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No one will be better informed than a Canadian web hosting service provider to detail the way today’s data centers can really ramp up operating costs. There’s a whole host of reasons for that, but nearly every one of them is contained in those centers’ digital architecture, and their sensors and instrumentation specifically. Making correct analyses of where inefficient operation is occurring is often beyond the means of even the most digitally savvy of us, but certainly not for the smart folks at Intel. Intel’s Data Center Manager helps data center operators lower costs and extend infrastructure life spans by automating data collection and presenting insights into ideal operating conditions and configurations. It involves identify and monitoring as many individual data points, so when there’s a problematic inefficiency, users are able to know exactly where it is. One of the common issues DCM data reveals is a need to increase the temperature in datacenters and thus minimize cooling costs. This shouldn’t come as a surprise entirely, given the ever-increasing workload these data centers face and the according way they will tend to run hot as a result. There are more data points than ever, and so by extracting that data and looking at it from a more objective perspective, you can be confident in choosing to turn up the temperature as a means of lowering your air conditioning costs. From there, the DCM team can set threshold levels and implement algorithms to try to predict temperatures and to alert datacenter operators of potential problems. Just one example of how Intel’s DCM is super effective in helping to manage and keep a Data Center cost controlled. Here’s more: Languages to Communicate Across OEMs All hardware manufacturers follow the Intelligent Platform Management Interface, or IPMI, specifications to report performance metrics independently of the hardware’s CPU, firmware, or operating system. Each brand customizes their IPMI feed slightly to differentiate their products, and that’s to be expected. DCM provides a simplified data feed to infrastructure and application performance managers to interpret or to connect with a facilities management interface. The out-of-band solution has its own discovery mechanism to locate network devices and languages, and...

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What is meant by NoSQL databases? NoSQL databases schemas and applications have now emerged into the mainstream as a modern tool for organizations battling big data requirements. But what does NoSQL actually imply, and what advantages and disadvantages does NoSQL deliver for data storage? Here is everything you ever wanted to know but were afraid to ask about NoSQL. To begin with, NoSQL”is not a specific database product. It is a term that refers to a general category of database methodology and techniques; and a handful of vendors have implemented NoSQL administration in different ways. Yet all NoSQL products share a basic defining characteristic; which is that NoSQL implementations do not use the “relational-database” model of traditional SQL-style databases; such as currently ubiquitous in shared hosting “MySQL”. “Traditional” DBs Gaining an understanding of exactly what NoSQL means requires a recap on how most databases today have typically functioned for the past several decades. With a relational database like MySQL, the database architect or programmer needs to define and detail in advance where the data is going to be stored. Different tables are created, different pieces of data are stored inside different tables, and data is retrieved based on table structure. So MySQL, and other relational databases, are close to perfect if you know ahead of time what structure your data will be represented in; and also have a sense of how much data that will need to be stored. But what happens when your storage needs not so predictable? What if your applications data storage needs to be highly scalable? Relational databases don’t work quite so well in those situations. Simplicity, Openness, and Scalability NoSQL allow you to stream data into a database without defining a formal storage structure ahead of time. As a result you do not need to write as much cryptic code for an application to interact with the database. Also you can retrieve data quickly without having to tell your application where precisely to pinpoint what data you want within a large, rigid, syntactically very sensitive database structure. NoSQL DB’s also tends to scale better as they are designed to be able to run easily on...

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