Google Cloud Concepts Part I

The Google Cloud Platform provides a comprehensive big data solution in a single platform.

The Google Cloud Platform is a full service platform, and it's set up so that you can utilize not only cloud native services, but also open-source tools. It also supports both batch and stream data processing modes.

Google Cloud Platform resources consist of physical resources, like computers and hard disk drives, as well as virtual resources, for example virtual machines. It's global in scope, with resources located around the world in Google data centers. And global distribution has a number of positive implications, including redundancy in the event of failure. The vast reach of the global data centers offered by Google Cloud Platform mean that you can pretty much deploy whatever number of resources you need to without worry. It also means reduced latency, since you can locate your services at a data center close to your end users.

Resources reside in regions or zones. A region is a particular geographical location where resources run. Each region contains one or more zones. For example, the us-central1 region specifies a region in central US that has zones in us-central1-a, us-central1-b, -c, and -f. Resources that reside in a zone, for example resources like virtual machine instances or persistent disks, are called zonal resources. Other resources, like static external IP addresses, are regional. Regional resources can be consumed by any resources within that region. And that includes any zone within that region, while zonal resources are only used by other resources within the same zone.

 

Google Cloud Platform resources are hosted across multiple locations globally. Placing resources in different zones within a region provides isolation from several common types of infrastructure, software, and hardware failures. Placing resources in different regions provides an even higher level of protection against failure. The bottom line is that you can design robust systems using resources that are spread across different failure domains. Compute Engine resources are either global, regional, or zonal. As an example, images themselves are global resources, while disks are zonal. Global resources are accessible by resources regardless of region or zone. So virtual machine instances from different zones can apply the same global image. The scope of a resource indicates how accessible it is to other resources. Though all resources, regardless of whether global, zonal, or regional, must be uniquely named within a project. What this means is that you can't, for example, name a virtual machine instance demo instance in one zone and then try to name another VM within the same project with that same name.

Google Cloud Platform Services

Google Cloud Platform provides a huge number of services.

Some of the more common services include computing and hosting, storage, networking as well as big data.Let's look at computing and hosting first. First, managed application platform. This is offered as Google App Engine and it's a platform as a service offering. It's a somewhat hands off approach in which you allow Google to manage hosting, scaling, and monitoring services. Well, for example, if traffic to your e-commerce website is a dramatic upturn, Google will automatically scale the system for you.

 And container based computing. This is focused on application code rather than deployment and hosting. Google Kubernetes Engine is referred to as containers as a service, and is very mature, and one of the most powerful container orchestration platform. Virtual machines are offered as a service called Google Compute Engine, and this is considered to be a type of infrastructure as a service.

With this type of service, you are responsible for configuration, administration, and monitoring tasks. In other words, Google will make sure that reliable resources are always available and up to date, but it's on you to manage and provision them.

 Now, let's look at storage services. Cloud SQL, which is a database service based on Structured Query Language or SQL, and it offers either MySQL or PostgreSQL databases. Google Cloud Platform offers two types of NoSQL data storage. One is Cloud Datastore and Cloud Bigtable is the other.

Cloud Spanner is a fully managed, highly available, relational database service for mission critical application. Cloud Storage offers large capacity, consistent and scalable data storage. And Compute Engine offers persistent disks. And this is available as the primary storage for your instances with both standard persistent disks, as well as solid state drives.

Now, let's look at networking services. Compute Engine provides networking services for virtual machine instances to use. You can load balance traffic across multiple instances. And there's Cloud DNS as well, which allows you to create and manage domain name system records. And Google Cloud Interconnect is an advanced connectivity service which allows you to connect your existing network to Google Cloud Platform networking resources.

And finally, big data services. First, BigQuery, this is a data analysis service. The data analysis services include custom schema creation, so you can organize your data as you wish. For example, you may have a schema structure in mind using specific datasets and tables.It offers the convenience of large dataset querying using SQL-like commands, so the learning curve is more manageable. It provides for loading, querying, and other operations via jobs. And supports managing and protecting data with controllable and manageable permission.

