“Edge” isn’t a new thing to most technologists. However, if you think it just relates to Internet-of-Things (IoT), it’s time to take a fresh look. Whether you’re at a startup to established enterprise, edge computing has become more relevant. Why? You’re generating data in more places: SaaS systems, public clouds, remote devices, on-premises, and partner data centers. You’re also creating systems that execute logic on mobile phones or vehicles, then at the CDN, and finally in your application. These distributed systems solve one set of problems, and can create another set of problems. At InfoQ, we sought to learn more from the people building and evaluating these edge-powered systems.
This series of articles touches on many of the key aspects of designing and delivering a solution that uses edge computing. We hope you enjoy it, and that it sparks new ideas and debates with your colleagues.
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.
#cloud computing services #all #hybrid cloud #cloud #multi-cloud strategy #cloud spend #multi-cloud spending #multi cloud adoption #why multi cloud #multi cloud trends #multi cloud companies #multi cloud research #multi cloud market
The moving of applications, databases and other business elements from the local server to the cloud server called cloud migration. This article will deal with migration techniques, requirement and the benefits of cloud migration.
In simple terms, moving from local to the public cloud server is called cloud migration. Gartner says 17.5% revenue growth as promised in cloud migration and also has a forecast for 2022 as shown in the following image.
#cloud computing services #cloud migration #all #cloud #cloud migration strategy #enterprise cloud migration strategy #business benefits of cloud migration #key benefits of cloud migration #benefits of cloud migration #types of cloud migration
It sometimes makes sense to treat edge computing not as a generic category but as two distinct types of architectures: cloud edge and device edge.
Most people talk about edge computing as a singular type of architecture. But in some respects, it makes sense to think of edge computing as two fundamentally distinct types of architectures: Device edge and cloud edge.
Although a device edge and a cloud edge operate in similar ways from an architectural perspective, they cater to different types of use cases, and they pose different challenges.
Here’s a breakdown of how device edge and cloud edge compare.
First, let’s briefly define edge computing itself.
Edge computing is any type of architecture in which workloads are hosted closer to the “edge” of the network — which typically means closer to end-users — than they would be in conventional architectures that centralize processing and data storage inside large data centers.
#cloud #edge computing #cloud computing #device edge #cloud edge
Global web services are largely served from public clouds today. As they reach the cloud edge, they are handed over to telco wireline and mobile wireless access networks for delivery to end users.
While this delivery approach has been adequate as a best-effort service delivery, mission-critical services — with stringent latency requirements in the range of milliseconds or lower — cannot work this way, since cloud to client latency can easily exceed tens of milliseconds on average and may fluctuate wildly depending on network loads. New emerging services that require ultra-low latency — such as autonomous driving, massive machine-type communications for smart infrastructure and manufacturing, as well as Internet of Things (IOT) — have led to the emergence of edge cloud and associated computing infrastructure to provide accelerated delivery with machine learning intelligence.
Although there is a great deal of consensus that cloud edge is where more intelligent processing is needed, there is every little consensus of where to build these edge infrastructures and if they are synonymous with 5G Mobile Edge Computing (MEC). Further, while 5G is expected to play a pivotal role in connecting edge and client devices into the cloud, many forms of wireline and wireless radio technologies are expected to play a role in the broad content of Internet of Things (IOT).
#cloud services #edge / iot #edge cloud #cloud
In this Lab, we will configure Cloud Content Delivery Network (Cloud CDN) for a Cloud Storage bucket and verify caching of an image. Cloud CDN uses Google’s globally distributed edge points of presence to cache HTTP(S) load-balanced content close to our users. Caching content at the edges of Google’s network provides faster delivery of content to our users while reducing serving costs.
For an up-to-date list of Google’s Cloud CDN cache sites, see https://cloud.google.com/cdn/docs/locations.
Cloud CDN content can originate from different types of backends:
In this lab, we will configure a Cloud Storage bucket as the backend.
#google-cloud #google-cloud-platform #cloud #cloud storage #cloud cdn