#green cloud

Cloud cost optimization is the practice of reducing unnecessary spending and improving efficiency within cloud environments by aligning resources with actual business needs. As organizations scale, cloud expenses can quickly spiral due to idle workloads, overprovisioned resources, and lack of visibility. Effective optimization ensures every dollar spent drives measurable business value, balancing agility with financial discipline.

The importance of cloud cost optimization extends beyond cost-cutting. It empowers businesses to improve governance, forecast expenses accurately, and sustain long-term scalability without overspending. Key drivers include visibility into cloud usage, rightsizing resources to match demand, eliminating waste, and adopting automation for scheduling, provisioning, and governance. Architecting applications for cloud-native scalability using reserved instances, spot pricing, or serverless models further enhances performance while reducing costs.

The benefits are multifaceted. Businesses gain improved ROI, operational efficiency, predictable forecasting, scalability with control, and even sustainability through reduced energy waste. However, challenges remain, such as complex provider pricing models, shadow IT, and cultural resistance to cost accountability. Overcoming these requires financial governance, analytics-driven insights, and a collaborative FinOps culture where finance and technology teams share responsibility.

Technology is central to enabling optimization at scale. Advanced platforms powered by AI and predictive analytics provide real-time visibility, automate cost-saving measures, and recommend optimal purchasing strategies. As cloud adoption matures, future trends will include AI-driven orchestration, green cloud initiatives, and unified optimization platforms that merge monitoring, governance, and cost management.

Ultimately, cloud cost optimization is not optional it’s a necessity for sustainable digital transformation. By proactively managing spend, eliminating waste, and leveraging intelligent automation, organizations can maximize the true value of their cloud investments while driving innovation with financial discipline.

The Road Forward

CANDY FLOSS CLOUDS

Figure: Proposed EH-GC architecture (credits:  Saurabh Singh, Pradip Kumar Sharma, Seo Yeon Moon and Jong Hyuk Park)

EH-GC: An Efficient and Secure Architecture of Energy Harvesting Green Cloud Infrastructure

Authors: Saurabh Singh, Pradip Kumar Sharma, Seo Yeon Moon and Jong Hyuk Park

Journal Title: Sustainability

ISSN: 2071-1050 (Online)

Publisher: MDPI AG

Nowadays, the high power consumption of data centers is the biggest challenge to making cloud computing greener. Many researchers are still seeking effective solutions to reduce or harvest the energy produced at data centers. To address this challenge, we propose a green cloud infrastructure which provides security and efficiency based on energy harvesting (EH-GC). The EH-GC is basically focused on harvesting the heat energy produced by data centers in the Infrastructure-as-a-Service (IaaS) infrastructure. A pyroelectric material is used to generate the electric current from heat using the Olsen cycle. In order to achieve efficient green cloud computing, the architecture utilizes a genetic algorithm for proper virtual machine allocation, taking into consideration less Service Level Agreement (SLA) violations. The architecture utilizes Multivariate Correlation Analysis (MCA) correlation analysis based on a triangular map area generation to detect Denial of Service (DoS) attacks in the data center layer of the IaaS. Finally, the experimental analysis is explained based on the energy parameter, which proves that our model is efficient and secure, and that it efficiently reuses the energy emitted from the data center.