Latest Professional-Cloud-Architect exam - Professional-Cloud-Architect Questions Answers -  Dumpsforsure.com
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Professional-Cloud-Architect
Version: Demo
[ Total Questions: 10]
Google - Professional-Cloud-Architect
Topic 1, Mountkirk Games Case Study
Company Overview
Mountkirk Games makes online, session-based. multiplayer games for the most popular mobile platforms.
Company Background
Mountkirk Games builds all of their games with some server-side integration and has historically used cloud
providers to lease physical servers. A few of their games were more popular than expected, and they had
problems scaling their application servers, MySQL databases, and analytics tools.
Mountkirk's current model is to write game statistics to files and send them through an ETL tool that loads
them into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the
game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics and
take advantage of its autoscaling server environment and integrate with a managed NoSQL database.
Technical Requirements
Requirements for Game Backend Platform
1. Dynamically scale up or down based on game activity.
2. Connect to a managed NoSQL database service.
3. Run customized Linx distro.
Requirements for Game Analytics Platform
1. Dynamically scale up or down based on game activity.
2. Process incoming data on the fly directly from the game servers.
3. Process data that arrives late because of slow mobile networks.
4. Allow SQL queries to access at least 10 TB of historical data.
5. Process files that are regularly uploaded by users' mobile devices.
6. Use only fully managed services
CEO Statement
Our last successful game did not scale well with our previous cloud provider, resuming in lower user adoption
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and affecting the game’s reputation. Our investors want more key performance indicators (KPIs) to evaluate
the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so
we can adapt the gams to target users.
CTO Statement
Our current technology stack cannot provide the scale we need, so we want to replace MySQL and move to an
environment that provides autoscaling, low latency load balancing, and frees us up from managing physical
servers.
CFO Statement
We are not capturing enough user demographic data usage metrics, and other KPIs. As a result, we do not
engage the right users. We are not confident that our marketing is targeting the right users, and we are not
selling enough premium Blast-Ups inside the games, which dramatically impacts our revenue.
Question #:1 - (Exam Topic 1)
For this question, refer to the Mountkirk Games case study.
Mountkirk Games has deployed their new backend on Google Cloud Platform (GCP). You want to create a
thorough testing process for new versions of the backend before they are released to the public. You want the
testing environment to scale in an economical way. How should you design the process?
A.  Create a scalable environment in GCP for simulating production load.
B.  Use the existing infrastructure to test the GCP-based backend at scale.
C.  Build stress tests into each component of your application using resources internal to GCP to simulate
load.
D.  Create a set of static environments in GCP to test different levels of load — for example, high, medium,
and low.
Answer: A
Explanation
From scenario: Requirements for Game Backend Platform
Dynamically scale up or down based on game activity
Connect to a managed NoSQL database service
Run customize Linux distro
Question #:2 - (Exam Topic 1)
For this question, refer to the Mountkirk Games case study
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Mountkirk Games needs to create a repeatable and configurable mechanism for deploying isolated application
environments. Developers and testers can access each other's environments and resources, but they cannot
access staging or production resources. The staging environment needs access to some services from
production.
What should you do to isolate development environments from staging and production?
A.  Create a project for development and test and another for staging and production.
B.  Create a network for development and test and another for staging and production.
C.  Create one subnetwork for development and another for staging and production.
D.  Create one project for development, a second for staging and a third for production.
Answer: D
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Topic 3, JencoMart Case Study
Company Overview
JencoMart is a global retailer with over 10,000 stores in 16 countries. The stores carry a range of goods, such
as groceries, tires, and jewelry. One of the company’s core values is excellent customer service. In addition,
they recently introduced an environmental policy to reduce their carbon output by 50% over the next 5 years.
Company Background
JencoMart started as a general store in 1931, and has grown into one of the world’s leading brands known for
great value and customer service. Over time, the company transitioned from only physical stores to a stores
and online hybrid model, with 25% of sales online. Currently, JencoMart has little presence in Asia, but
considers that market key for future growth.
Solution Concept
JencoMart wants to migrate several critical applications to the cloud but has not completed a technical review
to determine their suitability for the cloud and the engineering required for migration. They currently host all
of these applications on infrastructure that is at its end of life and is no longer supported.
