On Cloud9

I have long reticule cloud as mere hype. I have primarily worked in IT service Industry where applications are huge, they run on huge mainframe or UNIX server which are hosted in organizations premises. Since I started my career with healthcare provider, I know how much important data security is for any enterprise.

Also, upgrading server OS version to latest version itself used to be big task, usually companies delayed upgrade for the fear of breaking something unknown. Main goal used to be ” Don’t fix if its not broken”. his lead to OS upgrade to the very last moment when vendor decides to stop supporting older version. Nonetheless there used to be many applications which continued to run on unsupported OS version, and in some cases, product itself is out of support.

In such a cases I always used to wonder under which business case, organizations would like to migrate to cloud and loose control over infra.

 

Cloud does of easy scalability and infra support but my understanding was that, this is concern for mostly smaller organizations or start ups. For big corporations, spending money on scaling infra and acquiring experts to support is not a challenge.

However I do recognize now that many companies, not just new age companies like Netflix etc are using cloud, even the older generation Telecom companies are looking to use cloud for some of its product. It could be private could or hybrid cloud but still, there is some adoption.

obvious leaders in cloud as of now is AWS, followed by Azure by Microsoft. Google cloud platform (GCP) is distant third, however if you are interested in big data and ML services along with cloud, GCP is the go to option.

Currently, I am working in Telecom domain, however I think, I need to move from Telecom to cross domain area like Cloud, Machine Learning , Data Science, NLP. Considering this, I have decided to get certified  in GCP Cloud Architect.

For next couple of months, I will be focusing more on cloud technologies, starting with Virtualization to Cloudification. These articles will be my notes for future reference and can be supporting/guiding articles for fellow learners and professionals.

Understanding Google Cloud platform and Services

Google cloud and varied services provided on top of it are very confusing to comprehend. It’s not just with google but you can visit AWS and azure, it’s very confusion, rather I would say, since each cloud provided is using their own nomenclature for their services, it becomes difficult to remember what does what. Of course once you start using it, it will become natural to you but when you are getting started, this is frustrating. I have just completed a course How Google does Machine Learning so I thought let me make very simple note for myself and for other to keep track of it.

There are many services which are offered by Google but for beginners everything is not needed to get started, so I will split this post in two parts.

Part-1 : Getting started

Google Cloud Platform is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search and YouTube.

Compute EngineInfrastructure as a Service to run Microsoft Windows and Linux virtual machines.

App EnginePlatform as a Service to deploy Java, PHP, Node.js, Python, C#, .Net, Ruby and Go applications.

Cloud Storage – Object storage with integrated edge caching to store unstructured data.

Cloud Datalab – Tool for data exploration, analysis, visualization and machine learning. This is fully managed Jupyter Notebook service.

BigQuery – Scalable, managed enterprise data warehouse for analytics.

Cloud Natural Language – Text analysis service based on Google Deep Learning models.
https://cloud.google.com/natural-language/

Cloud Speech-to-Text – Speech to text conversion service based on machine learning.
https://cloud.google.com/speech-to-text/

Cloud Text-to-Speech – Text to speech conversion service based on machine learning.
https://cloud.google.com/text-to-speech/

Cloud Translation API – Service to dynamically translate between thousands of available language pairs
https://cloud.google.com/translate/

Cloud Vision API – Image analysis service based on machine learning
https://cloud.google.com/vision/

Cloud Video Intelligence API– Search and discover your media content with Cloud Video Intelligence
https://cloud.google.com/video-intelligence/