GCP_Lesson1.何謂cloud computing_GCP初探_GCP computing architectures

What is cloud computing?

First, you get computing resources on-demand and self-service. All you have to do is use a simple interface and you get the processing power, storage, and network you need, with no need for human intervention.

Second, you access these resources over the net from anywhere you want.

Third, the provider of those resources has a big pool of them and allocates them to customers out of that pool. That allows the provider to get economies of scale by buying in bulk and pass the savings on to the customers. Customers don't have to know or care about the exact physical location of those resources.

Fourth, the resources are elastic. If you need more resources you can get more, rapidly. If you need less, you can scale back.

Last, the customers pay only for what they use or reserve as they go. If they stop using resources, they stop paying.

But why is this model so compelling(引人注目) nowadays? To understand why, we need to look at some history. The first wave of the trend that brought us towards cloud computing was colocation(主機代管), which IT shops have been doing for decades. Instead of building costly capital intensive data centers, they can rent space in shared facilities.

That frees up capital for more flexible uses than real estate. In the first decade of the 2000s, IT departments' need for efficiency drove them to use virtualization. The components of a virtualized data center match the parts of a physical data center; servers, disks and so on.

But now there are virtual devices separately manageable from the underlying hardware. Virtualization lets us all use resources more efficiently and just like colocation, it lets us be more flexible too. With virtualization you still buy, house and maintain the infrastructure. So, you're still in the business of guessing how much hardware you'll need and when, setting it up and keeping it running.

About 10 years ago, Google realized that its business couldn't move fast enough within the confines of the virtualization model. So, Google switched to a container based architecture, an automated elastic Third Wave cloud built from automated services. We'll explain exactly what containers are later in this course. In Google's internal cloud, services automatically provision and configure the infrastructure that is used to run familiar Google applications. Google has spent billions of dollars building this platform and making it resilient and efficient.

Today, Google Cloud platform makes it available to Google customers.

Ref:
https://net.nthu.edu.tw/netsys/colocation
https://www.english.com.tw/modules/newbb/viewtopic.php?post_id=15322

Google believes that in the future every company, regardless of size or industry, will differentiate itself from its competitors through technology largely in the form of software, great software centered on data. Thus, every company will become a data company, if it isn't already one now. Google Cloud provides a wide variety of services for managing and getting value from data and doing that at scale.

Virtualized data centers brought you Infrastructure as a Service, IaaS, and Platform as a Service, PaaS offerings.

IaaS offerings provide raw compute, storage, and network organized in ways that are familiar from data centers.

PaaS offerings, on the other hand, bind application code you write to libraries that give access to the infrastructure your application needs. That way, you can just focus on your application logic.

In the IaaS model, you pay for what you allocate. In the PaaS model, you pay for what you use.
Both sure beat the old way where you bought everything in advance based on lots of risky forecasting.

As Cloud Computing has evolved, the momentum has shifted towards managed infrastructure and managed services.

GCP offers many services in which you need not worry about any resource provisioning at all.
They're easy to build into your applications and you pay per use. By the way, now that I've mentioned PaaS and IaaS, you might be asking yourself what about SaaS?

Of course, Google's popular applications like, Search, Gmail, Docs and Drive are Software as a Service applications in that they're consumed directly over the internet by end users.

According to some estimates out there publicly, Google's network carries as much as 40 percent of the world's Internet traffic every day. Google's network is the largest of its kind on earth and the company has invested billions of dollars over the years to build it.

It's designed to give its users the highest possible throughput(網路吞吐量) and the lowest possible latencies for their applications. The network interconnects at more than 90 Internet exchanges and more than 100 points of presence worldwide. When an Internet user sends traffic to a Google resource, Google responds to the user's request from an edge network location that will provide the lowest latency. Google's Edge-caching network cites content close to end users to minimize latency.
(備註:throughput(網路吞吐量)，在如乙太網路及封包無線電之類的電信網路之中，流通量或網路流通量是指於一通訊通道上單位時間能成功傳遞的平均資料量，資料可以於實體或邏輯鏈結上傳遞，或通過某個網路節點。流通量的單位通常表示為位元每秒，有時也可看到封包每秒，throughput = data length / frame length)

Here's how GCP is organized. Let's start at the finest grain level,
the Zone, shown here on the above.

