Chapter 1. What is “cloud”?

This chapter covers:

• Overview of “the cloud”

• When and when not to use cloud hosting and what to expect

• Explanation of cloud pricing principles

• What it means to build an application for the cloud

• A walk-through of Google Cloud Platform
  
  

Cloud is a collection of services that helps developers focus on their project rather

than on the infrastructure that powers it.

Cloud services are things like Amazon Elastic Compute Cloud (EC2) or Google

Compute Engine

(GCE), which provide APIs to provision virtual servers, where customers pay per

hour for the use of these servers.

Infrastructure, where computing, storage, analytics, networking, and more

are all pushed higher up the computing stack.

Away from CPUs and RAM and toward APIs for higher-level operations such as

storing or querying for data.

 

Cloud services aim to solve your problem  extremely flexible no provisioning or

long-term contracts.

Scale up and down with no advanced notice  paying only for the resources you use

in a given month.

1.1. What is Google Cloud Platform?

Google Cloud Platform (often abbreviated as GCP) is a collection of products that

allows the world to use some of Google’s internal infrastructure.

On-demand virtual machines via Google Compute Engine 

Object storage for storing files via Google Cloud Storage.

 APIs to some of the more advanced Google-built technology

Bigtable, Cloud Datastore, or Kubernetes.

Created incredible new technologies.

 MapReduce (the research paper that spawned Hadoop and changed how we handle “Big Data”)

 Bigtable (the paper that spawned Apache HBase), and Spanner.

 Google operates at such a scale that it has many economic advantages

lower prices. immense physical infrastructure,

which means it buys and builds custom hardware to support it

1.2. Why cloud?

Cloud hosting offers a lot of flexibility

How much computing power you need.

Maintenance built in for several products.

No need to manage your own databases, operating systems, and  your own hardware 

1.2.1. Why not cloud?

Google itself. Google’s infrastructural footprint is exabytes of data, hundreds of thousands of CPUs,

A relatively stable and growing overall workload.

In addition, Google is a big target for attacks(for example, denial-of-service

attacks) and government espionage and has the budget and expertise

to build gigantic infrastructural footprints. All of these things together make

Google a bad candidate for cloud hosting.

 

figure 1.2, which shows a more typical company of the internet age, where growth is spiky and

Unpredictable and tends to drop without much notice. In this case, the company bought enough computing capacity (the top line) to handle a spike, which was

 needed up front, but then when traffic fell (the bottom line), it was stuck with quite

a bit of excess capacity.

Figure 1.2. Unexpected pattern of resource consumption

 

1.3. What to expect from cloud services

1.3.1. Computing

Provisioning your machine will be fast. 

Compared to colocated or on-premises hosting will be  significantly faster.

If you turn on a VM right now, you might notice that there’s no mention of payment. 

Typical virtual private server (VPS), where you agree on a set price and purchase the VPS for a full year, making monthly payments.

Google doesn’t mention payment at this time for a simple reason: they don’t know how long you’ll keep that machine running, so there’s no way to know how much to charge you at the end of the month or when you turn off the VM. 

1.3.2. Storage

Storage is necessary.

Storing data is a complicated thing to do. 

Data to be edge-cached to speed up downloads for users on the internet? 

Are you optimizing for throughput or latency? 

 

How many concurrent readers do you need to support?

Abstraction provided by a storage service gives you the ability to configure your storage mechanisms for various levels of performance, durability, availability, and

cost.

The failure aspects of storing data typically disappear. 

A hard drive never fails  and your data is never lost. 

Reduced-availability options - try to download your data and get an error telling you to try again later, paying much less for storage of that class.

Virtual disks in the cloud - choices about how you can store your data, capacity (measured in GB)and in performance (I/O).

Cloud Datastore -  unique to cloud hosting, relying on huge, shared, highly scalable systems built by and for Google.

1.3.3. Analytics (aka, Big Data)

Analytics, see this area called “Big Data.”

Logging and storing almost everything,

Amount of data they have to analyze and use to draw  conclusions is growing.