Existing Technical Environment
JencoMart hosts all of its applications in 4 data centers: 3 in North American and 1 in Europe, most
applications are dual-homed.
JencoMart understands the dependencies and resource usage metrics of their on-premises architecture.
Application Customer loyalty portal
LAMP (Linux, Apache, MySQL and PHP) application served from the two JencoMart-owned U.S. data
centers.
Database
• Oracle Database stores user profiles
20 TB
Complex table structure
Well maintained, clean data
Strong backup strategy
• PostgreSQL database stores user credentials
Single-homed in US West
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No redundancy
Backed up every 12 hours
100% uptime service level agreement (SLA)
Authenticates all users
Compute
• 30 machines in US West Coast, each machine has:
Twin, dual core CPUs
32GB of RAM
Twin 250 GB HDD (RAID 1)
• 20 machines in US East Coast, each machine has:
Single dual-core CPU
24 GB of RAM
Twin 250 GB HDD (RAID 1)
Storage
• Access to shared 100 TB SAN in each location
• Tape backup every week
Business Requirements
• Optimize for capacity during peak periods and value during off-peak periods
• Guarantee service availably and support
• Reduce on-premises footprint and associated financial and environmental impact.
• Move to outsourcing model to avoid large upfront costs associated with infrastructure purchase
• Expand services into Asia.
Technical Requirements
• Assess key application for cloud suitability.
• Modify application for the cloud.
• Move applications to a new infrastructure.
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• Leverage managed services wherever feasible
• Sunset 20% of capacity in existing data centers
• Decrease latency in Asia
CEO Statement
JencoMart will continue to develop personal relationships with our customers as more people access the web.
The future of our retail business is in the global market and the connection between online and in-store
experiences. As a large global company, we also have a responsibility to the environment through ‘green’
initiatives and polices.
CTO Statement
The challenges of operating data centers prevents focus on key technologies critical to our long-term success.
Migrating our data services to a public cloud infrastructure will allow us to focus on big data and machine
learning to improve our service customers.
CFO Statement
Since its founding JencoMart has invested heavily in our data services infrastructure. However, because of
changing market trends, we need to outsource our infrastructure to ensure our long-term success. This model
will allow us to respond to increasing customer demand during peak and reduce costs.
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Question #:4 - (Exam Topic 3)
For this question, refer to the JencoMart case study.
The JencoMart security team requires that all Google Cloud Platform infrastructure is deployed using a least
privilege model with separation of duties for administration between production and development resources.
What Google domain and project structure should you recommend?
A.  Create two G Suite accounts to manage users: one for development/test/staging and one for production.
Each account should contain one project for every application.
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B.  Create two G Suite accounts to manage users: one with a single project for all development applications
and one with a single project for all production applications.
C.  Create a single G Suite account to manage users with each stage of each application in its own project.
D.  Create a single G Suite account to manage users with one project for the development/test/staging
environment and one project for the production environment.
Answer: D
Explanation
Note: The principle of least privilege and separation of duties are concepts that, although semantically
different, are intrinsically related from the standpoint of security. The intent behind both is to prevent people
from having higher privilege levels than they actually need
Principle of Least Privilege: Users should only have the least amount of privileges required to perform
their job and no more. This reduces authorization exploitation by limiting access to resources such as
targets, jobs, or monitoring templates for which they are not authorized.
Separation of Duties: Beyond limiting user privilege level, you also limit user duties, or the specific jobs
they can perform. No user should be given responsibility for more than one related function. This limits
the ability of a user to perform a malicious action and then cover up that action.
References: https://cloud.google.com/kms/docs/separation-of-duties
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Topic 2, TerramEarth Case Study
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries: About 80% of their
business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in
100 countries. Their mission is to build products that make their customers more productive.
Company Background
TerramEarth formed in 1946, when several small, family owned companies combined to retool after World
War II. The company cares about their employees and customers and considers them to be extended members
of their family.
