Research paper on Compute, Load balancing, security, Pricing in Google Cloud Platform(GCP).

1. Google Cloud Platform Load Balancing

Introduction:

Google Cloud Platform Load Balancing enables you to disseminate load-adjusted process assets in single or different locales, to meet your high accessibility prerequisites, to put your assets behind a solitary anycast IP and to scale your assets up or down with keen Autoscaling. Cloud Load Balancing is completely incorporated with Cloud CDN for ideal substance conveyance.  Utilizing Cloud Load Balancing, you can serve content as close as conceivable to your clients, on a framework that can react to more than 1 million questions for each second. Cloud Load Balancing is a completely dispersed, programming characterized, oversaw administration. It isn't occasion or gadget based, so you don't have to deal with a physical burden adjusting foundation.

Types of Cloud Load Balancing:

External load balancing:

Use external load balancing when you need to distribute traffic from the Internet to a GCP network. GCP external load balancing offers the following:

· HTTP or HTTPS traffic: global HTTP(S) Load Balancing

· TCP traffic with SSL offload: global SSL Proxy Load Balancing

· TCP traffic without SSL offload: global TCP Proxy Load Balancing

· UDP traffic: regional Network TCP/UDP Load Balancing

· IPv4 or IPv6 clients

· Global or regional load balancing

Global load balancing requires that you use the Premium Tier.

Internal load balancing:

Use internal load balancing when you need to distribute traffic to instances within a GCP network. GCP Internal TCP/UDP Load Balancing offers the following:

· TCP or UDP traffic

· RFC 1918 load balancing

· Client IP address is preserved

· Health checks

· Autoscaling without prewarming

· Session affinity

· Regional load balancing

GCP Internal HTTP(S) Load Balancing (Beta) offers the following:

· HTTP(S) traffic

· RFC 1918 load balancing

· Health checks

· Autoscaling without prewarming

· Session affinity

· Regional load balancing

2. GCP Security Process:

Introduction:

GCP administrations are intended to convey a more grounded security framework than given by conventional on-premises arrangements. Since Google keeps running on a similar framework made accessible to its clients, associations get similar advantages from these securities.

GCP Security Services:

VPC Service Controls: An instrument that makes and controls a security edge around information put away in API-based administrations like Google Cloud Storage, Big Query, and Bigtable.

Cloud Security Command Center: The device allows clients to view and screen their cloud resources and gives significant security bolster capacities like stockpiling framework filtering, powerlessness identification, and access consents survey.

Access Transparency: Provides clients with a review log of approved regulatory gets to from Google Support and Engineering that tracks action encompassing client information.

Cloud Armor: Cloud Armor is a DDoS and application safeguard administration. It is manufactured utilizing a similar significant innovation and framework that Google depends on to secure its administrations including Search, Gmail, and YouTube.

Information Loss Prevention API: An oversaw administration that allows clients to find, arrange, and possibly redact delicate data put away in computerized get to.

Cloud Identity: A help that controls and characterizes the clients and gatherings and the GCP assets they approach. It exists as an implicit help and independent item.

Why GCP Security is Important:

The insurance of client information is the biggest thought for Google's framework, items and cloud stage. The size of their activities and joint effort with the security inquire about network enable Google to address security vulnerabilities rapidly or anticipate them totally.

Google's shared duty model implies that associations incorporated into the GCP can depend on the security framework of an immense association, while as yet having granular authority over their information and administrations facilitated on the stage. For independent companies that don't have the assets to develop a private cloud administration and its imperative security frameworks, an open cloud administration soothes the weight of keeping up custom security arrangements.

3. Pricing

Introduction

Google Cloud Platform is a cloud computing suite offered by google to its esteemed customers that run on the infrastructure that it uses to for its end-user products such as YouTube or Google Search (Lakshmanan, 2018). According to Google, customers should prefer to host on its cloud platform due to its technical superiority and meritocracy. It also doesn’t tie its customers on the cloud platform in contract-like approaches, and they should be able to leave at any time as needs are. Moreover, Google cloud platform enables customers to switch between resource types anytime depending on how their needs may change (Lakshmanan, 2018). Google’s cloud platform also strives to ensure that customers enjoy the best prices in line with the current level of technology, global markets, and industry. This paper will analyze the Google Cloud Platform and the prices they charge their users for different types of services.

Cloud Computing

Google cloud platform has different categories of services that it offers to its online users, which include: Cloud Computing which has different types of services such as, compute, databases, management tools, and API management; Analytics and Machine Learning which enables cloud data analysis; Management Tools such as stack driver and monitoring; API Management for services such as API monetization and Analytics and Machine Learning (Ciaburro, Ayyadevara, & Perrier, 2018). Different types of services are billed differently and according to the usage. Google Cloud Platform applies the pay-as-you-go model of pricing, which means that there are no up-front fees to be paid as a Commitment before a user is rendered the services requested for.

