One of the greatest lessons of the cloud era is that the economic advantages of the cloud come to those who make them happen. The cloud on its own does not deliver improvements in application performance or financial payoffs. In fact, the opposite can be true if cloud managers are not diligent. The problem is that manual processes for managing cloud complexity are impossible to perform at scale.
Automation is required to effectively guide cloud optimization processes. An emerging breed of AI-driven cloud optimization solution now offers such a capability. In this report, PeerSpot members who use the IBM® Turbonomic® platform weigh in on best practices for selecting such a cloud optimization solution. In their view, the right solution will be one that puts the performance of the application first, leverages automation, supports Kubernetes, increases IT productivity and reduces cloud costs.
Savings of 30% - 35% in human resource time and cost involved in monitoring and optimizing cloud estate resources
Savings in cloud spend from an organization spending more than USD 3 million per year in Microsoft Azure
4-5 dedicated administrators needed to provision and manage a complex public cloud estate, down from 46 prior to leveraging automation
Accelerating cloud adoption brings agility and empowers speed to market, but it also introduces common cost and organizational challenges.
Applications run your business. Learn how you can safely reduce the costs to deliver cloud applications while ensuring peak performance.
Learn how differentiated automation techniques can give your cloud and applications teams the upper hand, and dramatically reduce the need for human troubleshooting.
The best cloud optimization solutions predictably and safely reduce costs and increase the productivity of your teams by large margins.