TerramEarth is proud of their ability to innovate on their core products and find new markets as their
customers' needs change. For the past 20 years trends in the industry have been largely toward increasing
productivity by using larger vehicles with a human operator.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second. Data is
stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced. The data is
downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the
vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data
directly. At a rate of 120 fields of data per second, with 22 hours of operation per day. TerramEarth collects a
total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth’s existing architecture is composed of Linux-based systems that reside in a data center. These
systems gzip CSV files from the field and upload via FTP, transform and aggregate them, and place the data in
their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned
downtime of their vehicles by 60%. However, because the data is stale, some customers are without their
vehicles for up to 4 weeks while they wait for replacement parts.
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Business Requirements
• Decrease unplanned vehicle downtime to less than 1 week, without increasing the cost of carrying surplus
inventory
• Support the dealer network with more data on how their customers use their equipment IP better position
new products and services.
• Have the ability to partner with different companies-especially with seed and fertilizer suppliers in the
fast-growing agricultural business-to create compelling joint offerings for their customers
CEO Statement
We have been successful in capitalizing on the trend toward larger vehicles to increase the productivity of our
customers. Technological change is occurring rapidly and TerramEarth has taken advantage of connected
devices technology to provide our customers with better services, such as our intelligent farming equipment.
With this technology, we have been able to increase farmers' yields by 25%, by using past trends to adjust how
our vehicles operate. These advances have led to the rapid growth of our agricultural product line, which we
expect will generate 50% of our revenues by 2020.
CTO Statement
Our competitive advantage has always been in the manufacturing process with our ability to build better
vehicles for tower cost than our competitors. However, new products with different approaches are constantly
being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our
industry. Unfortunately, our CEO doesn't take technology obsolescence seriously and he considers the many
new companies in our industry to be niche players. My goals are to build our skills while addressing
immediate market needs through incremental innovations.
Question #:5 - (Exam Topic 2)
For this question, refer to the TerramEarth case study.
TerramEarth's 20 million vehicles are scattered around the world. Based on the vehicle's location its telemetry
data is stored in a Google Cloud Storage (GCS) regional bucket (US. Europe, or Asia). The CTO has asked
you to run a report on the raw telemetry data to determine why vehicles are breaking down after 100 K miles.
You want to run this job on all the data. What is the most cost-effective way to run this job?
A.  Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job.
B.  Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job.
C.  Launch a cluster in each region to preprocess and compress the raw data, then move the data into a multi
region bucket and use a Dataproc cluster to finish the job.
D.  Launch a cluster in each region to preprocess and compress the raw data, then move the data into a
region bucket and use a Cloud Dataproc cluster to finish the jo
Answer: D
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Explanation
Storageguarantees 2 replicates which are geo diverse (100 miles apart) which can get better remote latency and
availability.
More importantly, is that multiregional heavily leverages Edge caching and CDNs to provide the content to the
end users.
All this redundancy and caching means that Multiregional comes with overhead to sync and ensure
consistency between geo-diverse areas. As such, it’s much better for write-once-read-many scenarios. This
means frequently accessed (e.g. “hot” objects) around the world, such as website content, streaming videos,
gaming or mobile applications.
References:
https://medium.com/google-cloud/google-cloud-storage-what-bucket-class-for-the-best-performance-5c847ac8f9f2
Question #:6 - (Exam Topic 2)
For this question, refer to the TerramEarth case study.
To speed up data retrieval, more vehicles will be upgraded to cellular connections and be able to transmit data
to the ETL process. The current FTP process is error-prone and restarts the data transfer from the start of the
file when connections fail, which happens often. You want to improve the reliability of the solution and
minimize data transfer time on the cellular connections. What should you do?
A.  Use one Google Container Engine cluster of FTP servers. Save the data to a Multi-Regional bucket. Run
the ETL process using data in the bucket.
B.  Use multiple Google Container Engine clusters running FTP servers located in different regions. Save
the data to Multi-Regional buckets in us, eu, and asia. Run the ETL process using the data in the bucket.
C.  Directly transfer the files to different Google Cloud Multi-Regional Storage bucket locations in us, eu,
and asia using Google APIs over HTTP(S). Run the ETL process using the data in the bucket.
D.  Directly transfer the files to a different Google Cloud Regional Storage bucket location in us, eu, and
asia using Google APIs over HTTP(S). Run the ETL process to retrieve the data from each Regional
bucket.