Cloud Dataflow is a managed service that includes software development kits or SDKs for batch and streaming data processing modes. And Cloud Dataflow is also applicable for extract, transform, load, or ETL operation. Then there's Cloud Pub/Sub. This is an asynchronous messaging service. It allows an application to send messages as JSON structures. And on the receiving end is a publishing unit referred to as a topic. These topics are global resources and what means is that other applications and projects owned by your organization can subscribe to the topic. Thereby receiving those messages in the body of HTTP requests or responses.

Benefits of Google Cloud Platform

Some of the main benefits of Google Cloud Platform include ,

Let's have a closer look at these. Future-proof infrastructure includes factors like live migration. And that means you can move Google Compute Engines instances to nearby hosts, even while they are active and under high load. Google Cloud Platform offers pricing innovations like per second billing and discounts for sustained use. The platform allows you to configure a wide combination of memory and virtual CPU, helping to avoid over-provisioning when sizing hardware for a particular workload. Fast archive restore provides a high throughput for right now restoration of data. Google's load balancer is the same system that supplies load balancing to Google products like Gmail and Google Maps over a global distributive platform. It's super fast and capable of tolerating extreme bites of traffic. You can take advantage of the Google security model, built and maintained by some of the top, application, information and network security experts. This is the same infrastructure that secures Google applications like Gmail and G Suite.

Google maintains a global network footprint, boasting over 100 points of presence, banning over 30 countries. Now let's look at powerful data and analytics as a benefit. You can build distributed services or fast results on the platform. BigQuery, Cloud Datalab and Cloud Dataproc. These are the same services that Google uses. So queries that traditionally take hours or days, can now be performed in a fraction of the time. Google Cloud Platform offers powerful applications and tools for working with big data, with data processing tools like Cloud Dataflow, Cloud Pub/Sub, BigQuery, and Cloud Datalab. Making it easier to use extreme volumes of data to deliver results.

Again, these are the same products that Google itself uses. And Google Cloud Machine Learning provides access to powerful deep learning system that google uses for services like Google Translate and Google Photos, as well as voice search. With respect to serverless computing, there are no upfront provisioning costs. So resources are allocated dynamically as needed. You simply bring your code and data. It's full management of servers and eliminates the repetitive tasks and potential errors that are inherent in tasks like scaling clusters and applying security badges. With automatic scaling and dynamic provisioning of resources, you pay only for what you use.

Let's consider a couple of use cases for a serverless computing. Take for example, web backend. You employ Google's App Engine with the highly scalable NoSQL Cloud Datastore database for a full scale, powerful backend infrastructure. Or Internet of Things or IoT device messaging, combined the real time geo-redundent Cloud Pub/Sub messaging service, with Cloud Dataflow serverless stream and batch data processing. When considering extract transform and load or ETL, we could combine Cloud Dataflow again for stream and batch data processing, with BigQuery for serverless data warehousing. [Other examples of Serverless Use Cases are shown.

 

Now one of the other benefits, customer-friendly pricing. As pointed out earlier, you do not have to commit to a specific deployment size, so no upfront costs are involved. You pay as you go and with per second pricing, that means that you pay for services as you require them. So you don't have to maintain a mountain of hardware and have that hardware sitting there idle. And you stop paying when you stop using a service, with no termination fees. Google Cloud Platform offers, as another benefit, data center innovation. For example, high performance virtual machines for fast and consistent performance.

Google's global network provides fast networking, performance, strong redundancy and high availability. Live migration technology means that maintenance of virtual machines is transparent, never requiring down time for scheduled maintenance. Google maintains very high security compliance and standards, providing some of the most secure infrastructure on earth. And Google builds its data centers with energy efficiency top of mind. In fact, Google is the first major Internet services organisation to obtain ISO 50,000 I certification. And Google has reportedly been carbon-neutral for over a decade. Now, consider security.

