Welcome!

@CloudExpo Authors: Pat Romanski, Elizabeth White, Liz McMillan, Yeshim Deniz, Zakia Bouachraoui

Related Topics: @CloudExpo, Microservices Expo, Containers Expo Blog

@CloudExpo: Blog Feed Post

Breaking the Storage Array Life Cycle with Cloud Storage: Part III

How do you leverage tiers of cloud storage in a manner that integrates seamlessly into your existing storage infrastructure?

While Part I and Part II of this series spelled out some of the economic benefits and deployment models of cloud storage, today’s installment will take a more pragmatic look at how to deploy cloud storage in environments that already have traditional storage infrastructure. While replacing traditional storage with cloud storage will break the traditional storage array life cycle, a complete “forklift” replacement may seem a bit of a stretch.

A more conservative approach might be to identify data suitable for cloud storage such as secondary copies, backups, off-site data and/or archives. Interestingly, archives are often stored on traditional onsite storage to make them easily accessible to meet compliance requirements. However, looking at the chart below, you can see that ESG’s research estimates a very rapid growth rate for archive data, approximately 56% per year.

Archive data growth

With literally hundreds of thousands of Petabytes of archives to store over the next few years, the benefits of offloading archives or infrequently accessed data from traditional storage are numerous.  In fact, transitioning this data to cloud storage can extend the traditional life cycle of storage arrays beyond the typical 3-5 year time frame. Imagine a 6-10 year storage array life cycle instead. That would result in a reduction of capital investment in storage infrastructure by half and introduce a significantly more efficient just-in-time, pay-as-you-go model.

So how do you leverage tiers of cloud storage in a manner that integrates seamlessly into your existing storage infrastructure?  Well, in combination with a cloud storage gateway or appliance like CloudArray, you may want to consider storage tiering software. Auto-tiering software can be found in storage virtualization solutions, data classification solutions, and even in some hypervisor solutions. Once you choose an auto-tiering framework, you can immediately begin to extend the life cycle of existing storage arrays and leverage the benefits of cloud storage by selectively offloading infrequently used data. Look for a more detailed discussion of auto-tiering solutions in a future post.

In the meantime, download CloudArray today to start enjoying all the benefits of cloud storage and discover how easy it is to break the traditional storage array life cycle.

Read the original blog entry...

More Stories By Nicos Vekiarides

Nicos Vekiarides is the Chief Executive Officer & Co-Founder of TwinStrata. He has spent over 20 years in enterprise data storage, both as a business manager and as an entrepreneur and founder in startup companies.

Prior to TwinStrata, he served as VP of Product Strategy and Technology at Incipient, Inc., where he helped deliver the industry's first storage virtualization solution embedded in a switch. Prior to Incipient, he was General Manager of the storage virtualization business at Hewlett-Packard. Vekiarides came to HP with the acquisition of StorageApps where he was the founding VP of Engineering. At StorageApps, he built a team that brought to market the industry's first storage virtualization appliance. Prior to StorageApps, he spent a number of years in the data storage industry working at Sun Microsystems and Encore Computer. At Encore, he architected and delivered Encore Computer's SP data replication products that were a key factor in the acquisition of Encore's storage division by Sun Microsystems.

CloudEXPO Stories
A valuable conference experience generates new contacts, sales leads, potential strategic partners and potential investors; helps gather competitive intelligence and even provides inspiration for new products and services. Conference Guru works with conference organizers to pass great deals to great conferences, helping you discover new conferences and increase your return on investment.
Using new techniques of information modeling, indexing, and processing, new cloud-based systems can support cloud-based workloads previously not possible for high-throughput insurance, banking, and case-based applications. In his session at 18th Cloud Expo, John Newton, CTO, Founder and Chairman of Alfresco, described how to scale cloud-based content management repositories to store, manage, and retrieve billions of documents and related information with fast and linear scalability. He addressed the challenges of scaling document repositories to this level; architectural approaches for coordinating data; search and storage technologies, Solr, and Amazon storage and database technologies; the breadth of use cases that modern content systems need to support; how to support user applications that require subsecond response times.
Poor data quality and analytics drive down business value. In fact, Gartner estimated that the average financial impact of poor data quality on organizations is $9.7 million per year. But bad data is much more than a cost center. By eroding trust in information, analytics and the business decisions based on these, it is a serious impediment to digital transformation.
With more than 30 Kubernetes solutions in the marketplace, it's tempting to think Kubernetes and the vendor ecosystem has solved the problem of operationalizing containers at scale or of automatically managing the elasticity of the underlying infrastructure that these solutions need to be truly scalable. Far from it. There are at least six major pain points that companies experience when they try to deploy and run Kubernetes in their complex environments. In this presentation, the speaker will detail these pain points and explain how cloud can address them.
Containers and Kubernetes allow for code portability across on-premise VMs, bare metal, or multiple cloud provider environments. Yet, despite this portability promise, developers may include configuration and application definitions that constrain or even eliminate application portability. In this session we'll describe best practices for "configuration as code" in a Kubernetes environment. We will demonstrate how a properly constructed containerized app can be deployed to both Amazon and Azure using the Kublr platform, and how Kubernetes objects, such as persistent volumes, ingress rules, and services, can be used to abstract from the infrastructure.