Research has shown that information and communication technology’s true proportion of global greenhouse gas emissions, including cloud computing, could be around 2.1-3.9%, which equates to higher emissions than the aviation industry. And as businesses increasingly rely on the cloud, minimizing this impact becomes critical.

While most major cloud providers are talking about going green– AWS and Microsoft Azure are pledging to use 100% renewable energy by 2025 – choosing a green cloud provider isn’t the only thing businesses do. 

The foundation of green cloud computing lies in optimizing resources and reducing energy consumption throughout cloud infrastructure. Although it requires added effort for companies and IT professionals, it’s also hugely beneficial to businesses overall as it leads to reduced costs and greater efficiency.  

So, let’s dive into three tactics that can help businesses shrink their carbon footprint, lower energy costs, become more efficient, and contribute to a more sustainable future.

Benefitting from Server Virtualization

Server virtualization allows IT professionals to create multiple virtual machines (VMs) on a single physical server. Imagine a physical server like a large apartment building and VMs like individual apartments. Each VM acts like a dedicated server with its own operating system and resources, but they all share the underlying hardware of the physical server. 

So, ​instead of running numerous servers with low utilization rates, this technique reduces the number of machines needed, allowing for lower energy consumption, improved efficiency, and optimized resource usage. 

And if businesses need more resources during peak hours, they can spin up new VMs instantly to handle the load based on real-time demands. There’s no need to buy, configure, and install entire physical servers, fostering agility and responsiveness to changing market conditions.

Furthermore, virtualization minimizes wear and tear on physical hardware by consolidating server utilization, extending its lifespan. This translates to fewer server replacements, resulting in decreased manufacturing emissions and reduced waste from discarded hardware.

So, increasing server utilization can significantly impact ​​cost savings, which is paramount for any successful business. And according to Gartner, decommissioning a single server can save $500 in energy, $500 in operating system licenses, and $1,500 in hardware maintenance costs annually.

Plus, businesses must be ready for all eventualities, meaning disaster recovery plans. And since virtualized servers can be easily migrated and backed up, this enables faster and more efficient disaster recovery, minimizing downtime and ensuring business continuity.

Smart Resource Allocation 

In the ever-evolving world of IT, smart resource allocation isn’t just about keeping servers at maximum capacity, but it’s about boosting efficiency, agility, and cost-effectiveness. It’s the art of putting the right resources in the right hands at the right time, and it can be a company’s secret weapon for optimizing performance, staying ahead of the curve, and going green.

But what exactly does smart resource allocation entail? There are a variety of techniques and solutions that could fall under this term, but some popular initiatives include auto-scaling and rightsizing instances. 

The former involves implementing auto-scaling policies to adjust resources based on workload demands. This ensures businesses have enough resources to handle peak loads without over-provisioning during periods of low demand. Most cloud providers offer built-in auto-scaling features, such as AWS Auto Scaling, Azure Autoscale, and Google Cloud Autoscaler. In fact, research has shown that auto-scaling can reduce energy usage by between three to five times. 

The latter works by regularly analyzing cloud infrastructure to ensure users use the suitable instance types and sizes for their workload. Tools like AWS Cost Explorer, Azure Advisor, and Google Cloud’s Rightsizing Recommendations can help identify underutilized resources and suggest appropriate sizing adjustments.

By understanding resource demands, usage patterns, and performance metrics through data analysis, IT professionals can optimize resource allocation to avoid overprovisioning and underutilization, enhancing the performance of their cloud environments. 

Moreover, by monitoring resource utilization and optimizing configurations, smart resource allocation techniques help companies mitigate the risks associated with resource constraints, performance bottlenecks, or unexpected spikes in demand. 

By ensuring they have the right resources available when needed, companies can maintain service reliability and continuity, minimizing the impact of potential disruptions on their business operations, and increase application response times and user experiences, improving customer satisfaction and retention.

These practices are integral to green cloud computing strategies as by optimizing resource allocation and minimizing energy consumption, organizations can reduce their environmental footprint while simultaneously enhancing operational performance. 

Data Storage Optimization

Data centers consume 10 to 50 times the energy per floor space of a typical commercial office building –which collectively account for approximately 2% of total U.S. electricity use. So, controlling a company’s data storage can make a significant difference when trying to be more sustainable. 

As the name suggests, data storage optimization involves strategies that squeeze the most out of a company’s storage while maintaining essential functionality – and there are various ways of achieving this. 

Firstly, IT professionals can identify and delete redundant data, as at least 30% of an organization’s unstructured data is obsolete. They can implement tools and policies to identify and eliminate duplicate and trivial data by leveraging deduplication software, file versioning policies and regular data audits.

Once redundant data has been dealt with, IT professionals can efficiently compress the data they need. Using data compression techniques like Gzip or Brotli to shrink data size without compromising integrity can significantly reduce storage requirements and energy consumption.

Infrequently accessed data can be transferred to economical archive tiers, such as Amazon Glacier or Azure Archive Blob Storage. This type of storage minimizes energy consumption for less frequently accessed information and has the lowest costs per gigabyte, freeing up primary storage for frequently used data. 

Getting data storage under control and ordering it more efficiently can reduce costs, as most cloud providers charge based on the storage used. Optimized storage systems also facilitate easier data organization, search, and retrieval, enhancing data accessibility and usability. With less data to sift through, processing speeds can improve, leading to faster data analysis and decision-making.

The cloud’s potential for agility and innovation is undeniable, but its environmental impact must be addressed. By implementing server virtualization, smart resource allocation, and data storage optimization, businesses can unlock the power of the cloud while reducing their carbon footprint. The journey to a greener cloud isn’t a passive one. It requires commitment, investment, and continuous improvement. But the rewards are substantial: reduced costs, enhanced efficiency, and contributing to a greener planet.