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What is Old Is New Again - The Cloud No comments yet

Cloud computing is the current IT rage, said to cure all information management skills.

Cloud computing is just a new name for timeshare, a system in which various entities shared a centralized computing facility. A giant piece or two of big iron and floors of tape decks provided information processing and storage capabilities for a price.

The user was connected to the mainframe by a dumb terminal and later on by PC’s. The advantage (said the sales jargon), was that the user didn’t need to buy any additional hardware, worry about software upgrades or data backup and recovery. They would only pay for the time and space their processes required. Resources would be pooled and connected by a high speed network and could be accessed as demanded. The user wouldn’t really know what computing resources were in use, they just got results. Everything depended on the network communications between the use and centralized computing source.

What is New

Cloud computing is more powerful today because the communications network is the Internet. Some Cloud platforms also offer Web access to the tools – programming language, database, web utilities needed to create the cloud application.

The most important aspect I believer the Cloud offers is instant elasticity. A process can be upgraded almost instantaneously to use more nodes and obtain more computing power.

There are quite a few blog entries out there concerning the “elastic” cloud. For thoughts on “spin up” and “spin down” elasticity see For thoughts on “how elasticity could make you go broke, or On-demand IT overspending” see

And finally, an article that spawned the “elasticity is a myth” connotation or “over-subscriptionand over-capacity are two different things, see –

A good article that covers elasticity, hypervisors, and cloud security in general is located at The site is maintained by the Association for Computing Machinery. There are lots of articles on all sorts of computing topics including, “Why Cloud Computing Will Never Be Free” (

The Clouds

The most notable Clouds are Amazon’s Elastic Cloud, Google’s App Engine, and Microsoft’s Azure.

The three Cloud delivery models include:

    • Software as a service (SaaS), applications running on a cloud are accessed via a web browser

    • Platform as a service (PaaS), cloud-developed user applications such as databases

    • Infrastructure as a service (IaaS), provides computing resources to users on an as-needed basis

Pros and Cons

There are pros and cons for Cloud Computing. Microsoft’s Bill Ballmer is a proponent of Cloud computing.

In a recent email ( to Microsoft’s employees, Ballmer make the following case for Cloud Computing. He advises his employees to watch a video ( in which he makes the following points.

In my speech, I outlined the five dimensions that define the way people use and realize value in the cloud:

  • The cloud creates opportunities and responsibilities

  • The cloud learns and helps you learn, decide and take action

  • The cloud enhances your social and professional interactions

  • The cloud wants smarter devices

  • The cloud drives server advances that drive the cloud

Some very notable people are anti-cloud.

Richard Stallman, GNU software founder, said in recent interview for the London Guardian ( that Cloud computing is a trap.

The Web-based programs like Google’s Gmail will force people to buy into locked, proprietary systems that will cost more and more over time, according to the free software campaigner.

‘It’s stupidity. It’s worse than stupidity: it’s a marketing hype campaign,’ he told The Guardian. ‘Somebody is saying this is inevitable — and whenever you hear somebody saying that, it’s very likely to be a set of businesses campaigning to make it true.’”

Aside from all that, what should a potential user be wary of in the Cloud? I’ll try to answer that below.

Security in the Cloud

Security in the cloud is a major concern. Hackers are salivating because everything – applications, data, are all in the same place.

How do you know the node your process is accessing is real or virtual? The Hypervisor (in Linux, a special version of the kernel) owns the hardware and spawns virtual nodes. If the Hypervisor is hacked, the hacker owns all the nodes created by it. http://www.linux-kvm. org has further explanations and discussions of virtual node creators/creations.

Data separation is a big concern. Could your data become contaminated by data in other environments in the cloud.? What access restrictions are in place to protect sensitive data?

Can a user in another cloud environment inadvertently or intentionally get access to your data?

Data interoperability is another question mark. A company cannot transfer data from a public cloud provider, such as Amazon, Microsoft, or Google, put it in a private IaasP that a private cloud provider develops for a company, and then copy that data from its private cloud to another cloud provider, public or private. This is difficult because there are no standards for operating in this hybrid environment.

Data Ownership

Who is the custodian and who controls data if your company uses cloud providers, public and private?

Ownership concerns have no been resolved by the cloud computing industry. At the same time, the industry has no idea when a standard will emerge to handle information exchanges.

W3C –, is sponsoring workshops and publishing proposals concerning standards for the Cloud. You can subscribe to their weekly newsletter and stay up on all sorts of web-based technologies.

Also, the Distributed Management Task Force Inc.( is a consortium ofof IT companies focusing on, “Developing management standards & promoting
interoperability for enterprise & Internet environments”.

The DMTF Open Cloud Standards Incubator was launched to address management interoperability for Cloud Systems ( The DMTF leadership board currently includes AMD, CA Technologies, Cisco, Citrix Systems, EMC, Fujitsu, HP, Hitachi, IBM, Intel, Microsoft, Novell, Rack Space, RedHat, Savvis, Sun Guard, Sun Microsystems, and VMWare.

Working with the Cloud

Working with the Cloud can be intimidating. One suggestion is to build a private cloud in-house before moving on to the public cloud.

However, even that has its difficulties. Not to worry, there are several tools available to ease the transition.

