Grid Computing

Grid Computing
The term Grid Computing collectively defines a set of distributed computing use cases that have certain technical aspects in common. There are two main use case in distributed computing that are most often referred to as Grid Computing namely Computational Grid and Data Grid.
Computational Grid
If you have a task that is executing unacceptably long time you can split the tasks into multiple sub-tasks executes each sub-tasks in parallel on a separate computer combine results from the sub-tasks and get the original tasks resulting time factor of O(N) (read it as "big-oh" of "N") times faster, where 'N' is a number of sub-tasks in the split.
Data Grid
Data grids allows for splitting data storing onto multiple computer. Much like computational grids splitting processing. Data Grids allow placing data onto multiple computers or storage resources and treat them virtually like one.

FIVE Mistakes a Security Vendor Made in the Cloud

When security experts sound the alarm about enterprises embracing cloud computing with little understanding of the risks, it's usually a case where the expert -- working for a vendor -- is making a pitch for their employer's products. That's all well and good, but here's the problem -- some of them have trouble keeping their own side of the cloud clean.

That, according to Nils Puhlmann, co-founder of the Cloud Security Alliance and previously CISO for such entities as Electronic Arts and Robert Half International.

Puhlmann recently contacted CSOonline about one example where a sizable security vendor made multiple mistakes in the cloud. He spoke on the condition that the vendor's name is kept anonymous, as he is working with the company to help address its problems.

"This major security vendor basically did everything you can possibly do wrong when rolling out the latest version of its SaaS (software as a service) product, leading to users uninstalling their solution in large numbers," he said.

In listing the following five mistakes (most of which are rooted in a lack of communication with customers), his goal is to show other security vendors how NOT to do things, and to arm IT security practitioners with a list of questions they should ask of those they pay to give them secure cloud-based services.

MISTAKE 1: Updating the SaaS product without telling customers or letting them opt out
Customers using a particular version of the SaaS product were caught unaware when the vendor decided to roll out a new version through the cloud. It was done in a way where, at the moment of the upgrade, any new endpoint that was added to be managed automatically got the new version. Customers were not asked or notified, and were forced into a mixed-version environment as a result. "In the past, I as a customer was able to choose if I wanted to do this, and I could choose the timing," he said. "Here, there was no control, no timing or notification."

MISTAKE 2: Not offering a rollback to the last prior version
The problem with the first mistake is that customers are now faced with compatibility issues in their environment that can cause a freeze-up of essential IT functions, including those related to security. The natural course for the IT security practitioner is to uninstall the new but incompatible version, dust off the CD with the last version of the product, and re-install the version that has proven itself stable in that environment. But in the cloud it's not always so simple, especially in this case, where the vendor offered no rollback option. "You get forced into a mixed environment and have no way to react," Puhlmann said.

MISTAKE 3: Not offering customers a choice to select timing of an upgrade
For IT security practitioners, dealing with new versions of a software or service that prove incompatible is nothing new. It happens just about every month when Microsoft releases its security updates. But in most cases, IT shops have control over when an update is pushed out in their environments. In the case of Microsoft's monthly Patch Tuesday updates, most IT admins run the updates through a roughly week-long gauntlet of testing and tweaking before deploying company-wide. But in this case, customers had no control over the timing of upgrades in their environments, Puhlmann said.

MISTAKE 4: New versions ignore prior configurations or settings, which creates instability in the customer environment
The third mistake was particularly problematic because the new version of the SaaS product proved buggy. For example, it disregarded whitelist and firewall settings programmed into the previous version, causing computers to suddenly bog down with pop-up warnings for a variety of commonly-used applications, including those built and maintained in-house. "The client now doesn't trust itself and blocks everything," he said. "Integrity between a cloud and an endpoint is essential, and this sort of disconnect could be exploited for denial-of-service attacks and the like. Vendors need to be thinking about this."

MISTAKE 5: Not offering a safety valve
Had the vendor offered some sort of safety mechanism in its cloud configuration, customers could have at least limited the damage upon realizing a bug was mucking up the works, Puhlmann said. But as far as he could tell, there was no such mechanism.

What customers can learn from this
Puhlmann does credit the vendor for its response to the mistakes he warned them about. They are now working to improve the process. For customers delving into the cloud who may have concerns about these things happening to them, his advice is simple: Ask a lot of questions before signing on the dotted line.

"You have to ensure things you did in the past, before the cloud, can still be done," he said. "You have to know for sure that services managed in the cloud have the highest integrity, and that you will have choices over whether to receive an update and when the update is made."

About this series: Enterprises are increasingly dependent on cloud-based infrastructure -- virtualized resources provided as a service over the Internet. But security experts worry that many businesses are embracing the cloud without regard for the risks. This series will define how the cloud has changed business processes, where the security risks are and how to mitigate those risks.

Source: http://ow.ly/sHvN

Operating a Data Warehouse with Hive, Amazon Elastic MapReduce and Amazon SimpleDB

This article shows how to use Amazon Elastic MapReduce and Hive to process logs uploaded to Amazon S3 from a fleet of boxes which are serving online advertising. The logs are processed and the resulting information is stored in a collection of relational tables persisted in Amazon S3 and queryable using Hive. Summaries of the data are pushed to Amazon SimpleDB where they are accessible to monitoring tools.

http://ow.ly/sHp9