Whether you realize it or not, you may already be using, rely upon, affiliated with, support or otherwise involved with data infrastructures. Granted what you or others generically refer to as infrastructure or the data center may, in fact, be the data infrastructure.
Generally speaking, people tend to refer to infrastructure as those things that support what they are doing at work, at home, or in other aspects of their lives. For example, the roads and bridges that carry you over rivers or valleys when traveling in a vehicle are referred to as infrastructure. This is also the situation with IT systems and services where, depending on where you sit or use various services, anything below what you do may be considered infrastructure.
There are different infrastructure layers about information technology (IT) from higher-level business systems (e.g. business infrastructure), along with applications and environments for those who support and create them (e.g. information infrastructures). Then there are the data infrastructures along with lower level physical facilities or real data centers also known as habitats for technology. The physical facilities can, in turn, rely on external electrical power, network communications, and other infrastructure resources or services.
However, let’s get back to our focus which will be in and around the data infrastructure that spans from on-premise to cloud. As a refresh or to provide context, data infrastructures are the collection of hardware and software, from legacy physical to software-defined virtual, containers, cloud.
The role of data infrastructures is to protect, preserve, process, move, secure and serve data as well as their applications for information services delivery. Technologies that make up data infrastructures include hardware, software, and cloud or managed services, servers, storage, I/O and networking along with people, processes, policies along with various tools spanning legacy, software-defined virtual, containers, and cloud.
Some of the trends, technologies, tools and techniques that will be discussed and explored in future posts may include among others converged and hyper-converged, cloud, hybrid topics. Application workload performance, availability, capacity and economic (PACE) considerations along with relevant data infrastructure resources to support them. Hardware as well as software including license optimization as well as open source considerations.
Of course, there will be the buzzword bingo topics such as AWS, AI, Analytics and Automation, Big Data (and little data) along with bleached data (e.g. wipe or secure erase). There are also Containers and Cloud, Data protection and data footprint reduction (DFR), energy and economics as well as efficiency (utilization or space savings) along with effectiveness (productivity and performance).
Then there are fast software, servers, storage and networks including flash SSD, Google, health check tools, Intel and IoT/IoD data infrastructure demands. Needless to say there are many other related items as well as industry activities we will have opportunities to discuss.
Let’s wrap up for now, and put it all back together in that data infrastructures are what exist in data centers and physical facilities. Data infrastructures can be small all in one hyper-converged infrastructures (HCI) or converged appliances in smaller environments.
Likewise, data infrastructures can be rack-scale in larger environments all the way up to larger enterprise and cloud service providers. The key is that data infrastructures exist to enable, protect, preserve, secure and serve applications that transform data into information. Combined information infrastructures and data infrastructures along with their underlying infrastructures as well as applications they support can be considered information factories.
Ok, nuff said, for now.
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