Answer: D
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Topic 7, TerramEarth Case 2
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries. About 80% of their
business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in
100 countries. Their mission is to build products that make their customers more productive.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second. Data is
stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced. The data is
downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the
vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data
directly. At a rate of 120 fields of data per second with 22 hours of operation per day, TerramEarth collects a
total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth’s existing architecture is composed of Linux and Windows-based systems that reside in a single
U.S. west coast based data center. These systems gzip CSV files from the field and upload via FTP, and place
the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3
weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned
downtime of their vehicles by 60%. However, because the data is stale, some customers are without their
vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
Decrease unplanned vehicle downtime to less than 1 week.
Support the dealer network with more data on how their customers use their equipment to better position new
products and services
Have the ability to partner with different companies – especially with seed and fertilizer suppliers in the
fast-growing agricultural business – to create compelling joint offerings for their customers.
Technical Requirements
Expand beyond a single datacenter to decrease latency to the American Midwest and east coast.
Create a backup strategy.
Increase security of data transfer from equipment to the datacenter.
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Improve data in the data warehouse.
Use customer and equipment data to anticipate customer needs.
Application 1: Data ingest
A custom Python application reads uploaded datafiles from a single server, writes to the data warehouse.
Compute:
Windows Server 2008 R2
- 16 CPUs
- 128 GB of RAM
- 10 TB local HDD storage
Application 2: Reporting
An off the shelf application that business analysts use to run a daily report to see what equipment needs repair.
Only 2 analysts of a team of 10 (5 west coast, 5 east coast) can connect to the reporting application at a time.
Compute:
Off the shelf application. License tied to number of physical CPUs
- Windows Server 2008 R2
- 16 CPUs
- 32 GB of RAM
- 500 GB HDD
Data warehouse:
A single PostgreSQL server
- RedHat Linux
- 64 CPUs
- 128 GB of RAM
- 4x 6TB HDD in RAID 0
Executive Statement
Our competitive advantage has always been in the manufacturing process, with our ability to build better
vehicles for lower cost than our competitors. However, new products with different approaches are constantly
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being developed, and I’m concerned that we lack the skills to undergo the next wave of transformations in our
industry. My goals are to build our skills while addressing immediate market needs through incremental
innovations.
Question #:7 - (Exam Topic 7)
For this question, refer to the TerramEarth case study. To be compliant with European GDPR regulation,
TerramEarth is required to delete data generated from its European customers after a period of 36 months
when it contains personal data. In the new architecture, this data will be stored in both Cloud Storage and
BigQuery. What should you do?
A.  Create a BigQuery table for the European data, and set the table retention period to 36 months. For
Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age
condition of 36 months.
B.  Create a BigQuery table for the European data, and set the table retention period to 36 months. For
Cloud Storage, use gsutil to create a SetStorageClass to NONE action when with an Age condition of 36
months.
C.  Create a BigQuery time-partitioned table for the European data, and set the partition expiration period to
36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with
an Age condition of 36 months.
D.  Create a BigQuery time-partitioned table for the European data, and set the partition period to 36
months. For Cloud Storage, use gsutil to create a SetStorageClass to NONE action with an Age
condition of 36 months.
Answer: C
Question #:8 - (Exam Topic 7)
For this question, refer to the TerramEarth case study. You need to implement a reliable, scalable GCP
solution for the data warehouse for your company, TerramEarth. Considering the TerramEarth business and
technical requirements, what should you do?
A.  Replace the existing data warehouse with BigQuery. Use table partitioning.
B.  Replace the existing data warehouse with a Compute Engine instance with 96 CPUs.
C.  Replace the existing data warehouse with BigQuery. Use federated data sources.
D.  Replace the existing data warehouse with a Compute Engine instance with 96 CPUs. Add an additional
Compute Engine pre-emptible instance with 32 CPUs.
Answer: C
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Topic 8, Mountkrik Games Case 2
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of
their games using some server-side integration. Historically, they have used cloud providers to lease physical
servers.
Due to the unexpected popularity of some of their games, they have had problems scaling their global
audience, application servers, MySQL databases, and analytics tools.
Their current model is to write game statistics to files and send them through an ETL tool that loads them into
a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the
game’s backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics,
and take advantage of its autoscaling server environment and integrate with a managed NoSQL database.
Business Requirements
Increase to a global footprint.
