Cloud-Digital-Leader Exam Dumps - Google Cloud Digital Leader exam

Containers and Kubernetes are ideal for the kind of requirement mentioned here - separate microservices that need to scale independently.

Google Kubernetes Engine (GKE) provides a managed environment for deploying, managing, and scaling your containerized applications using Google infrastructure. The GKE environment consists of multiple machines (specifically, Compute Engine instances) grouped together to form a cluster.

Reference link- https://cloud.google.com/kubernetes-engine/docs/concepts/kubernetes-engine-overview

Integrated repository for analytics and ML: The highest level of availability and performance within a single region is ideal for compute, analytics, and machine learning workloads in a particular region. Cloud Storage is also strongly consistent, giving you confidence and accuracy in analytics workloads.

Table Description automatically generated with medium confidence

https://cloud.google.com/storage/docs/storage-classes

Cloud Datastore is the best for semi-structured application data that is used in app engines' applications. Bigtable is best for analytical data with heavy read/write events like AdTech, Financial or IoT data. Cloud Storage is best for structured and unstructured, binary or object data like images, large media files and backups. SQL is best for web frameworks and in existing applications like storing user credentials and customer orders. Cloud Spanner is best for large scale database applications that are larger than two terabytes; for example, for financial trading and e-commerce use cases. As I mentioned at the beginning of the module, depending on your application, you might use one or several of these services to get the job done.

What is Infrastructure as a service :

IaaS (infrastructure as a service) is a computing model that offers resources on-demand to businesses and individuals via the cloud.

IaaS is attractive because acquiring computing resources to run applications or store data the traditional way requires time and capital. Enterprises must purchase equipment through procurement processes that can take months. They must invest in physical spaces: typically specialized rooms with power and cooling. And after deploying the systems, enterprises need IT, professionals, to manage them.

All this is challenging to scale when demand spikes or the business grows. Enterprises risk running out of capacity or overbuilding and ending up with infrastructure that suffers from low utilization.

These challenges are why IaaS use is steadily growing. Learn more about Compute Engine, Cloud Storage, etc.

Google provides a page that brings together everything needed around support. Its called the Support Hub

Reference link- https://cloud.google.com/support-hub

Compute Engine provides machine type recommendations to help you optimize the resource utilization of your virtual machine (VM) instances. These recommendations are generated automatically based on system metrics gathered by the Cloud Monitoring service over the previous 8 days. Use these recommendations to resize your instance’s machine type to use the instance’s resources more efficiently. This feature is also known as rightsizing recommendations

Reference link- https://cloud.google.com/compute/docs/instances/apply-machine-type-recommendations-for-instances

Using sync for new images implies that you will continue to use your onprem and keep synchronizing it forever, Sync just once for the old images, new images go directly to google cloud via pub/sub, and eventually get rid of the onprem.

In many cases, customers might not know the implications of the 9s with respect to scheduled maintenance, upgrades, etc. It's possible that they are holding unnecessary expectations that significantly exceed their requirements.

-> Even though 0.0009 % increase it looks like a small increment, an addition of a single 9 reduces the possible downtime by 10 times. So the effort is often much greater.

Reference link-  https://en.wikipedia.org/wiki/High_availability