---

Autonomous cloud operations

Blog: OpenText

Greetings from Skye, a trusted partner for your AI journey. This AI-generated llama has been living in the clouds, creating her own cloud trails to follow. Skye has spent the last six months working with IT departments to better understand current and future needs for cloud operations. 

You:  What is going on in IT departments around the globe?

SKYE: Limited resources, too many priorities, AI creating new parameters and needs.

You: What’s top of mind today for CIOs? 

SKYE: AI has brought back the need to think about cloud operations and data strategies end-to-end. 

You:  Why is that? 

SKYE: CIOs and CDOs are responsible for the management of information and technologies. The recent acceleration of generative AI is raising interest–every department wants their AI use cases and every company is spinning up internal AI initiatives.  But the promise of AI is dependent upon sound data strategies, cloud infrastructure, and information management as a pre-requisite. Without trusted data lakes that are well-governed and well-managed cloud operations, CIOs and CDOs cannot afford to take on AI initiatives.

You:  So how should forward-thinking CIOs and CDOs approach getting their cloud foundation right?

SKYE:  Just like anything else, it’s about managing complete and autonomous cloud operations. For a while, the lack of resources for operating cloud hindered many organizations. Then, cloud got expensive and the tradeoffs between scale and price became real. Now, looking forward, running cloud operations well will be widely dependent on visibility and discoverability.     

Let the machines do the work

Most enterprise organizations live in a multi-cloud environment. Data, assets, and applications are in public clouds, private clouds, consumed via API, and on prem. The complexities of thousands of applications across multiple environments are typically high.

Managing modern IT cloud operations starts with an end-to-end view:

• Asset discovery: location and viability of all IT assets across multiple clouds
• Observability: health of applications, product telemetry, cloud infrastructure, networks
• Security: scanning, data protection, threat intelligence, and recovery
• Correction: workflow for managing fixes across cloud operations 
• Cost & carbon management: containing on cloud costs and carbon footprint    
• Service experience: help desk for IT  

Once cloud operations can be broken down into these competency areas, automation and AI can be applied to drive simplification:

• Autonomous asset discovery across multi-clouds
• AI-assisted management of applications, networks, infrastructure, and product telemetry data
• Security everywhere–XDR for endpoint protection and predictive threat intelligence  AI-driven rules, workflow, resolution across the IT landscape  
• Fin-ops with predictive AI to contain cloud-consumption costs
• Green ops to track and see various layers of impact (scope 1-2-3) for sustainability goals
• AI-assistants as level 1 support for employees  

Learn more about how you can get started with OpenText™ Service Management, OpenText™ Asset Management, OpenText™ Universal Discovery, and OpenText™ Universal CMDB. These new solutions from OpenText enable businesses to reimagine IT operations. The future of autonomous decisions and letting the machines do the work with AI assistants will shift the world of IT operations. Don’t be left behind.

Catch a five-minute interactive tour of IT Operations Aviator. View OpenText World Europe keynotes for more information. Visit www.opentext.com.

The post Autonomous cloud operations appeared first on OpenText Blogs.