在GCP當中Zone被作為一個用來存放資源的空間，多數會直接將其視為資料中心。
但嚴格來講，它並不太能直接拿來和機房混唯一談。

GCP架構中很多的Zone會組成一個Region (一種多個zone的集合)，
所謂Region白話來講就是國家地理位置(省分、州、城鎮之類的)。
裡面的zone彼此間會相互往返連接，網速十分快延遲性也在5毫秒以下。

A zone is a deployment area for Google Cloud Platform Resources. For example, when you launch a virtual machine in GCP using Compute Engine, which we'll discuss later, it runs in a zone you specify. Although people think of a zone as being like a GCP Data Center, that's not strictly accurate because a zone doesn't always correspond to a single physical building.

You can still visualize the zone that way, though. Zones are grouped into regions, independent geographic areas, and you can choose what regions your GCP resources are in.

All the zones within a region have fast network connectivity among them. Locations within regions usually have round trip network latencies of under five milliseconds. Think of a zone as a single failure domain(故障域) within a region.
(備註:在計算中，故障域包括計算環境的物理或邏輯部分，當關鍵設備或服務出現問題時，會對計算環境造成負面影響。換句話說，故障域是可能發生故障的基礎結構的區域或組件。)

雞蛋不要放同一籃子~~~
As part of building a fault tolerant(故障容忍度) application, you can spread their resources across multiple zones in a region. That helps protect against unexpected failures. You can run resources in different regions too. Lots of GCP customers do that, both to bring their applications closer to users around the world, and also to protect against the loss of an entire region due to a natural disaster.
(備註:fault tolerant(故障容忍度)也稱容錯(性)，是指系統在部分組件（一個或多個）發生故障時仍能正常運作的能力。如果系統的執行品質全面降低，降低的幅度與故障程度成正比，相反的，設計時未考慮故障容許度的系統，在發生很小的故障時也可能完全故障。)

要多處備份並分散開來
A few Google Cloud Platform Services support placing resources in what we call a Multi-Region. For example, Google Cloud Storage, which we'll discuss later, lets you place data within the Europe Multi-Region. That means, it's stored redundantly in at least two geographic locations, separated by at least 160 kilometers within Europe.

The virtual world is built on physical infrastructure, and all those racks of humming servers use vast amounts of energy. Together, all existing data centers use roughly two percent of the world's electricity, so Google works to make data centers run as efficiently as possible.

Google's data centers were the first to achieve ISO 14001 certification, which is a standard that maps out a framework for improving resource efficiency and reducing waste. This is Google's data center in Hamina, Finland, one of the most advanced and efficient data centers in the Google fleet.

Its cooling system uses seawater from the bay of Finland to reduce energy use.
It's the first of its kind anywhere in the world.

Google is one of the world's largest corporate purchasers of wind and solar energy.
Google has been a hundred percent carbon neutral since 2007, and will shortly reach a hundred percent renewable energy sources for its data centers. Just like its customers, Google is trying to do the right things for the planet. GCP customers have environmental goals of their own, and running their workloads in GCP can be a part of meeting them.

Google是第一家提供By秒等級計價的主雲端服務供應商。

Google was the first major Cloud provider to deliver per second billing for its Infrastructure as a Service Compute offering, Google Compute Engine. Fine-grain(細顆粒的、細小) billing is a big cost savings for workloads that are bursty, which is a lot of them.

Many of the best-known GCP services billed by the second, including Compute Engine and Kubernetes Engine. Compute Engine offers automatically applied sustained use discounts which are automatic discounts that you get for running a virtual machine instance for a significant portion of the billing month. Specifically, when you run an instance for more than 25 percent of a month, Compute Engine automatically gives you a discount for every incremental minute you use for that instance. Compute Engines Custom Virtual Machine types lets you fine-tune(微調) virtual machines for their applications, which in turn lets you tailor(客製化) your pricing for your workloads. Try the online pricing calculator to help estimate your costs.

Open APIs

Some people are afraid to bring their workloads to the cloud because they're afraid they'll get locked into a particular vendor. But in lots of ways, Google gives customers the ability to run their applications elsewhere, if Google becomes no longer the best provider for their needs.

Here are some examples of how Google helps its customers avoid feeling locked in.
GCP services are compatible with open source products. For example, take Cloud Bigtable, a database we'll discuss later. Bigtable uses the interface of the open source database Apache HBase, which gives customers the benefit of code portability(可移植性).
Another example, Cloud Dataproc offers the open source big data environment Hadoop, as a managed service. Google publishes key elements of technology using open source licenses to create ecosystems that provide customers with options other than Google. For example, TensorFlow, an open source software library for machine learning developed inside Google, is at the heart of a strong open source ecosystem. Many GCP technologies provide interoperability(互通性).
Kubernetes gives customers the ability to mix and match microservices running across different clouds, and Google Stackdriver lets customers monitor workload across multiple cloud providers.

Why choose Google Cloud Platform ?

Google Cloud Platform lets you choose from computing, storage, big data, machine learning and application services for your web, mobile, analytics and back-end solutions.

It's global, it's cost effective, it's open source friendly and it's designed for security.
Let's sum up. Google Cloud Platform's products and services can be broadly categorized as compute, storage, big data, machine learning, networking and operations and tools.

Multi-layered security approach

Because Google has seven services with more than a billion users, you can bet security is always on the minds of Google's employees. Design for security is pervasive, throughout the infrastructure, the GCP and Google services run-on.

Let's talk about a few ways Google works to keep customers' data safe, starting at the bottom and working up. Both the server boards and the networking equipment in Google data centers are custom designed by Google. Google also designs custom chips, including a hardware security chip called Titan that's currently being deployed on both servers and peripherals.

Google server machines use cryptographic signatures to make sure they are booting the correct software. Google designs and builds its own data centers which incorporate multiple layers of physical security protections. Access to these data centers is limited to only a very small fraction of Google employees, not including me. Google's infrastructure provides cryptographic privacy and integrity for remote procedure called data-on-the-network, which is how Google services communicate with each other. The infrastructure automatically encrypts our PC traffic in transit between data centers. Google Central Identity Service, which usually manifests to end users as the Google log-in page, goes beyond asking for a simple username and password. It also intelligently challenges users for additional information based on risk factors such as whether they have logged in from the same device or a similar location in the past.

Users can also use second factors when signing in, including devices based on the universal second factor U2F open standard. Here's mine. Most applications at Google access physical storage indirectly via storage services and encryption is built into those services. Google also enables hardware encryption support in hard drives and SSDs. That's how Google achieves encryption at rest of customer data. Google services that want to make themselves available on the Internet register themselves with an infrastructure service called the Google Front End, which checks incoming network connections for correct certificates and best practices. The GFE also additionally, applies protections against denial of service attacks.

The sheer scale of its infrastructure, enables Google to simply absorb many denial of service attacks, even behind the GFEs. Google also has multi-tier, multi-layer denial of service protections that further reduce the risk of any denial of service impact. Inside Google's infrastructure, machine intelligence and rules warn of possible incidents. Google conducts Red Team exercises, simulated attacks to improve the effectiveness of its responses. Google aggressively limits and actively monitors the activities of employees who have been granted administrative access to the infrastructure. To guard against phishing attacks against Google employees, employee accounts including mine require use of U2F compatible security keys. I don't forget my keys as much as I used to. To help ensure that code is as secure as possible Google stores its source code centrally and requires two-party review of new code. Google also gives its developers libraries that keep them from introducing certain classes of security bugs. Externally, Google also runs a vulnerability rewards program, where we pay anyone who is able to discover and inform us of bugs in our infrastructure or applications.

Module

When you run your workloads in GCP, you use projects to organize them.
You use Google Cloud Identity, and Access Management, also called IM, or IAM to control who can do what. And you use your choice of several interfaces to connect.

In this module, you'll use these basics to get started. Projects are the main way you organize the resources you use in GCP. Use them to group together related resources, usually because they have a common business objective. The principle of least privilege(特殊權限) is very important in managing any kind of compute infrastructure, whether it's in the Cloud or on-premises(本機部屬). This principle says that each user should have only those privileges needed to do their jobs. In a least-privilege environment, people are protected from an entire class of errors.

GCP customers use IM to implement least privilege, and it makes everybody happier.
There are four ways to interact with GCP's management layer:

through the web-based console,
through the SDK and its command-line tools,
through the APIs,
and through a mobile app.

When you build an application on your on-premises infrastructure, you're responsible for the entire stack security. From the physical security of the hardware, and the premises in which they're housed, through the encryption of the data on disk, the integrity of your network, all the way up to securing the content stored in those applications. When you move an application to Google Cloud Platform, Google handles many of the lower layers of security. Because of its scale, Google can deliver a higher level of security at these layers than most of its customers could afford to do on their own. The upper layers of the security stack remain the customers' responsibility. Google provides tools such as IAM to help customers implement the policies they choose at these layers.