Improve uptime – downtime is loss of players.
Increase efficiency of the cloud resources we use.
Reduce latency to all customers.
Technical Requirements
Requirements for Game Backend Platform
Dynamically scale up or down based on game activity.
Connect to a transactional database service to manage user profiles and game state.
Store game activity in a timeseries database service for future analysis.
As the system scales, ensure that data is not lost due to processing backlogs.
Run hardened Linux distro.
Requirements for Game Analytics Platform
Dynamically scale up or down based on game activity
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Process incoming data on the fly directly from the game servers
Process data that arrives late because of slow mobile networks
Allow queries to access at least 10 TB of historical data
Process files that are regularly uploaded by users’ mobile devices
Executive Statement
Our last successful game did not scale well with our previous cloud provider, resulting in lower user adoption
and affecting the game’s reputation. Our investors want more key performance indicators (KPIs) to evaluate
the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so
we can adapt the game to target users. Additionally, our current technology stack cannot provide the scale we
need, so we want to replace MySQL and move to an environment that provides autoscaling, low latency load
balancing, and frees us up from managing physical servers.
Question #:9 - (Exam Topic 8)
For this question, refer to the Mountkirk Games case study. You need to analyze and define the technical
architecture for the compute workloads for your company, Mountkirk Games. Considering the Mountkirk
Games business and technical requirements, what should you do?
A.  Create network load balancers. Use preemptible Compute Engine instances.
B.  Create network load balancers. Use non-preemptible Compute Engine instances.
C.  Create a global load balancer with managed instance groups and autoscaling policies. Use preemptible
Compute Engine instances.
D.  Create a global load balancer with managed instance groups and autoscaling policies. Use
non-preemptible Compute Engine instances.
Answer: C
Question #:10 - (Exam Topic 8)
For this question, refer to the Mountkirk Games case study. You need to analyze and define the technical
architecture for the database workloads for your company, Mountkirk Games. Considering the business and
technical requirements, what should you do?
A.  Use Cloud SQL for time series data, and use Cloud Bigtable for historical data queries.
B.  Use Cloud SQL to replace MySQL, and use Cloud Spanner for historical data queries.
C.  Use Cloud Bigtable to replace MySQL, and use BigQuery for historical data queries.
D.  Use Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and use BigQuery for
historical data queries.
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Answer: D
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Topic 6, Dress4Win Case 2
Company Overview
Dress4win is a web-based company that helps their users organize and manage their personal wardrobe using a
website and mobile application. The company also cultivates an active social network that connects their users
with designers and retailers. They monetize their services through advertising, e-commerce, referrals, and a
freemium app model. The application has grown from a few servers in the founder’s garage to several hundred
servers and appliances in a collocated data center. However, the capacity of their infrastructure is now
insufficient for the application’s rapid growth. Because of this growth and the company’s desire to innovate
faster. Dress4Win is committing to a full migration to a public cloud.
Solution Concept
For the first phase of their migration to the cloud, Dress4win is moving their development and test
environments. They are also building a disaster recovery site, because their current infrastructure is at a single
location. They are not sure which components of their architecture they can migrate as is and which
components they need to change before migrating them.
Existing Technical Environment
The Dress4win application is served out of a single data center location. All servers run Ubuntu LTS v16.04.
Databases:
MySQL. 1 server for user data, inventory, static data:
- MySQL 5.8
- 8 core CPUs
- 128 GB of RAM
- 2x 5 TB HDD (RAID 1)
Redis 3 server cluster for metadata, social graph, caching. Each server is:
- Redis 3.2
- 4 core CPUs
- 32GB of RAM
Compute:
40 Web Application servers providing micro-services based APIs and static content.
- Tomcat - Java
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- Nginx
- 4 core CPUs
- 32 GB of RAM
20 Apache Hadoop/Spark servers:
- Data analysis
- Real-time trending calculations
- 8 core CPUS
- 128 GB of RAM
- 4x 5 TB HDD (RAID 1)
3 RabbitMQ servers for messaging, social notifications, and events:
- 8 core CPUs
- 32GB of RAM
Miscellaneous servers:
- Jenkins, monitoring, bastion hosts, security scanners
- 8 core CPUs
- 32GB of RAM
Storage appliances:
iSCSI for VM hosts
Fiber channel SAN – MySQL databases
- 1 PB total storage; 400 TB available
NAS – image storage, logs, backups
- 100 TB total storage; 35 TB available
Business Requirements
Build a reliable and reproducible environment with scaled parity of production.