The Cloud Compute service on the Google Cloud Platforms has different types of services it offers to its users which comprises of, Compute Engine, App Engine, Cloud Run (Beta), Google Kubernetes Engine, Anthos on-premises, Cloud Functions, Cloud Functions for Firebase, Knative, Shielded VMs, and Graphics Processing Unit (Ciaburro, Ayyadevara, & Perrier, 2018). The cloud computing services, for instance, Compute Engine are charged for disk size and network usage calculated in gigabytes (GB). 1 GB is equivalent to 1 unit of gibibyte (GiB) which is equal to 230 bytes. Table 1 below shows the price analysis of Compute Engine for general-purpose machine types in US dollars billed at the end of each billing cycle.

Table 1. Compute Engine price list

Databases

Google Cloud Platform also has database services that it offers to its cloud users. Databases are collections of data which are organized, stored, and accessed electronically. Google offers databases as a cloud service that enables the users to store, organize and access large amounts of data from Google’s internal infrastructure (Ciaburro, Ayyadevara, & Perrier, 2018). A good example of Google Cloud Platform databases services is Cloud Bigtable which is a compressed, proprietary, high performance data storage system on Google File System. Users of Cloud Bigtable are charged for the following; the amount of storage, amount of network bandwidth, the total number of nodes and type of Cloud Bigtable instance. Tables 2, 3, and 4, below shows a price list for the Cloud Bigtable services charged for instant type and storage and networks respectively.

Bigtable pricing based on instant type

Table. 3 Bigtable pricing based on storage

Table 4. Bigtable pricing based on networks

Management Tools

Another Google Cloud platform service is Management Tools. An example of management tools is Stackdriver. This service is a freemium cloud computing system service, but it requires a credit card. Stackdriver provides diagnostic data and performance to public users as a hybrid solution for both AWS and Google cloud environments (Laszewski, Arora, Farr, & Zonooz, 2018). Currently, Stackdriver Debugger and Stackdriver Profiler products are free. However, usage of Stackdriver Logging, Stackdriver Error Reporting, Stackdriver Monitoring and Stackdriver Trace products are chargeable. Table 5. Below shows the price list for the chargeable Stackdriver products.

Table 5. Prices for chargeable Stackdriver Cloud Services

Analytics and Machine Learning

Another service chargeable on Google Cloud Platform is Analytics and Machine Learning. This service enables data scientists and developers to build and run machine learning models on the Google Cloud Platform. An example of this service is BigQuery pricing which offers flexible and scalable pricing options based on user technical needs. Table 6. Shows the price list of BigQuery service storage charges.

Table 6. BigQuery pricing

Conclusion

From the price analysis presented in this paper, it is evident that Google does its best to tailor their prices for different needs and preferences of Cloud Platform users. Google Cloud Platform charges its users mostly based on the amount of space used in gibibytes (GiB), network usage and the number of nodes. Google Cloud Platform offers different types of services which include Cloud Computing, Analytics and Machine Learning Tools, API Management, and Analytics and Machine Learning. In addition, The Cloud Compute service on the Google Cloud Platform has different types of services it offers to its users which comprises of, Compute Engine, App Engine, Cloud Run (Beta), Kubernetes Engine and Anthos on-premises among others.

References

Ciaburro, G., Ayyadevara, K., & Perrier, A. (2018). Hands-On Machine Learning on Google Cloud Platform: Implementing smart and efficient analytics using Cloud ML Engine. Birmingham: Packt Publishing.

Lakshmanan, V. (2018). Data science on the Google cloud platform: Implementing end-to-end real-time data pipelines: from ingest to machine learning. Sebastopol, CA: O'Reilly Media.

Laszewski, T., Arora, K., Farr, E., & Zonooz, P. (2018). Cloud native architectures: Design high-availability and cost-effective applications for the cloud. Birmingham: Packt Publishing Ltd.

4. Compute

Useful technical info:

https://cloud.google.com/products/compute/

https://cloud.google.com/compute/ 30% Describe here about use, advantages, and offerings from google on Cloud TPU or GPU.

https://cloud.google.com/appengine/ 10%-15% or less if needed

https://cloud.google.com/kubernetes-engine/ Containers and container management 10-20%%

Accelerated Cloud Computing 20%

Write who is making use of GCP compute offerings from Google. 10%

Any other info.

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