 1 vCPU, 2GB RAM, 100GB storage - S: 2 vCPU, 4GB RAM, 500GB storage - M: 2 vCPU, 8GB RAM, 1TB storage - L: 4 vCPU, 16GB RAM, 2TB storage - XL: 8 vCPU, 32GB RAM, 4TB storage

AWS Instance Types (Precise):

prism workspace launch python-ml my-project --instance-type t3.xlarge

Use --verbose to see AWS instance type:

# Default output
prism workspace list
# → my-project   running   Size: L   $2.40/day

# AWS details
prism workspace list --verbose
# → my-project   running   t3.xlarge (4vCPU, 16GB)   $2.40/day


Cost & Optimization Terminology

Hibernation

Prism: Hibernate a workspace AWS: Hibernate an EC2 instance

Both terms refer to the same AWS hibernation feature - pausing compute while preserving RAM state.

Spot Workspaces

Prism: Spot workspace AWS: Spot instance

Uses AWS EC2 Spot Instances for 60-90% cost savings (with potential interruption).


Technical Reference Terms

Terms that Remain AWS-Specific

Some terms are inherently technical and remain AWS-specific in Prism:

Term Context Why Unchanged
EC2 Instance Types Technical sizing Industry-standard classification (t3.large, m5.xlarge, etc.)
Spot Instances Cost optimization Established AWS pricing model
Instance ID System internals AWS resource identifier (i-1234567890abcdef0)
AMI Template optimization AWS Machine Image - technical artifact
VPC/Subnet Network configuration AWS networking concepts
Security Groups Network security AWS firewall rules
IAM Roles Authentication AWS identity and access management

When you see these terms: They refer to AWS infrastructure concepts and are intentionally preserved for technical accuracy.


Region & Availability

Prism: Region AWS: AWS Region Same meaning: Geographic location of AWS data centers

Examples: - us-west-2 - US West (Oregon) - us-east-1 - US East (N. Virginia) - eu-west-1 - Europe (Ireland)


Templates & AMIs

Templates

Prism Term: Template What it is: Pre-configured research environment (e.g., "Python Machine Learning", "R Research") Contains: Software packages, system configuration, user setup

AWS Equivalent: Combination of AMI, user data (cloud-init), and configuration

AMIs (Advanced)

Prism: AMI AWS: Amazon Machine Image Purpose: Pre-built snapshot of a template for faster launching (30s vs 5-8 minutes)

When you see "AMI": This is an advanced performance optimization feature. Most users only need templates.


Lifecycle States

Prism State AWS EC2 State Meaning
Running running Workspace is active and billable
Stopped stopped Workspace is paused (only storage billed)
Hibernated stopped (hibernated) Workspace paused with RAM preserved
Terminated terminated Workspace permanently deleted
Pending pending Workspace is starting up
Stopping stopping Workspace is shutting down

Configuration & Profiles

Prism Profiles

Prism Term: Profile Purpose: Manages AWS credentials, region, and configuration Not to be confused with: AWS profiles (in ~/.aws/credentials)

How they relate:

# Prism profile references an AWS profile
prism profiles add personal research \
  --aws-profile my-aws-creds \
  --region us-west-2

Prism profile = AWS profile + region + Prism settings


Finding Technical Details

CLI --verbose Flag

Add --verbose to any command to see AWS technical details:

# Simple output
prism workspace list
# → my-ml-project   running   Size: L

# Technical details
prism workspace list --verbose
# → my-ml-project   running   t3.xlarge (i-abc123, us-west-2a)

GUI Technical Mode

Settings → Advanced → Show AWS Technical Details

Enables: - Instance types in workspace list - Instance IDs in connection info - AWS service names (EBS, EFS, S3) - VPC/subnet information

CLI Technical Details

Add --verbose to CLI commands to see AWS technical details (instance IDs, ARNs, etc.).


Why This Matters

For Researchers (Majority of Users)

  • Focus on work, not infrastructure: "Workspace" and "storage" make sense for research computing
  • Gentle learning curve: AWS complexity hidden by default, revealed progressively
  • Confidence: Clear terminology reduces fear of misconfiguration or unexpected costs

For DevOps/IT (Power Users)

  • Precise control available: --instance-type, --vpc, --subnet flags for exact AWS resource specification
  • Transparency: --verbose flag reveals all AWS technical details
  • Compatibility: Can use Prism alongside native AWS tools (AWS CLI, Console)

For AWS Experts (Contributors)

  • Code uses AWS terminology internally: Variable names, API calls use instance, instanceId, etc.
  • Documentation for mixed audiences: User guides use "workspace", admin guides use both terms
  • Clear distinction: User-facing vs. implementation terminology

Progressive Disclosure

Prism follows progressive disclosure - simple by default, detailed when needed:

User Level Experience Tools
Beginner Researcher "Launch a workspace for Python ML" GUI, simple CLI commands
Intermediate "Configure storage and networking" CLI with common flags
Advanced "Fine-tune instance types and optimize costs" CLI with --instance-type, cost analysis
Expert "Full AWS infrastructure control" CLI with all AWS flags, --verbose, direct AWS API access

Examples in Context

Scenario: Launching a Workspace

Beginner (Simple):

prism workspace launch python-ml my-research

Intermediate (Sized):

prism workspace launch python-ml my-research --size L

Advanced (Spot + Storage):

prism workspace launch python-ml my-research \
  --size L \
  --spot \
  --attach-storage my-data

Expert (Full Control):

prism workspace launch python-ml my-research \
  --instance-type c5.4xlarge \
  --spot \
  --subnet subnet-abc123 \
  --security-group sg-def456 \
  --verbose

Scenario: Checking Workspace Status

Beginner:

prism workspace list
# → my-research   running   $2.40/day

Advanced:

prism workspace list --verbose
# → my-research   running   c5.4xlarge (i-abc123456789, us-west-2b)   $2.40/day

Expert:

aws ec2 describe-instances --instance-ids i-abc123456789
# → Full AWS EC2 API response


Summary

For Most Users For AWS Experts
Use workspaces, storage, regions Add --verbose to see AWS details
Focus on research, not infrastructure Use --instance-type for precise control
GUI and simple CLI commands Full AWS flag support in CLI
Prism handles AWS complexity Direct AWS API access available

Key Principle: Prism meets users where they are - simple for researchers, powerful for experts.


See Also: - Issue #15 - Instances → Workspaces Rename - Issue #66 - Storage Terminology Simplification - Design Principles - User Requirements