Enormous amounts of data more manageable, new and interesting open source projects are popping up, such as Apache Spark, HBase, and Hadoop.

1.3.4. Networking

Those pieces to talk to each other, your system isn’t a single system—it’s more of a pile of isolated systems. 

Expect that it has a connection to the internet and that it will be fast enough.

Faster-than-normal network connections, advanced firewalling abilities (where you only allow certain IPs to talk to certain ports), load balancing (where requests come in and can be handled by any one of many machines), and SSL certificate management (where you want requests to be encrypted but don’t want to manage the certificates for each individual virtual machine).

Typical computing stack (such as configure VPNs, set up firewalls with iptables, and balance requests across servers using HAProxy) are all still possible. 

Simplify the common cases, rely on Google’s Cloud Load Balancer to route requests.

 

 

1.3.5. Pricing

Comparing only the dollar cost of buying the hardware from a vendor versus a cloud hosting provider is going to favor the vendor.

Compare costs of hosting infrastructure use  TCO, or total cost of ownership.  the cost of purchasing the physical hardware.

Costs such as human labor (like hardware administrators or security guards), utility costs (electricity or cooling) support and on-call staff who make sure that any software services running build redundancy for your systems so that  data is never lost.

Necessary knowledge to design the system for this configuration. 

1.4. Building an application for the cloud

1.4.1. What is a cloud application?

Difference is in the assumptions made about the application’s architecture.

In a traditional application, we tend to deploy  binaries running on particular servers .

Typical cloud application relies on hosted or managed services whenever possible.

Relies on containers the way a traditional application would rely on servers. 

Cloud application is often much more flexible and able to grow and shrink

1.4.2. Example: serving photos

The old way of doing this was to store the image data in your relational database, and then whenever someone wanted to see the profile photo, you’d retrieve it from the database and return it through your web server:

 as shown in figure 1.3.

Figure 1.3. Serving photos dynamically through your web server

Storing binary data in your database is inefficient. 

Storing the binary data of a photo in your database, you’re putting extra load on the database itself, but not using it for the things it’s good at, like joining relational data together.

Don’t need transactional semantics on your photo (which here, we don’t), it makes more sense to put the photo somewhere on a disk and then use the static serving capabilities of your web server to deliver those bytes, as shown in figure 1.4. 

Figure 1.4. Serving photos statically through your web server

Have a single web server living somewhere inside a data center, serving a photo it has stored locally on its disk.

If someone nearby (for example, in New York) requests that photo, they’ll get a relatively zippy response. 

Someone far away, like in Japan, requests the photo? The only way to get it is to send a request from Japan to the United States, and then the server needs to ship all the bytes from the United States back to Japan.

The answer is edge caching, or relying on a content distribution network. services is that you give them copies of your data in lots of different geographical locations. 

Send a URL pointing to this content distribution provider, returning the photo using the closest available server. 

Cloud hosting is to provide managed services that solve the problem 

managed storage service, which handles content distribution automatically

Figure 1.5. Serving photos statically through Google Cloud Storage

The Cloud is more than a different way of managing computing resources. Managed or hosted services via simple APIs to do complex things

1.4.3. Example projects

To-Do List

To-Do List is nothing more than an application that allows users to create lists, add items to the lists, and mark them as complete.

In short, the To-Do List is a useful demonstration of doing something real, but incredibly simple, with cloud infrastructure.

 

 

InstaSnap

InstaSnap  -  application allows users to take photos or videos, share them on a “timeline” and have them self-destruct.

Focus is on scaling the application to handle hundreds of thousands of requests every single second.

Add up to enormous amounts of data.

Thousands of people to request the same photos at the same time.

E*Exchange

E*Exchange is an application for trading stocks in the United States

Enterprise-grade features of cloud infrastructure concerns about using shared services, with regard to security and access control.

 Summary

• Cloud has become a buzzword, a collection of services that abstract away computer infrastructure.

• Cloud is a good fit if you don’t want to manage data centers and needs change often.

Cloud is a bad fit if your usage is steady over long periods of time.
When in doubt, if you need tools for GCP, start at http://cloud.google.com.