Update Certification-Exam-Guide.md

Certification-Exam-Guide.md

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 ### Section 1: Designing and planning a cloud solution architecture
 1.1 Designing a solution infrastructure that meets business requirements. Considerations include:
 - business use cases and product strategy
+    * > What does success look like qualitatively
 - cost optimization
+    * > A separate step after business logic criteria are met
 - supporting the application design
+    * > What procedures and processes will be needed?
 - integration
+    * > Working with existing systems in parallel at first? Are there parts that must remain on premises?
 - movement of data
+    * > How and when will the data migrate to the new solutions? 
 - tradeoffs
+    * > Priorities. Timing can be critical to value.
 - build, buy or modify
+    * > Control vs. overhead vs. time
 - success measurements (e.g., Key Performance Indicators (KPI), Return on Investment (ROI), metrics)
+    * > What does success look like quantitatively?
 - Compliance and observability
 
 1.2 Designing a solution infrastructure that meets technical requirements. Considerations include:
 - high availability and failover design
+    * > What are the real criteria?
+    * > What are the measurable goals?
 - elasticity of cloud resources
+    * > How do you want the solution to behave when busy? How will the system behave when under attack? How will it behave when traffic diminishes?
 - scalability to meet growth requirements
+    * > Scaling for growth is different from autoscaling to cover temporary demand non-linearities. When is it time to add a node, upgrade a service, or switch services?
 
 1.3 Designing network, storage, and compute resources. Considerations include:
 - integration with on premises/multi-cloud environments
+    * > When to use gsutil, gsutil rsync, and Storage Transfer Service
 - Cloud native networking (VPC, peering, firewalls, container networking)
+    * > Understand all the networking services and how to connect for throughput, security, billing, and so forth.
 - identification of data processing pipeline
 - matching data characteristics to storage systems
+    * > Velocity(how frequent), Volume(how much), Variety(format, structure), Volatility(how often does it change) -- which services match?
 - data flow diagrams
+    * > Very helpful to know where the data will travel through the solution and to look for bottlenecks and flow monitoring and control 
 - storage system structure (e.g., Object, File, RDBMS, NoSQL, NewSQL)
+    * > ACID(Atomicity, Consistency, Isolation, Durability) - What is eventual consistency? BASE(Basically Available, soft state, eventual consistency). Structure requirements?
 - mapping compute needs to platform products
+    * > Scale, capacity, control/overhead?
 
 1.4 Creating a migration plan (i.e., documents and architectural diagrams). Considerations include:
 - integrating solution with existing systems
+    * > Parallel?
 - migrating systems and data to support the solution
+    * > How much, how to synchronize in both directions? Where is the source of data truth? 
 - licensing mapping
+    * > Data center license to cloud license -- may have different license or requirements for licensed software. 
 - network and management planning
+    * > How will on premises connect to the cloud solution? 
 - testing and proof-of-concept
+    * > Different ways to divide a test audience: random, group, phased, test. 
 
 1.5 Envisioning future solution improvements. Considerations include:
 - cloud and technology improvements
+    * > When the technology improves, how will the solution embrace the improvements?
 - business needs evolution
+    * > When the business changes, how will the solution change? Most solutions don't just need to work once, they need to become self-sustaining.
 - evangelism and advocacy
-
+    * > Who are the gatekeepers and what do they need to know to effectively do their jobs?
+    
 ### Section 2: Managing and provisioning solution Infrastructure
 2.1 Configuring network topologies. Considerations include:
 
 - extending to on-premise (hybrid networking)
+    * > VPN. Interconnect.
 - extending to a multi-cloud environment which may include GCP to GCP communication
+    * > Interoperation interface. Stackdriver(GCP + AWS)
 - security
 - data protection
+    * > Encryption, access, CSEK, KMS
 
 2.2 Configuring individual storage systems. Considerations include:
 - data storage allocation
+    * > Where will the data be located? Resiliency? Change?
 - data processing/compute provisioning
+    * > Which Platform? What capacity?
 - security and access management
+    * > CSEK and Cloud Storage, for example. 
 - network configuration for data transfer and latency
+    * > Location makes a difference in egress charges and round-trip time.
 - data retention and data lifecycle management
+    * > What is the Nearline and Coldline policy? When to delete data?
 - data growth management
+    * > When do you need a different way to organize the data? How much/how big will the current design support?
 
 2.3 Configuring compute systems. Considerations include:
 
 - compute system provisioning
+    * > Speed, throughput, capacity, burstiness? Turn off when not in use?
 - compute volatility configuration (preemptible vs. standard)
+    * > Stateful vs. Stateless. Tolerance for lost data/state
 - network configuration for compute nodes
+    * > Firewall rules, load balancing, NAT, VPN
 - infrastructure provisioning technology configuration (e.g. Chef/Puppet/Ansible/Terraform)
+    * > Deployment Manager...others. The value of self-documenting and automated orchestration of infrastructure.
 - container orchestration (e.g. Kubernetes)
+    * > The value of container-based development: portability, scalability, fault isolation, platform agnostic deployment, CI/CD development methods
 
 ### Section 3: Designing for security and compliance
 3.1 Designing for security. Considerations include: