Traditional storage was designed to present a LUN to a server. This worked well until that server became a hypervisor running 10, 20 or 30 virtual servers, all pointing to the same LUN. Adding to the complexity, all hypervisors need to point to the same LUN to enable VM mobility or high availability. Architecturally, this creates a many-to-one relationship that makes optimization impossible. Each VM has a different I/O pattern. When they all mix together, the aggregate I/O becomes highly random, creating performance issues with no way to isolate problems or control I/O per VM.

read more

(c)iStock.com/eric1513

Many great innovations have come out of cloud computing, such as on-demand infrastructure, consumption-based pricing and access to global computing resources. However, these powerful innovations have come at a high cost: complexity.

Managing cloud infrastructure today is substantially more complex than managing traditional data center infrastructure. While some of the complexity is a direct consequence of operating in a highly transient and shared computing environment, most has to do with the unintended side effects of cloud computing. For example, consumption-based pricing allows us to pay for only what we use, but requires careful monitoring and continuous optimization to avoid resource waste and poor cost management.

API-driven resources allow us to launch compute and storage with a few lines of code, but require that the resources be highly configurable to support the various needs of its different users. Purpose-built services (e.g. Amazon S3) substantially reduce the barrier to building new types of applications, but require that we obtain the necessary expertise to manage and operate the new services.

The rise of cloud management

These early experiences with the growing complexity of managing cloud environments spawned a new generation of open source and commercial products intended to help us contain this complexity. However, the continued pace of innovation in public, private and hybrid clouds, combined with the increasing importance of multi-cloud environments, has continued to widen the gap between the complexity of our infrastructure and our ability to manage that infrastructure. It has become increasingly clear that something needs to change to support the cloud environments of tomorrow.

The genesis of autonomic computing

In 2001, IBM released a manifesto predicting a looming software complexity crisis caused by our inability to manage the rapid growth in computation, communication and information technology. The solution proposed was autonomic computing, a term which took its name from the autonomic central nervous system, essentially an automatic control system for the human body. In its manifesto, IBM defined autonomic computing as self-managing systems that can configure, optimize, heal and protect themselves without human intervention.

While the paper launched a field of research that remains active today, its impact has not been widely felt in the industry, in large part because the gap IBM forecasted did not become a substantial impediment to businesses until the early mainstream adoption of cloud computing, almost a decade later. But now, with the gap between the complexity of infrastructure and our ability for software to manage this complexity continuing to widen, the IBM manifesto seems suddenly prescient.

The impact of cloud autonomics

Cloud autonomics is the use of autonomic computing to enable organisations to more effectively harness the power of cloud computing by automating management through business policies. Instead of relying on manual processes to optimise cost, usage, security and performance of cloud infrastructure, a CIO/CTO can define business policies that define how they want their infrastructure to be managed and allow an autonomic system to execute these policies.

Cloud autonomics envisions a future in which businesses manage their clouds like brokerages manage equity trading – with policy-aware automation. A business will configure an autonomic system with governance rules. The system will then continuously monitor the business’s cloud environment, and when the environment goes out of compliance, will make the necessary changes to bring it back in line. Some sample policies cloud autonomics anticipates include:

Cost

• The automated purchase of reserved capacity in support of organizational or functional needs (e.g. AWS reservations).
• The automated movement of an idempotent workload from one cloud provider to another to obtain cost efficiencies.

Availability

• The automated migration of data to another region in support of business service level agreements (SLAs).
• The automated migration and/or backup of storage from one medium to another (e.g. migrating data in AWS EBS to S3 or Glacier).

Performance

• The automated increase of the machine type for a workload to support more efficient operation of non-horizontally scaling workloads.

Security

• The automated change of network and/or endpoint security to conform to business policies.

Usage

• The automated shutdown of idle or long-running instances in support of business policies (e.g. shutdown idle development infrastructure running more than a week).

Making cloud autonomics work for you

Cloud autonomics requires a system capable of executing a collect, analyze, decide and act loop defined in autonomic computing. Unlike autonomic computing, a cloud autonomic system relies on policy-driven optimizations instead of artificial intelligence. The system monitors one or more cloud providers and the customer infrastructure running within these cloud providers, evaluates user-defined policies, and using optimization algorithms, identifies recommendations to alter the infrastructure to be consistent with the user-defined policies. These recommendations may optionally require external approval before execution, and can seek privileges from an external system to execute approved changes.

A cloud autonomic system is capable of continual and automated optimization of cloud infrastructure based on business policies, both within a single cloud environment and across multiple clouds. It promises a future in which organizations can define policies, and have these policies securely managed down to microsecond decisions, resulting in consistent implementation and optimal resource utilization.

With worldwide spending on cloud services and infrastructure growing by 23% in 2015 to $118B, it is clear that cloud services are here to stay. Yet, the rate of cloud adoption varies by companies and markets around the world. With thousands of outages and hijacks across the Internet every day, one reason for hesitation is the faith in quality Internet performance.
In his session at 16th Cloud Expo, Michael Kane, Senior Manager at Dyn, will explore how Internet performance affects your end-user’s experience and how you can make variations in the Internet work to your competitive advantage.

read more

(c)iStock.com/4x-image

By Steve Davis, Marketing Director, Next Generation Data

Britain’s internet demand is expanding so fast that it could consume the nation’s entire power supply by 2035, scientists told the Royal Society earlier this month.

Hopefully it won’t come to that but Andrew Ellis, professor of optical communications at Aston University, told the “Capacity Crunch” conference that data storage and transmission on the internet, along with devices such as PCs and TVs, are already consuming at least 8% and as much as 16% of Britain’s power — and doubling every four years.

This problem is already hitting some data centres and as a result they are limiting the power available to the racks hosted in their facilities. In some cases this can be as low as 2 kW. This was fine a few years ago, but now the higher density racks being installed demand much more power. And while virtualisation and other new technologies allow huge improvements of IT efficiency more power to each rack is a pre-requisite to run them.

Because of this it is not unusual for some data centres to force customers to take more space (and charge for it) than necessary purely to deliver the power required.

This problem is only going to get worse. Make sure you choose a data centre which has the ability to deliver the right levels of power now, have plenty in reserve for the future and won’t penalise you by making you take more space than you really need.

Also ensure your data centre provider can actually deliver the amount of power it has contracted to. There have been cases where power availability has been ‘oversold’ as some providers have gambled on the fact that not all customers will use all their allocated amount of power at the same time.

A data centre relationship should last for many years. Apart from risking business continuity and competitive edge through unreliable or insufficient power, having to make an unplanned move from one data centre provider to another will be a time consuming and costly exercise.

For data centre users it is essential to do your homework sooner than later as increasingly, when it comes to the power game, there will be those facilities that have it and those that don’t. 

The worldwide cellular network will be the backbone of the future IoT, and the telecom industry is clamoring to get on board as more than just a data pipe.
In his session at @ThingsExpo, Evan McGee, CTO of Ring Plus, Inc., discussed what service operators can offer that would benefit IoT entrepreneurs, inventors, and consumers.
Evan McGee is the CTO of RingPlus, a leading innovative U.S. MVNO and wireless enabler. His focus is on combining web technologies with traditional telecom to create a new breed of unified communication that is easily accessible to the general consumer. With over a decade of experience in telecom and associated technologies, Evan is demonstrating the power of OSS to further human and machine-to-machine innovation.

read more