Google security model is an end-to-end process. Google uses practices and controls to secure data access and when retired, hard disks that contain customer information undergo a data destruction process. With only a few exceptions, customer data stored at rest is always encrypted on Google Cloud Platform. The encryption is automatic and transparent, so no customer intervention or action is required. Google's secure global network helps to improve security of in transit data. And the combination of cloud interconnect and managed VPN, means that you can create encrypted channels from an on-prem private IP environment, to Google's network. In addition to that, Cloud Security Scanner assists app engine developers to identify common vulnerabilities.

Google Cloud Platform also allows the configuration of user permissions at the project level, for full control of who has access to what resources and at what level. Using tools like Google Cloud logging and Google Cloud monitoring, simplifies the collection and analysis of request logs, as well as the monitoring of infrastructure services availability.

Comparing GCP and Other Models

When you're talking about cloud services suppliers, there are really three main suppliers. That's Amazon Web Services, Google Cloud Platform, and Microsoft Azure. The major differences from platform to platform include pricing. And one thing that you should keep in mind when considering pricing is this. How to calculate cost? For example, the pricing for Amazon's EC2 and Azure's Virtual Machines scalable computing service can get pretty complicated. While Google's scalable computing service is perhaps a little less flexible, but the pricing, way more straightforward. Another major difference lies in how these vendors name and group the services that they offer.

  

Compute offerings

With respect to scalable computing on demand, Amazon Web Services has its Elastic Compute Cloud, or EC2. While Google Cloud Platform offers Compute Engine, and Azure has Virtual Machines and Virtual Machine Scale Set. For web and mobile apps, we have AWS Elastic Beanstalk and GCP, and I'll refer to Google Cloud Platform hereafter as GCP. GCP's App Engine, and Azure offers Webs Apps and Cloud Services. For software container management, Amazon Web Services has ECS. And ECS is Amazon's EC2 container service, while EKS is Amazon Elastic Container Service for Kubernetes. Google Cloud Platform provides the Google Kubernetes Engine. And I'm quite familiar with that having a lot of personal experience with GKE, and I can tell you it is very powerful, very flexible, and fantastic. Azure offers AKS, which is Azure Container Service, and Azure Container Instances. 

  

 

For storage offerings, we have object storage. So Amazon Web Services offers Simple Storage Service, or S3. GCP has Cloud Storage, while Azure has Blob Storage. As far as archiving, or as it's known, cold storage, is concerned, AWS offers Glacier and Data Archive. GCP has Cloud Storage Nearline. And Azure offers Backup and Archive. With respect to content delivery networks, AWS offers CloudFront. GCP offers Cloud CDN, and Azure has its Content Delivery Network.

Now let's look at analytics offerings. For big data, AWS offers EMR and Athena. While GCP offers BigQuery, Cloud Dataflow, Dataproc, Datalab, and Pub/Sub. Azure has HDInsight and Data Lake Analytics. For BI, or business intelligence, AWS offers QuickSight. GCP offers Data Studio, while Azure has Power BI. Now, you might be thinking, well, Power BI, isn't that an installable application? Yes, it is an installable application. There are applications that are installable on desktop, or on servers even. But they connect to cloud resources very readily and easily. That's why I'm including those here. With respect to machine learning, AWS has Amazon Machine Learning, or AML. Google has Cloud Machine Learning, and Azure offers Azure Machine Learning.

Now let's consider briefly locations offerings. So really you should try to choose your data center close to users, because it reduces latency and provides better user experience. I mean, that goes without saying, if you're involved in any capacity in networking, in administration, you already know that. So here's the thing, AWS has the most global coverage, but unfortunately there's no coverage in Africa at this point. Google Cloud Platform has good coverage in the US, but not so good in Europe and Asia, and there's none in South America or Africa at this time. But knowing Google, I'm pretty sure that they are in the process of planning those right now. And as far as Azure goes, really they have the second best global coverage behind AWS, but again, there is no coverage in Africa.

GCP Locations https://cloud.google.com/about/locations/#global-products

AWS Locations https://aws.amazon.com/about-aws/global-infrastructure/

Azure Locations https://azure.microsoft.com/en-gb/global-infrastructure/regions/

Login https://cloud.google.com/

Developed by: Google Platform: Google App Engine, Google Compute Engine, Google Cloud Datastore, Google Cloud Storage, Google BigQuery, Google Cloud SQL

Initial release: April 7, 2008; 10 years ago

License: Proprietary Written in: Java, C++, Python, Go, Ruby

In the beginning, we need to apply a Google Cloud Platform (GCP) account and the new client would have $300 credit to spend in the first 12 months.

