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Resources / Analyst Report

Gartner recognizes Avesha and states that an emerging technology can automate the optimization of price and performance while achieving predefined business objectives

In their report titled, "How Platform Engineering Teams Can Augment DevOps With AI." Platform engineering teams play a crucial role in managing and optimizing software delivery infrastructure across all SDLC environments. When platform engineers use self-service tools and AI-augmented technologies, they can balance cost, reliability, and sustainability to ensure efficient software delivery.

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In the figure Gartner emphasizes that Platform Engineering Teams Support Tooling for AI-Augmented Optimization of Infrastructure Costs, Reliability, Sustainability.

Key aspects highlighted in the figure as per our understanding

AI-Augmented Tools for Cost Optimization:

Rightsizing Recommendations

Tools that analyze resource usage and provide recommendations to ensure that infrastructure resources are neither over-provisioned nor under-utilized, leading to significant cost savings.

Dynamic Resource Allocation

AI-driven solutions that adjust resources in real-time based on workload demands, helping to avoid unnecessary expenses.

Enhancing Reliability with AI:

Predictive Maintenance

AI tools that predict potential failures and suggest proactive maintenance, reducing downtime and improving system reliability.

Anomaly Detection:

Systems that detect unusual patterns and behaviors in real-time, enabling quick responses to prevent issues before they escalate.

Sustainability Goals:

Energy Efficiency:

AI-powered solutions that optimize energy consumption by managing resources more efficiently, contributing to environmental sustainability.

Carbon Footprint Reduction:

Tools that provide insights and recommendations for reducing the carbon footprint of infrastructure operations.

As described in the Report

Overcoming Challenges in Cloud Infrastructure

"Optimizing public cloud infrastructure is becoming especially difficult - but important at the same time. This is primarily due to the dizzying array of cloud services, inconsistent pricing models, the distributed nature of cloud-native applications, and seasonality in traffic patterns. To manage and govern infrastructure reliably, cost-effectively and sustainably, platform engineering teams should provide self-service platforms and tools that support Al-augmented optimization of costs, reliability and sustainability to product teams. Emerging technologies - such as autonomous workload optimization and augmented FinOps - can automate the process of optimizing price/performance while achieving predefined business objectives.”

Leveraging AI for Infrastructure Optimization

Gartner emphasizes the importance of integrating AI-augmented optimization tools to address constraints across the SDLC, ultimately enhancing cost savings, reliability, and sustainability, which are critical for modern software engineering practices.

In addition to this research report on augmenting platform engineering with AI,

Avesha has also been recognized as a Sample Vendor in the following Gartner® Hype Cycle™ Reports

Hype Cycle for Infrastructure Strategy (July, 2024)

Hype Cycle for Infrastructure Platforms (July, 2024)

Hype Cycle for Container Technology (July, 2024)

Hype Cycle for Data Center Infrastructure Technologies (July, 2024)

Gartner, How Platform Engineering Teams Can Augment DevOps With Al, By Manjunath Bhat, Cameron Haight, Bill Blosen, 8 January 2024

Gartner, Hype Cycle for Infrastructure Strategy, 2024, By Philip Dawson, Nathan Hill, 17 June 2024

Gartner, Hype Cycle for Infrastructure Platforms, 2024, By Dennis Smith, 25 June 2024

Gartner, Hype Cycle for Container Technology, 2024, By Dennis Smith, 20 June 2024

Gartner, Hype Cycle for Data Center Infrastructure Technologies, 2024, By Henrique Cecci, Philip Dawson, 27 June 2024

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, HYPE CYCLE is a registered trademark of Gartner, Inc, and/or its affiliates and is used herein with permission. All rights reserved.

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Avesha.

Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.