Optimizing Cloud Costs with Sustainability Goals with Intelligent Automation

Here is an article by Geeta Gurnani, IBM Technology CTO & Technical Sales Leader, IBM India & South Asia.

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Geeta Gurnani, IBM

As businesses continue their digitization journeys, adopting cloud-based solutions has become an essential part of this transformation strategy. However, once in the cloud, approximately 80% of companies report receiving bills two to three times higher than estimated. This poses a significant challenge, especially since most businesses today are facing strong economic headwinds and are looking at ways to increase revenue while reducing operational costs.

Many believe that the important driver for cloud adoption is that you pay for what you use, but that is an inaccurate assumption. In reality, organizations pay for how much they anticipate demand and provision cloud resources to meet that demand. It’s however, almost impossible for humans to continuously determine the exact compute, storage and database configurations to deliver performance at the lowest cost. To compensate, most enterprise IT teams over-allocated resources to ensure there are no application performance risks. This difference between consumption and allocation leads to cloud bills to skyrocket.

Supplying cloud resources to match demand in real-time across multiple applications, metrics and dimensions requires complex calculations and split-second decisions, that cannot be made manually.

While for most organizations managing cloud costs would be the biggest problem, they cannot compromise on performance either — the two are tightly entwined. This balancing act is putting enterprise IT teams under unrelenting pressure.

To tackle this, IT teams need an intelligent automation solution that can do three things:

  1. Enable continuous performance – to automate responses to performance issues and remain compliant with service levels without impacting client requirements.
  2. Refocus manual labour – to help them spend less time monitoring and allocating resources, and focus on more critical projects.
  3. Increase efficiency – Automatically address resource underutilization or overprovisioning with true full-stack visibility to run a more cost-effective infrastructure.

Mastering Cloud Cost Optimization

Using the IBM Turbonomic platform, IT teams can achieve all three and eliminate the guesswork. The platform’s AI-powered automation and cloud cost optimization solutions ensure the best application performance and compliance (across public, private, multi-cloud and hybrid cloud environments) while optimizing costs. Quite simply, Turbonomic allows for smarter cloud investments and easier automation – and when intelligent software acts automatically you gain the value of speed, scale and agility while being sustainable.

A leading Indian System Integrator (SI), for example, needed to ensure seamless cloud adoption and elasticity for their customers while optimizing costs. They turned to IBM Turbonomic to address their cloud cost and performance challenges – achieving 20% cost savings on their cloud infrastructure and increased operational efficiency, enabling them to focus on delivering more value-added services to their customers. Turbonomic also enabled them to provide their customers with predictable and consistent application performance, driving increased customer satisfaction.

Achieving Sustainability Goals – The Client Zero Story

Sustainability has become an important boardroom discussion and as many organizations are starting to strategize how to build a more sustainable enterprise – having an application resource management solution like Turbonomic will become indispensable.

At IBM, we are using Turbonomic at the IBM Hursley data center to conserve power use across 4,500 physical systems without compromising on performance to achieve our carbon-neutral goals. Turbonomic helped the team identify opportunities to rebalance resources to maximize utilization of their existing infrastructure, providing financial and environmental benefits. The team was able to reduce capital expenditure on new hardware and minimize the carbon footprint by reducing the electricity required to both power and cool unnecessary infrastructure.

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