Once we logged in to the GCP console, we need to create a new project in order to use the GCP services. Simply click the New Project button and type the project name. At the same time, it would assign a unique project ID for your project which we need to use to access the GCP in terminal later.

Win Every Interview with these 6 Steps

1.    Predict the future. You can anticipate 90% of the interview questions you’re going to get. Three of them are listed below, but it’s an easy list to generate.

“Why do you want this job?” “What’s a tough problem you’ve solved?” If you can’t think of any, Google “most common interview questions.” Write down the top 20 questions you think you’ll get.

2.    Plan your attack. For EVERY question, write down your answer. Yes, it’s a pain to actually write something. It’s hard and frustrating. But it makes it stick in your brain. That’s important. You want your answers to be automatic. You don’t want to have to think about your answers during an interview. Why not? Keep reading.

3.    Have a backup plan. Actually, for every question, write down THREE answers. Why three? You need to have a different, equally good answer for every question because the first interviewer might not like your story. You want the next interviewer to hear a different story. That way they can become your advocate.

4.    Prove yourself. Every question should be answered with a story that proves you can do what you’re being asked about. “How do you lead?” should be answered with “I’m a collaborative/decisive/whatever leader. Let me tell you about the time I ….” Always tell a story or have facts to prove you are what you say you are. More on how to construct and tell these stories in a future article.

5.    Read the room. All that brainpower you’re not using to desperately come up with answers to questions? Look around. Focus on the interviewer. In the first 10 seconds, is there anything in their office, or about them, you can notice and use to forge a connection? A book on a shelf? A family photo? A painting? Read the interviewer: is their body language open or closed? Are they tired and should you try to pep them up? Do they like your answer or should you veer in another direction?

6.    Make it to Carnegie Hall. How do you get to Carnegie Hall? Practice. Same goes for getting a job. When I was in my second year of job hunt, I practiced my interview answers -- out loud -- until I could tell each story smoothly, without thinking about it (but not so smoothly that I was bored with the re-telling). My roommate walked in one day to find me sitting on the futon reciting why I thought I was a great leader again and again. He figured I was stuck in some kind of Stuart Smalley-like self-help loop. But I got 2 job offers from 5 companies (that’s another story) and was on track to get another 1 before I stopped interviewing. How is that possible? Practice.

Everyone deserves an amazing job. I hope this helps you get one.

           Courtesy :Laszlo Bock SVP,  People Operations at Google

Microsoft Powerpoint 2013 Shortcuts

Self-Promotion

Hey Friends today I am quoting a wonderful article By Susan Wilson Solovic it is about how savvy professional women promote themselves. 

Susan Wilson Solovic is a women of many talents, she is an award winning entrepreneur, media personality , amazon top 100 bestselling author, sought after keynote speaker etc.

Solovic has written four bestselling books: “It’s Your Biz”, The Girls’ Guide to Power and Success; Reinvent Your Career; and The Girls’ Guide to Building a Million-Dollar Business.

Perhaps you're one of those people who gets personal satisfaction out of a job well done. Maybe you sincerely believe that if you work hard and produce a quality product, the rewards and recognition will come. Unfortunately, things don't work that way.

Talent and brilliance alone won't get you to the top. You need to launch a personal marketing campaign for yourself. The goal is to "wow" them.

We women aren't good at tooting our own horns because we're taught that good girls don't brag. While boys grow up vying for the limelight and learning to one-up each other, girls are taught to share the glory. We aren't supposed to be the center of attention. Therefore, in business, we sadly watch as we're passed by time and time again for promotions, high-visibility assignments, committee chairs and so on because we don't draw attention to our accomplishments.

