Addressing Multi-Cloud Challenges: Anant Adya's Perspective at Infosys

In today's rapidly evolving digital landscape, enterprises face the challenge of managing complex multi-cloud environments while harnessing the power of AI for operational excellence. To gain deeper insights into how a global leader like Infosys navigates these challenges, Manisha Sharma, Assistant Editor at Ciol, engaged in an exclusive interaction with Anant Adya, Executive Vice President and Service Offering Head at Infosys. In this exclusive interview, Adya shares his perspectives on multi-cloud management, AI integration, and how Infosys is preparing for the future."

How does Infosys approach the complexities of managing multi-cloud environments?

Infosys' approach to managing multi-cloud environments is meticulously designed to help enterprises harness the agility and innovation of cloud and AI while effectively navigating the complexity of multiple cloud environments. Our comprehensive approach yields tangible benefits, including optimal workload placement, cost-efficiency, and service assurance. We prioritize workload optimization, guiding clients to strategically place workloads across the cloud based on business needs and cloud provider strengths. This ensures peak performance, cost-efficiency, and service assurance. Our strategy, built on centralized management and governance, establishes a unified control plane for visibility, consistency, and security across all cloud platforms. We leverage automated processes powered by AI and ML to streamline operations and optimize resource utilization. At Infosys, we understand that a skilled workforce is not just important; it's crucial for long-term success in managing multi-cloud environments. We invest in training and fostering a culture of cloud innovation to ensure our clients have the expertise to harness the full potential of their multi-cloud environments. Infosys plays a pivotal role in empowering organizations to navigate the complexities of multi-cloud environments confidently. We achieve this by combining our expertise with strong vendor partnerships. We work closely with cloud providers to optimize costs, ensure service levels, and stay ahead of emerging technologies. This collaborative approach, combined with our unique strategy, enables us to unlock the full potential of cloud and AI for business growth and transformation.

What strategies ensure seamless integration and operation across different cloud platforms?

A multi-cloud strategy is crucial for businesses to meet technical requirements and compliance needs. It involves ensuring the stability of business processes and the resilience of the IT portfolio across different clouds. Integration is managed at three levels: business process, data, and operational. Each industry vertical has specific business standards for integration and interoperability. On the technology side, various architecture patterns of APIs, events, and callbacks address real-time and batch integration needs. Our proactive approach to service assurance in operations sets us apart, ensuring a unified observability platform across clouds and enhanced self-healing capabilities with AIOps. The unified observability is typically created in a federated model, with direct management control within a cloud platform and aggregate signals for correlation and triggering targeted actions in each cloud platform.

In what ways is AI being utilized to automate traditional cloud administrative tasks?

Businesses today operate with a combination of conventional work processes and cloud-based operations. They use a unified cloud management platform to ensure their systems are resilient. New work processes are designed to manage themselves while existing work processes are automated using observability and AIOps. Machine learning and AI are actively used with traditional work processes for monitoring and alerting. This exciting development allows businesses to generate useful alerts and reduce unnecessary alerts. AI also plays a key role in self-repair activities based on alerts to restore expected operational standards. If AI-driven self-repair actions are impossible, humans step in, and AI assistance is used for in-depth data analysis and knowledge retrieval services.

Could you provide examples of how AI has transformed cloud management in specific industries like healthcare or finance?

Today, it's essential to have a comprehensive approach that includes both applications and cloud infrastructure to meet business SLAs. Integrating AI capabilities into cloud management is now necessary. For example, a major US bank needed to process all settlements within a specific timeframe, regardless of the number of transactions. They collected monitoring data from various sources such as business processes, applications, integrations, platforms, and infrastructure to ensure they meet business SLAs. They brought it all together on a single platform. They then used AI/ML to analyze trends and patterns in processing throughput and resource consumption. Based on how the transactions progressed, they dynamically managed resource allocation to meet the processing window while optimizing cloud costs. This approach is also used in FinOps.

What are the key challenges and opportunities in modernizing the data landscape across multi-cloud environments?

Data is crucial for enterprises, enabling operational efficiencies and business growth. Modernization is necessary across various areas such as identification, profiling, transferring, maintaining quality, and data consumption. The strategy for placing data workloads in the cloud should be based on proximity to the data source, transformation requirements, and the availability of advanced models and services for AI and machine learning. By adopting the right cloud strategy, the unique strengths of each cloud platform can be utilized while minimizing the risk of latency in data movement. Data lineage and governance help manage data quality in a multi-cloud environment, while embedded data security ensures data confidentiality and privacy. Robust data-sharing platforms are implemented to share data across an extended partner ecosystem spanning multiple clouds. This is complemented with confidential computing in distributed multi-cloud environments to facilitate collaborative data processing across enterprises while protecting their confidentiality and intellectual property.

