With new applications and the rise of artificial intelligence (AI), data centers have a huge share in our energy consumption. According to predictions, data centers would consume about 20% of electricity and account for 5.5% of emissions by 2025. So there is a need for sustainable solutions, including in the way we store data.
Green storage refers to the set of methods and technologies we use to store data in the most environmentally friendly way possible. From energy-efficient hardware to reducing the footprint of the data itself, data centers will have to push hard for sustainable practices in the coming years. Ultimately, it’s not just the planet that has to gain from this, as focusing on efficiency will also significantly reduce operational costs.
Storage, of course, is just one cog in a much larger system, but it will certainly be crucial to smartly managing our growing amount of data. That’s why we discuss four techniques that form the basis of more efficient data storage. The common thread in our story is software-defined storage. By putting a software layer over storage, you need less hardware and can store data in a scalable way. At DataCore, we offer this in the form of Swarm, a software-defined storage solution for core, edge and hydride cloud environments.
1. Make the best use of the resources you have
The basis of the software-defined storage principle lies in the fact that you are going to extend the life of your current storage. The software ensures that you use every available disk for storage and therefore do not have to constantly purchase new storage resources.
For example, if you buy a new car every four years, you obviously always have the most sustainable vehicle on the market. But if you drive the same car for twenty years, your footprint also remains limited because a new car does not have to be constantly produced. The same goes for storage. Perhaps the answer lies somewhere in the middle, but in any case, you are being green if you extend and expand existing storage as much as possible.
Virtualization plays an important role in this. The technique decouples the direct connection between physical storage and applications or users. As a result, you get a virtual pool of storage resources that is easier to manage. Additional advantages lie in the fact that you are a lot less dependent on vendors, can integrate new technology more easily and allows non-disruptive data migration. This allows data centers to grow and expand without exponentially increasing their energy consumption and footprint.
2. Reduce the footprint of your data
Another aspect of software-defined storage is the idea that you can use intelligent functionality that is in the software and therefore not in the hardware. As a result, you need less “iron” to do the same thing and consume less energy.
Important techniques here are deduplication and compression. Data deduplication ensures that redundant data in the storage system is not stored multiple times in its original format. Once the first data set is saved, the next identical data set will reference the original and avoid unnecessary duplication.
Subsequently, compression will further reduce the size of the data, reducing the amount of space needed to hold more data and also reducing the bandwidth of data centers. AI and Machine Learning (ML) also provide additional opportunities here.
3. Manage the energy consumption of storage systems
So software-defined storage adds a piece of intelligence to a storage system. For example, when a storage device doesn’t need to do anything, you don’t want it to be in full use. With intelligent software, you can downspin nodes or disks, bringing your power consumption down.
Advanced technology accounts for fluctuating workload demand and ensures that systems switch to an energy-saving mode when demand is limited. As soon as demand increases again, they can immediately reactivate. Hardware also wears out less quickly this way.
4. Put data flexibly in the right place
Finally, software makes it possible to always put data in the most efficient place. Load balancing, for example, ensures that workloads are evenly distributed across storage devices. That way, you avoid overloading one system. With data placement, you then go on to further evaluate the location of the data. High-performance data should be accessed quickly, while cooler data can be placed on slower, more energy-efficient and cheaper storage systems.
Conclusion? Data centers have a significant impact on our energy consumption. With new energy guzzlers such as AI applications, that footprint will only increase. Thanks to software-defined storage, data centers are at least future-ready and can grow with the needs of the market in an energy-efficient manner. They have the flexibility to make the optimizations needed to make data centers as sustainable as possible.
This is a submitted guest contribution by Pieter van de Burg, Senior Solutions Architect Benelux at DataCore. DataCore offers flexible software-defined storage solutions with SANsymphony and Swarm. Click here for more info and calculate how much energy you can save.