Ensuring a Consistent Experience and Compliance: HipLocal's Solution
Question
Case Study - Company Overview - HipLocal is a community application designed to facilitate communication between people in close proximity.
It is used for event planning and organizing sporting events, and for businesses to connect with their local communities.
HipLocal launched recently in a few neighborhoods in Dallas and is rapidly growing into a global phenomenon.
Its unique style of hyper-local community communication and business outreach is in demand around the world.
Executive Statement - We are the number one local community app; it's time to take our local community services global.
Our venture capital investors want to see rapid growth and the same great experience for new local and virtual communities that come online, whether their members are 10 or 10000 miles away from each other.
Solution Concept - HipLocal wants to expand their existing service, with updated functionality, in new regions to better serve their global customers.
They want to hire and train a new team to support these regions in their time zones.
They will need to ensure that the application scales smoothly and provides clear uptime data.
Existing Technical Environment - HipLocal's environment is a mix of on-premises hardware and infrastructure running in Google Cloud Platform.
The HipLocal team understands their application well, but has limited experience in global scale applications.
Their existing technical environment is as follows: " Existing APIs run on Compute Engine virtual machine instances hosted in GCP.
" State is stored in a single instance MySQL database in GCP.
" Data is exported to an on-premises Teradata/Vertica data warehouse.
" Data analytics is performed in an on-premises Hadoop environment.
" The application has no logging.
" There are basic indicators of uptime; alerts are frequently fired when the APIs are unresponsive.
Business Requirements - HipLocal's investors want to expand their footprint and support the increase in demand they are seeing.
Their requirements are: " Expand availability of the application to new regions.
" Increase the number of concurrent users that can be supported.
" Ensure a consistent experience for users when they travel to different regions.
" Obtain user activity metrics to better understand how to monetize their product.
" Ensure compliance with regulations in the new regions (for example, GDPR)
" Reduce infrastructure management time and cost.
" Adopt the Google-recommended practices for cloud computing.
Technical Requirements - " The application and backend must provide usage metrics and monitoring.
" APIs require strong authentication and authorization.
" Logging must be increased, and data should be stored in a cloud analytics platform.
" Move to serverless architecture to facilitate elastic scaling.
" Provide authorized access to internal apps in a secure manner.
HipLocal's.net-based auth service fails under intermittent load.
What should they do?
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D.D.
https://www.qwiklabs.com/focuses/611?parent=catalogThe best option for HipLocal would be to move to a serverless architecture, which can facilitate elastic scaling, and use Cloud Functions for autoscaling, which can provide authorized access to internal apps in a secure manner, and ensure strong authentication and authorization.
Option A, using App Engine for autoscaling, is not as efficient for handling intermittent load as Cloud Functions, which can be triggered by specific events, such as incoming requests, and can scale up or down automatically. Moreover, App Engine has more limitations regarding the language used, and may require more effort to migrate the existing .net-based auth service.
Option C, using a Compute Engine cluster for the service, would require more management time and cost than a serverless architecture. Also, it would not provide the required strong authentication and authorization for APIs, and would not facilitate elastic scaling as efficiently.
Option D, using a dedicated Compute Engine virtual machine instance for the service, would not be as efficient for handling the increased demand and would require more management time and cost than a serverless architecture. It also would not facilitate elastic scaling as efficiently.
Therefore, Option B, using Cloud Functions for autoscaling, would be the best option for HipLocal to handle intermittent load, provide strong authentication and authorization, and ensure authorized access to internal apps in a secure manner. Moreover, this option would facilitate elastic scaling, as well as providing usage metrics and monitoring, logging, and storing data in a cloud analytics platform.