How does Infosys Cobalt ensure data security and compliance when setting up cloud infrastructure?

Infosys Cobalt, a set of services, solutions, and platforms for enterprises to accelerate their cloud journey, presents a resilient, secure-by-design underpinning for industry-specific cloud platforms. This all-encompassing offering seamlessly amalgamates industry proficiency, multi-cloud management capabilities, and cutting-edge cybersecurity solutions. At the core of Cobalt lies an unwavering dedication to embedding security throughout the application lifecycle, from its initiation to deployment. Our flagship multi-cloud management platform, Infosys Polycloud, is meticulously crafted with a secure-by-design ideology, ensuring secure governance and control across varied cloud environments. Accompanying Polycloud is Infosys CyberNext, a secure-by-design cybersecurity suite with robust threat detection, prevention, and response capabilities. Collectively, these elements establish a fortified ecosystem that empowers enterprises to expedite digital transformation while mitigating risks. By placing security at the forefront, Cobalt enables organizations to propel digital transformation confidently, safeguarding their assets through a robust, secure-by-design architecture.

How does Infosys ensure that enterprises can quickly adapt to market changes and emerging technologies, and how does the cloud play a role in this?

Businesses in various industries are in different stages of digital transformation and are constantly working to digitize their business functions. For example, in a manufacturing company, this entails improving design, planning, production, distribution, and service to enhance customer experience and drive growth. Infosys Cobalt's industry cloud platform approach enables the creation of new business products more rapidly from existing business capabilities, allowing for quicker adaptation to market changes. The underlying technical platform facilitates the integration of new technologies while efficiently meeting security and compliance requirements. Infosys helps enterprise customers foster innovation and agility across business and technology domains through these capabilities.

What metrics or KPIs should organizations focus on to measure the success of their cloud and AI initiatives?

At Infosys, we group enterprise customers' digital transformation with cloud and AI into two main themes: 'Save and Optimize' and 'Grow and Disrupt'. In the 'Save and Optimize' scenario, cloud and AI help reduce IT costs and improve system performance. This involves tracking metrics like IT cost, business transaction costs, system availability, and response time for reduction while also working on reducing process cycle time and failure rates on the business side. In the 'Grow and Disrupt' scenario, cloud and AI enable technical services and scalability, leading to improved customer experience, market growth, and new product and service creation. This is expected to increase revenue, customer satisfaction, and margins.

How is Infosys leveraging generative AI to enhance cloud capabilities and What are the potential risks and benefits associated with integrating generative AI into cloud environments?

Infosys Topaz offerings focus on using AI and generative AI, while Infosys Cobalt focuses on cloud technology. They work together to add value to the business. We are using Topaz to increase the value of Cobalt and vice versa. For example, generative AI gathers knowledge from many projects in Cobalt's advisory and consulting services to create Cobalt Knowledge assets for new consulting projects. Additionally, to help developers work more efficiently in cloud-native development, generative AI tools and capabilities are integrated into the Infosys iLEAD Platform (Infosys Live Enterprise Application Development Platform). Using generative AI in cloud environments has led to quicker market launches, stability, and resilience while reducing costs. However, some risks are associated with generative AI, such as predictability/explainability, code quality, copyright/patent issues, software supply chain risks, and inadvertent data leakage. We can reduce these risks by implementing a responsible AI framework when using generative AI in cloud environments.

How is Infosys preparing to stay ahead in this rapidly evolving landscape and What advice would you give to enterprises looking to integrate cloud and AI technologies into their operations?

For over 40 years, Infosys has been the top choice for providing technology services to Global 2000 and other clients worldwide. We have developed processes and tools and made necessary investments to track technologies, set up Centers of Excellence (CoE) for experimenting with technologies, and create academies to increase the capacity to deliver with these technologies. For cloud services, we established Cobalt, and for AI, we developed Topaz to experiment and scale in a focused manner. In today's world, every enterprise needs to be digitally enabled to stay competitive and grow. Enterprises can reimagine their business processes and value chain across their internal organization and with partners as a digitally connected ecosystem. However, for this to happen, people across all parts of the organization need to be digitally savvy. Successful enterprises have set up academies for these technologies so that employees are eager to embrace new technologies rather than fear them in their jobs.

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