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True Economics of Cloud Computing: Part 1: What It Really Means to be “Agile”?

By Ajinkya Shetty - July 26, 2019

Over the past several years, several companies have altered their IT strategies to shift an increasing share of their applications and data to cloud infrastructure and platforms. Organizations have faced a constant struggle of achieving a quicker time-to-market, building customer experience, and improving agility while addressing governance and monetary challenges. Cloud technology offers a flexible operating model while allowing organizations to save time and money, improve operations, and encourage innovation.

Demands for scalable and secure access to applications, spikes in network loads, and a move towards pay-per-use pricing have all nurtured a demand for cloud technology. Cloud deployments rapidly multiply across enterprises today, serving as the IT infrastructure driving new digital businesses. According to Cisco, by 2021, 94 percent of workloads and compute instances will be processed by cloud data centers; traditional data centers will process 6 percent.

What is Agility?

In a cloud computing context, agility often refers to developing, testing rapidly, and launching applications that drive business growth in a constantly changing IT environment. Cloud technology offers businesses a key means of promoting agility and is a vital tool in the enterprise push toward better adaptability.

Let’s explore some key benefits of agility in the cloud:

Greater Business Continuity and Flexibility: Cloud services can be rolled up or down as per business requirements without increasing the pool of IT equipment that a company must purchase and manage. The pay-per-use flexibility of the cloud allows end-users to scale or downscale quickly based on the demands of the business. For example, you can start with a 10 node cluster and easily increase to 50 nodes as your requirements change.

Infrastructure Agility: Cloud allows companies to decrease their time to provision and de-provision IT infrastructure significantly. You have the ability to start small, and scale up as needed and, if you face a scenario where you need to cut back, it’s easy to make that happen. While a physical server could take days or weeks to procure and provision, a cloud server takes minutes. Using Apache Hadoop, Spark, and Hive in the cloud enables growth of data processing power in real-time. Faster time to market means faster time to revenue.

Automated allocation of resources: Cloud computing distributes workloads and shares resources to achieve coherence and economies of scale. It simplifies provisioning, de-provisioning, and re-deploying resources through automation and easy-to-use APIs and web consoles. The time an IT systems administrator spends on managing and supporting cloud infrastructure is significantly reduced compared to that seen in a physical data center.

Up-to-date technology upgrades:The refresh cycles for an upgrade can be long as plenty of dependencies needs to be planned out — infrastructure, operations, and software. However, today, cloud providers add services from vendors that make it easier to upgrade without impacting your overall solution. Environments with cloud data lake architectures can upgrade to a new version of Hadoop in a matter of days.

Hadoop in the Cloud

Companies have now started to understand how much-unstructured data they need to analyze over the coming years. Thus, letting a cloud provider manage scalability problems is likely to be more cost-effective and convenient. Scalability and elasticity are top priorities as up-front capacity planning is nearly impossible. Hadoop platforms, typically, are designed to ingest unknown data sets. Hadoop as a service can help improve the speed of creating data lakes.

Whether you are fork-lifting traditional Hadoop platforms on Cloudera/Hortonworks and hosting them on the cloud, migrating them to cloud-native big data services like EMR, or undertaking a modernization project for your on-premise ERP/SAP HANA system with new applications that run on the cloud, you need to ensure that your cloud data strategy provides flexibility and agility for your business needs.

Conclusion

In a highly competitive marketplace, where time-to-market is key, and the cost of doing business is always a matter of concern, you need to choose the right cloud service provider the first time around. Consider a data management solution that enables you to freely move data and applications across clouds and between cloud and on-premise environments.

Clairvoyant’s multi-cloud-enabled services allow you to achieve a seamless, efficient, and cost-effective transition to conducting your business in the cloud. Our proven design and deployment expertise ensures that you gain a dynamic infrastructure solution at minimum risk without a cloud vendor lock-in. Besides this, our data management solution offers the ability to gain insights via built-in predictive analytics, machine learning, and optimized processes. We deliver fully managed implementations of Hadoop and Spark in the cloud that meets the rigorous demand for enterprise-class reliability, scalability, and security.
To get the best cloud based services, reach out to us at Clairvoyant.

For more information or further queries, please email us at sales@clairvoyantsoft.com or call us at (623)282–2385. 

References:

Hardy T, Embracing Architecture Flexibility And The Cloud. Retrieved from: https://www.digitalistmag.com/cio-knowledge/2018/07/23/embracing-architecture-flexibility-cloud-imperative-3-06178329

Cognizant Whitepaper, Switch On Cloud Computing for More Agility, Flexibility and Cost Savings. Retrieved from: https://www.cognizant.com/whitepapers/Brochure-Cloud-Services.pdf

Cisco White Paper, Global Cloud Index: Forecast and Methodology 2016–2021. Retrieved from: https://www.cisco.com/c/en/us/solutions/collateral/service-provider/global-cloud-index-gci/white-paper-c11-738085.html

Author
Ajinkya Shetty

Tags: Cloud Services

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