Book Image

Cloud Analytics with Google Cloud Platform

By : Sanket Thodge
Book Image

Cloud Analytics with Google Cloud Platform

By: Sanket Thodge

Overview of this book

With the ongoing data explosion, more and more organizations all over the world are slowly migrating their infrastructure to the cloud. These cloud platforms also provide their distinct analytics services to help you get faster insights from your data. This book will give you an introduction to the concept of analytics on the cloud, and the different cloud services popularly used for processing and analyzing data. If you’re planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations to be kept in mind, and choose the best tools and alternatives for analytics, based on your requirements. The chapters in this book will take you through the 70+ services available in Google Cloud Platform and their implementation for practical purposes. From ingestion to processing your data, this book contains best practices on building an end-to-end analytics pipeline on the cloud by leveraging popular concepts such as machine learning and deep learning. By the end of this book, you will have a better understanding of cloud analytics as a concept as well as a practical know-how of its implementation
Table of Contents (16 chapters)
Title Page
Packt Upsell
Foreword
Contributors
Preface
Index

Emerging cloud technologies and services


With cloud analytics we are having many emerging cloud technologies and services which were not present earlier. We will be discussing about few of them below:

  • Serverless: With serverless computing, developers are only responsible for the code. Developers has to upload code to the cloud and cloud vendor will load and execute it. In responses to different events. These events then triggers in backend some defined functions to perform the given task. Customer in turn pay only for the resources used to run those functions. AWS Lambda, Google Cloud Functions, and Azure Functions are examples of serverless computing services that we have in major cloud vendors.
  • Artificial Intelligence and Machine Learning: Other major cloud technology is artificial intelligence and machine learning. AI and ML are creating waves in cloud vendors as well. Every cloud vendor is trying to integrate as many as AI, ML and Deep Learning services as possible. They are also providing services to build custom models. Google Cloud Machine Learning Engine and Google Cloud Speech API are services available in Google Cloud Platform, whereas in AWS we have Amazon Machine Learning, and AWS has Rekognition.
  • BigData and Analytics: This is not really an emerging technology, but lot of innovation is taking place here. Highly available RDBMS are being introduced, petabyte scale NoSQL databases are in place now, and many other aspects like this are shaping the paradigm of BigData and Analytics. Cloud providers now have a goodnumber ofbigdata services, includingGoogle BigQueryfor large-scaledatawarehousing and Amazon Web Services Elastic MapReduceandMicrosoft Azure Data Lake Analyticsfor processing huge datasets, be it structured or unstructured.

Different ways to secure the cloud

Now, as we have seen the concerns and threats on cloud, let us now look at the different features provided by the cloud vendors to secure the cloud data storage:

  • Secure access: Secure Access is going to help the customer secure access with a username and password, or security keys on a few occasions.
  • Built-in firewalls: Cloud platform also provides built-in firewalls. They not only protect your services with the DoS attack by allowing certain IP address, but can also keep certain ports open.
  • Unique user: You can also create your own unique user using an IAM tool, which is available for free by most cloud vendors.
  • Multi factor authentication: Multi factor Authentication (MFA) is another major leap in providing security. You can use Google's virtual MFA app Authenticator to safeguard your systems.
  • Private Subnet: If you want you can also create your private Subnet and can have more and better control over your network.
  • Encrypted data storage: You can also encrypt your data at rest, which means you can encrypt the data that you have in the cloud. No one in the world will be able to read this data without having an awareness of the decryption method.
  • Dedicated connection option: This is typically a special service in which the cloud vendor will give you access to the edge node and thus the data that you are uploading will bypass the normal internet method to reach a cloud vendor's data center, but it will be sent directly to the cloud vendor.

These features makes the cloud vendors more robust, strong, and very secure!