There is a Cloud programming language – Bloom, developed at UC Berkeley by Dr. Joseph Hellerstein. HPC In The Cloud has published an interview with Dr. Hellerstein at

Bloom is based on Hadoop ( which is open source software for High Performace Computing (HPC) from Apache..

For ease of inter connectivity, Apache has released Apache libcloud, a standard client library written in python for many popular cloud providers – But libcloud doesn’t cover data standards, just connectivity.

MIT StarCluster– , is an open source utility for creating and managing general purpose computing clusters hosted on Amazon’s Elastic Compute Cloud (EC2). StarCluster minimizes the administrative overhead associated with obtaining, configuring, and managing a traditional computing cluster used in research labs or for general distributed computing applications.

All that’s needed to get started with your own personal computing cluster on EC2 is an Amazon AWS account and StarCluster.

HPC presents use cases as a means to understanding cloud computing.

BCM Bioinformatics has a new methodology article – Cloud Computing for Comparative Genomics that includes a cost analysis of using the cloud. Download the .pdf at

I hope this will get you started.  Once again, a big thanks to Bill for his assistance.

Keep to Good Faith No comments yet

I was going through a box of textbooks last week and stumbled upon a copy of the Enron Code of Ethics. I have another one stored away with a form, signed by Ken Lay, that states I have read and will comply with the Enron Code of Ethics.

I was employed at Enron from 2000 through 2002 and was there when the wheels came off. Our department was left intact. Otherwise, whole floors of the Enron building were vacated. It really was a shame, because Enron was a great place to work. Several friends and acquaintances lost most of what they had because of the malfeasance of a greedy few.

This had to be the most blatant example of unethical conduct in the workplace I encountered. There were others, that appeared seemingly minor, ended up costing companies money and talent. Most of these losses were mostly the result of mismanagement and not outright unethical behavior. But, then again, is mismanagement itself unethical?

I book I read recently entitled “A Small Treatise of the Great Virtues, The Uses of Philosophy in Everyday Life” by Andre Comte-Sponville (Metropolitan Books), talks about truth as “Good Faith”.

He states on page 196, that “at the very least that one speaks the truth about what one believes, and this truth, even if what one believes is false, is less true for all that. Good faith, in this sense, is what we cal sincerity (or truthfulness or candor) and is the opposite of mendacity, hypocrisy, and duplicity, in short, the opposite of bad faith in all its private and public forms.”

In my position at a major hardware/software developer I was told that I “didn’t need to know about a product to sell it.”

At another position, I found that a few fraudulent claims by a contractor caused a company to fork over three quarters of a million dollars for custom software when a fifteen thousand dollar piece of hardware would have an enabled an already existing piece of commercial software to do the job. With a more accurate accountability of the data, I might add.

In fact, the whole program was completely mismanaged, to the detriment of the company, not the contractor. In fact, he was ready for the next program as he had one of his engineers hired in to head up that project. An engineer who didn’t have the slightest idea about our system, much less its theory. Thankfully, we got him transferred out of there and back to design where he belonged.  The contractor was kicked out of the company.

These are straight-forward examples of bad faith. The following are a little harder to classify.

Beware the ulterior motive, especially if the new system you are proposing will impose on someone’s fiefdom.

Data analysis for the existing program consisted of placing a request with the a data analysis group and waiting up to 3 days for results. The system proposed (and later deployed) would give each and every engineer access to an analysis application that they could use to inspect the data one and a half hours after a particular test cycle was completed. A little training and they were ready to go.

Countless hours were spent in useless meetings defending the system. Everybody shut up when the system came up on day one and stayed up through months of testing.

This test/record/analysis cycle fits perfectly into the Laboratory Information Management Systems (LIMS) cycle of genomics research. A successful LIMS implementation in one lab aroused the ire of yet another lab attempting to develop their own solution. Let’s just say a lot of bad faith erupted.

The real loser in the above examples is the company. Money is wasted and talented people go elsewhere.

Biotechnology is a hot commodity right now. Stimulus funding bringing fresh capital to many projects. Companies are leveraging existing corporate products by repackaging them as biotech ready.

National Instruments LabView is one of these. I used it a lot in engineering. Now it’s a big player in the lab, incorporating interfaces for research lab instrumentation.

What is a LIMS (Laboratory Information Management System)? Is it an inventory management system? Is it a data pipeline? Can one size fit all?

Some companies have taken existing Inventory Management Systems and relabeled them as a Laboratory Information Management Systems. (At least the acronym fits.) Most of these systems don’t distinguish between research and manufacturing environments. They also don’t support basic validation of the LIMS application for its intended purpose. No wonder some 80% of LIMS users are dissatisfied.

At a recent conference I talked with researchers from various pharmaceutical companies and they were thoroughly dissatisfied with their LIMS systems. One scientist stated that they had a problem with their LIMS. When they went to report the problem, they found the company was no longer in business.

The latest IT (Information Technology) trends – SaaS, Cloud computing – may work in a business environment , but they won’t translate well to a pharmaceutical research area where they want everything safe behind the firewall.

There are many, many factors that go into developing biotechnology applications. Getting the right people, controlling the political environment, finding or developing the right software – it’s a jungle out there.

Keep to Good Faith and please be careful.

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