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| Section | Objectives |
|---|---|
| Topic 1: Designing and planning a cloud solution architecture | - Creating a migration plan
|
| Topic 2: Designing for security and compliance | - Designing for compliance
|
| Topic 3: Managing implementation | - Interacting with Google Cloud programmatically
|
| Topic 4: Ensuring solution and operations reliability | - Evaluating quality control measures - Monitoring/logging/profiling/alerting solution
|
| Topic 5: Managing and provisioning a solution infrastructure | - Configuring individual storage systems
|
| Topic 6: Analyzing and optimizing technical and business processes | - Analyzing and defining business processes
|
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NEW QUESTION # 334
You have a Python web application with many dependencies that requires 0.1 CPU cores and 128 MB of memory to operate in production. You want to monitor and maximize machine utilization. You also want to reliably deploy new versions of the application. Which set of steps should you take?
Answer: A
NEW QUESTION # 335
An application development team has come to you for advice.They are planning to write and deploy an HTTP(S) API using Go 1.12. The API will have a very unpredictable workload and must remain reliable during peaks in traffic. They want to minimize operational overhead for this application. What approach should you recommend?
Answer: C
Explanation:
https://cloud.google.com/appengine/docs/the-appengine-environments
NEW QUESTION # 336
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?
Answer: C
Explanation:
Explanation/Reference:
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
NEW QUESTION # 337
Case Study: 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.
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.
You analyzed TerramEarth's business requirement to reduce downtime, and found that they can achieve a majority of time saving by reducing customers' wait time for parts.
You decided to focus on reduction of the 3 weeks aggregate reporting time.
Which modifications to the company's processes should you recommend?
Answer: A
Explanation:
B - Migrate from FTP to streaming transport, migrate from CSV to binary format, and develop machine learning analysis of metrics.
If no cellular connection, then it cannot do streaming; CVS to binary does not necessary reduce the size (compress does).
C (Correct answer) - Increase fleet cellular connectivity to 80%, migrate from FTP to streaming transport, and develop machine learning analysis of metrics.
TerramEarth Existing Technical Environment New Solution: 80% going to streaming; 20% goes to Batch; No FTP GCP offers many ways to connect to PubSub and GCS such as IOT Type, rich client library, as well as gsutil for reliable, parallel, resumable upload data By increase fleet cellular connectivity to 80%, migrating from FTP to streaming transport, and the rest of 20% batch users for Cloud storage upload instead of FTP, majority of bottlenecked areas are covered and resolved.
A and D can be eliminated for "Migrate from FTP to SFTP transport" since SFTP doesn't provide speed advantage over FTP nor the better solution with streaming.
NEW QUESTION # 338
A development manager is building a new application He asks you to review his requirements and identify what cloud technologies he can use to meet them. The application must
1. Be based on open-source technology for cloud portability
2. Dynamically scale compute capacity based on demand
3. Support continuous software delivery
4. Run multiple segregated copies of the same application stack
5. Deploy application bundles using dynamic templates
6. Route network traffic to specific services based on URL
Which combination of technologies will meet all of his requirements?
Answer: C
Explanation:
Explanation
Helm for managing Kubernetes
Kubernetes can base on the URL to route traffic to different location (path)
https://cloud.google.com/kubernetes-engine/docs/tutorials/http-balancer eg.apiVersion: networking.k8s.io/v1beta1 kind: Ingress metadata:
name: fanout-ingress
spec:
rules:
- http:
paths:
- path: /*
backend:
serviceName: web
servicePort: 8080
- path: /v2/*
backend:
serviceName: web2
servicePort: 8080
NEW QUESTION # 339
......
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