This document discusses the architecture of a Cassandra cluster using UML and Azure Digital Twin Domain Language (DTDL). It covers the three layers of architecture - functional, generic physical, and specific physical. The functional architecture defines the concepts and operations in the cluster. The generic physical architecture shows the major services and structural divisions. The specific physical architecture selects services and deploys them to infrastructure. It also discusses digital twins, how Azure Digital Twins Explorer can be used to create and query models, and limitations of the DTDL language. There is a demonstration of creating room and floor models to establish relationships.

1. Version 1.0
Architecture of a Cassandra
Cluster in UML and the Azure
Digital Twin Domain Language
UML Architecture and Exploring Azure Digital Twin Explorer
and DTDL for Cassandra
Nicholas Brackley
Enterprise Architect

2. What is Architecture?
● “the conceptual structure and logical organization of a computer or computer-based
system.”
● “Makeup of a composite within context”
● That building thing

3. 3 Layers of Architecture and their Outcomes
● Functional Architecture
○ Data that needs to be managed
○ Database definitions
● Generic Physical Architecture
○ Service and Component Definitions
● Specific Physical Architecture
○ Service Selection, Deployment Architecture, and Digital Twin

4. Functional Architecture of a Cluster
● What are the concepts/ideas involved
in the Cluster
○ Ingress and Egress
○ ELT
● What are major
operations/engagements occuring?
● Nouns, verbs, and adjectives in UML
○ All terms in Cassandra.yaml and
other config files are captured in
the functional architecture

5. Generic Physical Architecture of a Cluster
● Answers Questions
○ What are major services and where are they located?
○ What are the structural divisions in your system?
● Uses
○ Training
○ Deployment Agnostic Architecture
■ Transition Between Clouds/Services
■ Service Connection Requirements

6. Sample Generic Physical Architecture

7. Specific Physical Architecture of a Cluster
● Service Selections
● What services are being deployed into what infrastructure?

8. Cassandra Cluster Specific Physical Architecture

9. Cassandra Cluster Specific Physical Architecture
https://github.com/Anant/cassandra.toolkit

10. Architecture of a Cassandra Cluster
https://blog.anant.us/apache-cassandra-lunch-51-cassandra-cluster-design-and-architecture/
*semi-Functional
*semi-Physical

11. Digital Twins, What and Why?
● A Simulated System
○ Modeling for testing
○ Life-cycle analysis
○ Cost savings
● Use Data Inputs from Real Systems Validate Models
○ Compare the inputs and outputs of the real system and Digital Twin
○ Tools to understand zero day failures
● Tools for Training and Analysis

12. Azure Digital Twins Explorer
● Released June 1, 2021 – Available in Preview on browser in Azure Marketplace
● Import models in human readable formats (JSON, xlsx)
○ Note that this primarily uses Digital Twin Domain Language (DTDL) which is based on JSON- LD
● View Relationships (inheritance, composition) in a graph view
● CLI with SQL-like language to throughout model
● Properties editable
● Connect Properties to IoT devices in the real world

13. Limits to DTDL in Azure
● All top-level DTDL elements in a model must be of type Interface. The reason for this requirement is
that Azure Digital Twins model APIs can receive JSON objects that represent either an interface or
an array of interfaces. As a result, no other DTDL element types are allowed at the top level.
● DTDL for Azure Digital Twins must not define any commands.
● Azure Digital Twins only allows a single level of component nesting, meaning that an interface that's
being used as a component can't have any components itself.
● Interfaces can't be defined inline within other DTDL interfaces; they must be defined as separate
top-level entities with their own IDs. Then, when another interface wants to include that interface as
a component or through inheritance, it can reference its ID. - There is a LOT of editing necessary to
propagate changes throughout a model.

14. Demo (stage 1 - establishing models)
● Using Azure to Start the Instance
● The Room and Floor Tutorial
○ Query
● Static Cassandra Cluster Example
○ Relationships, Inheritance, and Components
○ Query

15. Strategy: Scalable Fast Data
Architecture: Cassandra, Spark, Kafka
Engineering: Node, Python, JVM,CLR
Operations: Cloud, Container
Rescue: Downtime!! I need help.
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