Organizations today are increasingly migrating to the cloud to become more cost-efficient, agile, and innovative in operating their businesses. This has opened up huge job opportunities for professionals with cloud skills. In this article, we will compare the leading cloud vendors – AWS vs Azure vs Google Cloud. We will take a closer look at the top three cloud platforms and their key differences to help you decide which one should you learn.
In the midst of this pandemic, what is allowing us unprecedented flexibility in making faster technological advancements is the availability of various competent cloud computing systems. From delivering on-demand computing services for applications, processing and storage, now is the time to make the best use of public cloud providers. What’s more, with easy scalability there are no geographical restrictions either.
Machine Learning systems can be indefinitely supported by them as they are open-sourced and within reach now more than ever with increased affordability for businesses. In fact, public cloud providers are increasingly helpful in building Machine Learning models. So, the question that arises for us is – what are the possibilities for using them for deployment as well?
Model building is very much like the process of designing any product. From ideation and data preparation to prototyping and testing. Deployment basically is the actionable point of the whole process, which means that we use the already trained model and make its predictions available to users or other systems in an automated, reproducible and auditable manner.
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Having taken over our daily communications almost entirely, the web is constantly evolving and expanding. With this continuous expansion, it provides you with more and more data that you consume daily. However, all the information that appears on the web, every like, subscription, tweet, downloaded video, or uploaded vlogs, making all of this possible requires a highly sophisticated computational process working behind it, constantly.
The smooth functioning of the web has more to it than just the computational procedure. Current web services operate through a solid and intricate network of RAM, containers, database engines as well as machine learning skills.
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The world of data analytics and technology have been dramatically altered by cloud computing. The two companies which are known for providing tremendous cloud computing technologies are- Google Cloud Platform and Amazon Web Services.
This artcile highlights the comparison between these big companies.
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A multi-cloud approach is nothing but leveraging two or more cloud platforms for meeting the various business requirements of an enterprise. The multi-cloud IT environment incorporates different clouds from multiple vendors and negates the dependence on a single public cloud service provider. Thus enterprises can choose specific services from multiple public clouds and reap the benefits of each.
Given its affordability and agility, most enterprises opt for a multi-cloud approach in cloud computing now. A 2018 survey on the public cloud services market points out that 81% of the respondents use services from two or more providers. Subsequently, the cloud computing services market has reported incredible growth in recent times. The worldwide public cloud services market is all set to reach $500 billion in the next four years, according to IDC.
By choosing multi-cloud solutions strategically, enterprises can optimize the benefits of cloud computing and aim for some key competitive advantages. They can avoid the lengthy and cumbersome processes involved in buying, installing and testing high-priced systems. The IaaS and PaaS solutions have become a windfall for the enterprise’s budget as it does not incur huge up-front capital expenditure.
However, cost optimization is still a challenge while facilitating a multi-cloud environment and a large number of enterprises end up overpaying with or without realizing it. The below-mentioned tips would help you ensure the money is spent wisely on cloud computing services.
Most organizations tend to get wrong with simple things which turn out to be the root cause for needless spending and resource wastage. The first step to cost optimization in your cloud strategy is to identify underutilized resources that you have been paying for.
Enterprises often continue to pay for resources that have been purchased earlier but are no longer useful. Identifying such unused and unattached resources and deactivating it on a regular basis brings you one step closer to cost optimization. If needed, you can deploy automated cloud management tools that are largely helpful in providing the analytics needed to optimize the cloud spending and cut costs on an ongoing basis.
Another key cost optimization strategy is to identify the idle computing instances and consolidate them into fewer instances. An idle computing instance may require a CPU utilization level of 1-5%, but you may be billed by the service provider for 100% for the same instance.
Every enterprise will have such non-production instances that constitute unnecessary storage space and lead to overpaying. Re-evaluating your resource allocations regularly and removing unnecessary storage may help you save money significantly. Resource allocation is not only a matter of CPU and memory but also it is linked to the storage, network, and various other factors.
The key to efficient cost reduction in cloud computing technology lies in proactive monitoring. A comprehensive view of the cloud usage helps enterprises to monitor and minimize unnecessary spending. You can make use of various mechanisms for monitoring computing demand.
For instance, you can use a heatmap to understand the highs and lows in computing visually. This heat map indicates the start and stop times which in turn lead to reduced costs. You can also deploy automated tools that help organizations to schedule instances to start and stop. By following a heatmap, you can understand whether it is safe to shut down servers on holidays or weekends.
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Cloud computing has brought about a new wave of change in the industry, especially for enterprises and organizations that are continually growing. Thanks to cloud computing platforms, you no longer need to struggle with on-premise servers’ limitations and manage a complicated hardware infrastructure. Cloud computing takes care of all your enterprise storage and computing needs in a much more cost-efficient and secure manner.
Globally, the cloud computing market is dominated by three giants – Azure, Google Cloud, and AWS. Today, we’re going to pit Google Cloud and AWS to get a neck-to-neck comparison of these two cloud computing platforms.
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