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Azgomi is a community application designed to facilitate communication between people in close proximity. It is used for event planning, organizing sporting events, and for businesses to connect with their local communities. Azgomi 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.

The company's executive statement is to take their local community services global. Azgomi 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.

Azgomi's environment is a mix of on-premises hardware and infrastructure running in Google Cloud Platform. The Azgomi team understands their application well, but has limited experience in global scale applications. 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.

Azgomi's investors want to expand their footprint and support the increase in demand they are seeing. Their requirements are to 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, and adopt the Google-recommended practices for cloud computing.

Technical requirements include providing usage metrics and monitoring, APIs requiring strong authentication and authorization, increased logging, and data stored in a cloud analytics platform. The application and backend must be moved to a serverless architecture to facilitate elastic scaling. The authorized access to internal apps should be provided in a secure manner. Azgomi has connected their Hadoop infrastructure to GCP using Cloud Interconnect in order to query data stored on persistent disks.

What would be the most appropriate IP strategy for them to implement?

A stateless web application for a marquee is being developed for Google Cloud. It is expected that the incoming user traffic will be unpredictable, with some days having no traffic while other days will have large spikes. The application should be able to automatically scale up and down, while minimizing the cost associated with running the application.

What actions do you need to take?

The analytics system is currently facing a permission error while executing queries against a BigQuery dataset. The SQL query is executed in batch by passing the contents of a SQL file to the BigQuery CLI, which in turn redirects the output to another process. To resolve this issue, you need to identify the root cause of the permission error and take necessary steps to fix it.

What actions are recommended in this situation?

What is the purpose of predefined roles in GCP?

What is a pod in a Kubernetes cluster?