While investing in building new data centers all over the world and creating the management overlay in order to be able to sell their hardware, IaaS operators are also relying on their ecosystem to support the evolving enterprises that go to the cloud (e.g. the “Enterprise Grade Cloud”).
API First – The move to the cloud pushes the data center to re-invent itself within the new environment. It is a fact that, although the cloud is a pure revolution (at least in MHO), terms such as SLA, TCO and ROI are still valid in this new IT era. Thanks to industry leaders such as Salesforce.com that realize the notion of “API first”, vendors such Amazon cloud present new capabilities first through their APIs. In this way, the cloud operator platform enables development of its ecosystem.
The benefits of migrating workloads between different cloud providers or between private and public clouds can only truly be redeemed with an understanding of the cloud business model and cloud workload management. It seems that cloud adoption has reached the phase where advanced cloud users are creating their own hybrid solutions or migrating between clouds while striving to achieve interoperability values within their systems. This article aims to answer some of the questions that arise when managing cloud workloads.
Last month I attended HP Discover (disclosure: my participation was funded by Ivy World). The IT war already started however HP stands still not taking initiatives and real risks as true leaders should take. At the three-day conference I learned why some companies don’t last and why this IT giant is at a great risk of losing in this new era IT battle. This is a story of a lasting company that might have already lost.
The IT capacity plan is derived from the current and future resources utilization for holding, storing and accommodating the software services. It is a given fact that servers’ average utilization in the traditional data center is between 5% and 20%. By contract, when planning capacity in the cloud, the basic working assumption is that, utilization should match the demand at all times and support temporary demand peaks and future trends.
Capacity planning is described by Wikipedia as the
“process of determining the production capacity needed by an organization to meet changing demands for its products.” It is also given by the following formula:
(number of machines or workers) × (number of shifts) × (utilization) × (efficiency)
In his CIO’s article about cloud computing capacity, Bernard Golden wrote,
One of the most important features of the cloud is the sharing of resources by multi-tenants. Without sharing and being able to optimize utilization of resources, the cloud operator can’t provide scalability and support “economies of scale” for its business. The IaaS public contains its “cloud magic” as well as real hardware such as computing, storage and network devices. The utilization of these resources should be optimized by meeting demand (by time), hence they must be shared between the cloud consumers.
In April 2011, when Amazon’s cloud s east region failed. I posted the first chapter of theAmazon Cloud Outage Conspiracy – it was already very clear that the cloud will fail again and here it is… Chapter 2
Let’s first try to understand Amazon’s explanation for this outage.
“At approximately 8:44PM PDT, there was a cable fault in the high voltage Utility power distribution system. Two Utility substations that feed the impacted Availability Zone went offline, causing the entire Availability Zone to fail over to generator power. All EC2 instances and EBS volumes successfully transferred to back-up generator power.”
Last week I attended one of the most popular cloud technology conferences in the world – CloudConnect. The CloudConnect conference started about four years ago. Attending the event gave me a clear understanding of the market maturity and evolution rhythm. Check out the following sections for the main points on what I heard and learned:
The underlying infrastructure performance, round trip time, bandwidth, caching and rendering are to be counted as the major features of an online service performance. In an interesting presentation by @joeweinman (known by his famous “Cloudonomics” theory), it was claimed that latency holds the greatest weight among these faetures. I encourage you to check out his new research – As Time Goes By: The Law of Cloud Response Time presents some good formulas, methods and considerations with regards to online services’ performance and latency (including simple facts, for example, that people tend to prefer selecting from fewer options on an online page – so you can have less content on a page and achieve a better browsing performance).
Last week I was invited to the HP Tech Day in HP’s campus in Houston to learn and hear more about the giant’s cloud offering. I appreciate HP and Ivy very much for the invitation and for a great event where I was able to learn more and see these clouds in real. I had the privilege to meet savvy and professional guys. It is always great to see people who are enthusiastic on their jobs and are proud of their company. Let me share with you HP’s cloud from my point of view.