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Google Cloud Platform vs. Microsoft Azure

This video compares Microsoft Azure to Google Cloud Platform, covering the following topics in about five minutes:

  1. Complexity versus simplicity
  2. Innovation
  3. Performance, reliability, and cost
  4. Opinions from top research firms
  5. And finally a summarization of benefits 

(This is an edited, high-level transcript.) Let’s start from the top. Complexity is Microsoft's middle name. Pricing is difficult, licensing is difficult, and the software is designed in a manner that makes it challenging to use. Compared to Azure, Google Cloud Platform is simple and elegant (but not simplistic).

Complexity vs. Simplicity

On Microsoft Azure, there's a tendency to productize every variation of a service. For example, if you need a load balancer, there are a number of different products that provide various load balancing services and each one has a separate SKU and is categorized as a completely different product. On GCP, you simply select ‘load balancer’ and walk through a series of steps to configure that load balancer using options and parameters.

A similar scenario exists on the storage side. In terms of user interface design, Azure blades are designed to make the tool easy to use but often it makes things more cumbersome and complex. In the video, we show that as we continue to click into different options, we eventually run out of screen space. If we continue to click forward we lose some of the blades to the left and it gets complicated to find our way back or to remember where we started from. By contrast, GCP provides a single pane of glass for your projects. You can configure the dashboard and see all your infrastructure and services at a glance. Let’s say you want to add a new service or resource to your infrastructure. When you click the menu, the main screen darkens a bit, making it easy to keep your attention in the right place. It's a very simple design but it's much more elegant and easy to use.


According to Doug Cutting, Founder of Hadoop, ‘Google is living a few years in the future and sends the rest of us messages.’ Google is one of the most prolific contributors to the open source community. Take Kubernetes. Kubernetes has become a buzzword in the industry. Google created this product as a way to manage and orchestrate containers and since, it has become a standard that both Microsoft and Amazon have implemented.

Another example is Cloud Spanner. (If you're not familiar with the CAP Theorem in terms of database design and practice, take a look here.) Cloud Spanner is a unique offering in the marketplace with a horizontally scalable, strongly consistent, globally scoped relational database.

Google Cloud Platform's AI features are years ahead of what others offer. Google created TensorFlow, another open source project. TensorFlow is a core component of machine learning systems. Google also created TPUs to process tensors more efficiently and quickly. These are proprietary processing units that speed up your machine learning work significantly.

Performance, reliability, and cost

Krystallize Technologies has created a service capability measure that looks at performance, reliability, and cost. From the charts shown in the video, we notice that Google has the best service capability across the board. It also shows that Google’s performance and costs are the most predictable and the most reliable of all these platforms. As we look at total reported downtime, we see Azure had (by far) the most reported downtime of all the three platforms. In the cloud, networking is a critical factor in terms of performance. Looking at more data, we notice that Google leads the way on maximum networking throughput. In addition, network latency is a measure of responsiveness. The minimum average latency of Azure exceeds that of GCP by a long shot.

We want to hear from the research firms!

What does Gartner have to say about all this? One Gartner Analyst said, ‘Enterprises frequently lament the quality of Microsoft technical support (along with the increasing cost of support) and field solution architects.’ Another Gartner Analyst states that one of the downsides of Azure has been a series of outages over the years, including a major global outage in May of 2019.

Google Cloud has proved itself in a number of studies over the years. Of these, are The Forrester Wave™: Data Security Portfolio Vendors, Q2 2019, Gartner’s ‘2019 Magic Quadrant for Full Life Cycle API Management’, as well as Gartner’s ‘2020 Magic Quadrant for Cloud AI Developer Services’. From a data security perspective, Google leads in terms of strong strategy and a strong ability to deliver. With their Apigee product, Google is by far and away the leader in Full Lifecycle API Management. In modern computing, APIs are often used as a way to integrate legacy systems and cloud systems or on-prem systems.

To summarize: Why Google Cloud Platform?

Google may very well be the most innovative cloud company on the planet. Big Data is in its blood; the history of Google as a company began with a mission to organize the world's data and make it available to everyone. Google has been dealing with Big Data challenges since the day it was born. GCP is also the most reliable cloud platform with the most consistent service capability, and the most predictable cost model. Google also has one of the largest private global networks on the planet with the best performance and throughput and the lowest latency. Finally, Google offers the best cost model all up, with tremendous predictability, and many ways to optimize your spend and save money while maximizing the value you get from a cloud platform.

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Thank you for taking the time to watch this video! If you have any questions feel free to reach out to Cloudbakers. You can speak to our experts directly at care@cloudbakers.com.

Originally published on June 12, 2020

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