"One woman I used to work with was always tooting her own horn, and I didn't like it. Then, one day I realized that I was impressed with her track record. Subsequently, I realized you really have to do your own PR work. For a lot of women, including myself, that's hard. But you really have to do that if you want people to understand what your contributions are," says Juanita Weaver, a creativity consultant based in Washington, D.C.

"Nobody knows you better than you. There's nothing wrong with letting your manager or others know about your successes. But as women, not only do we fail to draw attention to our accomplishments, but we tend to downplay them," says Sharon Hadary, executive director of the National Foundation for Women Business Owners, based in Washington, D.C.

Self-promotion can be accomplished in an artful and tasteful manner. You don't want to appear too opportunistic, nor do you want to become a legend in your own mind. The best advice is to watch and learn from others.

Let the Right People Know

Does you boss's boss know what a great job you're doing? Does your sales contact keep his or her supervisors apprised of your company's performance record? Will anyone be aware of your accomplishments if your supervisor or company contact leaves or gets promoted? If you can't answer yes confidently to these questions, then you aren't doing a good job of marketing yourself. You need an action plan.

"What I try to do personally is document what I do, and let people know about it. You have to recognize that it's okay to say you're good at something, and by documenting things you've done, you can show them on paper," says Catherine Garda Newton, a former IBM executive. "I also regularly update my resume because it forces me to look back at what I've done and keep it firmly in my mind. I also can evaluate better whether I'm moving toward where I want to go."

Seek Ways to Tell Your Story

If your company has staff meetings, always be prepared to highlight your results. Utilize internal memos and weekly or monthly progress reports as methods of keeping associates informed of your accomplishments. Use opportunities to remind your customers of your performance record. Rather than bragging, you'll appear competent and professional for keeping everyone informed.

Be Generous with Your Praise

Make certain your business associates, employees or team members receive recognition for a job well done. When you're quick to sincerely praise the good work of others and allow them to bask in the limelight, they'll readily do the same for you. You won't have to say a thing about yourself because your associates will enthusiastically carry your banner.

Use External Sources

Enhance your credibility and stature by writing an article for a trade journal or business publication. Establish yourself as a resource with the media -- someone they can call when they need an authority to quote. Send out news releases announcing your business successes. Share published articles with business associates and customers. Of course, always make certain you have permission to copy printed materials so you don't infringe on a publication's copyright.

Write a Dazzling Bio

Create a personal bio that will wow readers. If you aren't a good writer, hire someone who can do it for you. Even though I've been a marketing professional for more than 20 years, I hire marketing professionals to write for me. These professionals have the objectivity to make me sound great. If you choose to do it yourself, make certain that you highlight your achievements and experience as well as any awards or special recognition you may have received. The goal is to look like the superstar you are.

There's a delicate balance when it comes to self-promotion, and you don't want to be guilty of overkill. But when used appropriately, a personal marketing campaign can create magic for you and help you get where you want to go. Marketing yourself is like marketing your business -- if no one knows about your product, who will buy it?

7 C’s of Communication

Clear: Your messages need to be clear if they are to be effective.

Concise: If you want your messages to be read by busy people, make them brief. Say what you need to say, and say no more (while maintaining goodwill, of course). Remove all words phrases and sentences that serve no purpose. You can also eliminate wordiness by substituting one word for wordy, overused expressions.

Concrete: You have a choice in your writing to use concrete (specific) or abstract (vague) words. They both have a place in business writing. However, concrete terms are typically more accurate and, in some cases, more believable.

Correct: Correctness in business writing includes spelling, grammar, punctuation, and format. For spelling, punctuation, and grammar, you should keep a dictionary and a writer's guide at your desk.

Coherent: Messages need to "hang together." Ideas need to flow from one to the next through smooth transitions. You can achieve this by outlining your messages, writing simple sentences and focusing each paragraph on one idea. You can also improve the coherence of your message through parallel structure, connecting words and phrases, and guide posts.

Complete: Check to be sure that your message is complete. Have you included all the information you need to ensure that the other person can do a complete job or make a reasonable decision?

Courteous: Your message should be positive-building goodwill and focused upon the reader. Watch gender specific language and always use proper titles.