Improve security by defining and adhering to a set of security and Identity and Access Management (IAM)
best practices for cloud.
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Improve business agility and speed of innovation through rapid provisioning of new resources.
Analyze and optimize architecture for performance in the cloud.
Technical Requirements
Easily create non-production environment in the cloud.
Implement an automation framework for provisioning resources in cloud.
Implement a continuous deployment process for deploying applications to the on-premises datacenter or cloud.
Support failover of the production environment to cloud during an emergency.
Encrypt data on the wire and at rest.
Support multiple private connections between the production data center and cloud environment.
Executive Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They
are also concerned that a competitor could use a public cloud platform to offset their up-front investment and
free them to focus on developing better features. Our traffic patterns are highest in the mornings and weekend
evenings; during other times, 80% of our capacity is sitting idle.
Our capital expenditure is now exceeding our quarterly projections. Migrating to the cloud will likely cause an
initial increase in spending, but we expect to fully transition before our next hardware refresh cycle. Our total
cost of ownership (TCO) analysis over the next 5 years for a public cloud strategy achieves a cost reduction
between 30% and 50% over our current model.
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Topic 4, Dress4Win case study
Company Overview
Dress4win is a web-based company that helps their users organize and manage their personal wardrobe using a
website and mobile application. The company also cultivates an active social network that connects their users
with designers and retailers. They monetize their services through advertising, e-commerce, referrals, and a
freemium app model.
Company Background
Dress4win’s application has grown from a few servers in the founder’s garage to several hundred servers and
appliances in a colocated data center. However, the capacity of their infrastructure is now insufficient for the
application’s rapid growth. Because of this growth and the company’s desire to innovate faster, Dress4win is
committing to a full migration to a public cloud.
Solution Concept
For the first phase of their migration to the cloud, Dress4win is considering moving their development and test
environments. They are also considering building a disaster recovery site, because their current infrastructure
is at a single location. They are not sure which components of their architecture they can migrate as is and
which components they need to change before migrating them.
Existing Technical Environment
The Dress4win application is served out of a single data center location.
Databases:
MySQL - user data, inventory, static data
Redis - metadata, social graph, caching
Application servers:
Tomcat - Java micro-services
Nginx - static content
Apache Beam - Batch processing
Storage appliances:
iSCSI for VM hosts
Fiber channel SAN - MySQL databases
NAS - image storage, logs, backups
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Apache Hadoop/Spark servers:
Data analysis
Real-time trending calculations
MQ servers:
Messaging
Social notifications
Events
Miscellaneous servers:
Jenkins, monitoring, bastion hosts, security scanners
Business Requirements
Build a reliable and reproducible environment with scaled parity of production.
Improve security by defining and adhering to a set of security and Identity and Access Management
(IAM) best practices for cloud.
Improve business agility and speed of innovation through rapid provisioning of new resources.
Analyze and optimize architecture for performance in the cloud.
Migrate fully to the cloud if all other requirements are met.
Technical Requirements
Evaluate and choose an automation framework for provisioning resources in cloud.
Support failover of the production environment to cloud during an emergency.
Identify production services that can migrate to cloud to save capacity.
Use managed services whenever possible.
Encrypt data on the wire and at rest.
Support multiple VPN connections between the production data center and cloud environment.
CEO Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They
are also concerned that a new competitor could use a public cloud platform to offset their up-front investment
and freeing them to focus on developing better features.
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Google - Professional-Cloud-Architect
CTO Statement
We have invested heavily in the current infrastructure, but much of the equipment is approaching the end of its
useful life. We are consistently waiting weeks for new gear to be racked before we can start new projects. Our
traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is
sitting idle.
CFO Statement
Our capital expenditure is now exceeding our quarterly projections. Migrating to the cloud will likely cause an
initial increase in spending, but we expect to fully transition before our next hardware refresh cycle. Our total
cost of ownership (TCO) analysis over the next 5 years puts a cloud strategy between 30 to 50% lower than
our current model.
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