You’re a large organization, using cloud computing to your advantage. You’ve enjoyed your cloud experience and see how this model is helping you evolve. Still, you wish you could make your cloud infrastructure run a little bit better. You’d love to experience better performance and utilize your cloud resources a bit more efficiently. But how can you upgrade your cloud experience without recreating your entire architecture?
Many shops have now migrated to some type of cloud model for many different reasons. There are lots of use cases emerging which make cloud a powerful platform to utilize.
Still, like everything in technology, solutions right out of the box have the potential to be optimized. So let’s take a look at five technologies which have helped organizations of all sizes utilize their cloud infrastructure more intelligently.
Cloud Automation
This is a pretty big one because you’re effectively creating powerful cloud intelligence. It’s not quite a “set it and forget it” system. But it can get pretty close. Technologies like CloudPlatform, OpenStack and Eucalyptus all create powerful management extensions for your cloud environment. Dynamic resource provisioning and de-provisioning, workload and application control, and a very powerful distributed cloud management portal can help organizations gain new insights into their infrastructure.
At this logical layer, you can connect a myriad of cloud models into one automation and orchestration module to really create a proactively dynamic cloud infrastructure. Remember, you can automatically control everything from storage resources, to VM provisioning here. If you’re a growing organization utilizing various cloud technologies, cloud automation can make your life a lot easier.
Agnostic Cloud Control
Private, public, hybrid, distributed, community – does it really matter? The cloud model continues to evolve, and soon it’ll just be “How can I manage all of my cloud instances agnostically?” The agnostic cloud concept arises from the fact that almost all cloud environments are pulling resources from outside of themselves. Whether it’s an application that lives as a SaaS instance or there is a connection into a public cloud provider for DR, the idea is to manage the whole thing intelligently.
Technologies like BMC begin to explore the concept of agnostic cloud control. By connecting with major control plains and interfacing with solid APIs, the cloud computing concept and everything beneath it can be better abstracted.
Software-Defined Technology (SDx)
There are very real technologies behind many of these terminologies. Cloud computing relies on the virtual layer for it to run optimally. Now, virtualization and the logical layer have helped abstract on physical-only platforms. We have software-defined: Storage, Security, Networking and even Data Center. Each of those four examples already have technologies there to back up the conversation:
- Storage: Atlantis USX and VMware vSAN.
- Networking: Cisco NX-OS and VMware NSX.
- Security: Palo Alto PAN-OS and Juniper Firefly.
- Data center: VMware SDDC and IO.OS.
These are solid platforms which help control many new aspects of cloud computing. Furthermore, many of these SDx technologies directly integrate into the agnostic cloud model.
Data-Specific and WAN Optimization
We have more resources, better bandwidth capabilities, and a lot more users and organizations connecting into the cloud. WANOP had to evolve beyond simple traffic optimization. Data-defined optimization in conjunction with WANOP is creating a new tier of information distribution. Concepts like content delivery networks (CDNs) create powerful delivery methodologies where data center and WAN interconnectivity play a big role.
Technologies like CloudBridge, SilverPeak, Riverbed and Aryaka strive to create new ways to delivery and manipulate data in the cloud. WAN control has expanded far beyond just optimization. Virtual and physical appliances control and optimize the flow of traffic for replication, DR, and regular delivery services. Traditionally, physical appliances put this type of technology out of reach for some organizations. Now, with the virtual platform, the cost has come down and many more shops can insert an enterprise-class platform directly into their data center.
The Cloud and Data Center Operating System
The conversation here revolves around the software-defined data center as well as the data center operating system. The idea here is to abstract all data center functionality (and I mean all) into the logical layer. Basically we’re trying to create the virtual data center layer. VMware is working on their SDDC model to enable administrators to see all of their physical resources on a distributed plane and assign resources as needed. The idea is to have the VMware SDDC management layer control – agnostically – all resources that are being utilized. This can be network, storage, compute and more.
Similarly, the data center operating system, like IO.OS, take data center control to a completely new level. Global data center control and integration with underlying APIs creates a model that can control all sorts of workloads including big data, virtual workloads, mobility and more. Here’s why it’ll make your cloud better: this technology is extensible and adaptive, which means it’ll grow with your cloud, data center and business needs.
Cloud optimizations are emerging everywhere. New types of control technologies help you abstract the physical layer to deliver even more power from you infrastructure. Administrators need to look at the logical layer to help them optimize their cloud environment before needing to invest in expensive hardware. We’re able to control so much from a virtual platform that the distributed cloud model is become a truly powerful business engine for many to consider.
In working with your own cloud model, evaluate your current systems and their capabilities. Do you need an upgrade? Are there ways you can optimize existing resources? How far can you push your environment to make it even more cost-effective? Modern technologies are allowing traditional platforms to be completely abstracted. This scales from security to entire data center models. Always look for ways to optimize existing resources. And most of all, look for ways to make this process as automated and intelligent as possible.
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