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Enterprises Must Expedite Hybrid Multi-Cloud Initiatives to Drive Business Outcomes


NelsonHall recently completed an in-depth analysis of end-to-end cloud infrastructure management services, in which we spoke to multiple leading IT services vendors and their clients. This blog looks at some of the key themes from this research, the investments vendors need to make to meet client demand, and how the market will evolve over the next 12 to 18 months.

There is an increasing focus on utilizing the cloud to deliver value across every business function within an enterprise; for example, improving security, compliance, and governance for the CSO and enabling HR to drive positive employee engagement and experience. In addition, cloud management and FinOps provide CFOs with greater visibility and management of the cloud ecosystem to control and optimize cloud costs and greater utilization of AI and automation to enable CIOs to focus beyond TCO. Vendors are creating cloud-native industry-specific solutions to support LOB heads and expedite enterprises’ ability to create and develop new products and services by sector.

The three overarching themes from this study were:

  • Enhancing hybrid cloud management and employee experience
  • Ramping digital re-skilling and empowering end-users
  • Increasing focus on AIOps and cloud-native capabilities.

Let’s look at these three focus areas in more detail.

Defining and measuring cloud journeys through co-creation

Vendors need to take a collaborative design thinking approach to cloud transformation to co-create and innovate with clients to support business outcomes. This includes utilizing AI and analytics in the initial cloud advisory and assessment stages to improve the overall cloud transformation roadmap. This takes a three-phased approach, including:

  • Advisory and assessment: enabling data-driven insights to provide deep discovery of infrastructure and application assets. Also, cloud architecture analysis and identifying the right cloud type (IaaS, PaaS, SaaS) and approach (private, public, hybrid). Then developing cloud maturity roadmaps including OCM to deliver the desired client outcomes through the identification of business needs and driving digital adoption
  • Migration and modernization: identifying application modernization opportunities, including monolithic architecture implementation and deployment. Then deploying a migration factory approach with templates, repeatable tasks, and agile squads. This includes landing zone and platform build, including cloud-native and adoption of DevOps and serverless architecture. An example includes Capgemini’s Cloud Migration Factory, providing a highly automated and industrialized approach to application and infrastructure migration. This includes providing end-to-end migration from package to production using an automated release pipeline and a migration management portal. It also provides an assessment tool for cloud cost optimization for clients that have already migrated to the cloud
  • Operate and manage:  Clients want to manage hybrid, multi-cloud environments through a single CMP console with self-service and automated provisioning with a single click. This also includes the integration of private cloud and edge. There is also a greater focus on cloud-native PaaS support, including microservices and containers. This includes a more open approach to orchestration, including cloud-native provisioning with cloud APIs. In addition, integration of third-party monitoring and visualization tools to tag, monitor, and optimize spend based on usage patterns, with automated reporting and chargebacks to business units through FinOps. 

Over the next 12-18 months, we expect vendors to rapidly increase the utilization of Cloud CoEs, labs, experience centers, and Digital Transformation Centers to help clients prototype and co-create cloud-first solutions to facilitate this approach.

Vendors need to identify and measure employee experience, define industry personas, and personalize experience services across the enterprise. They need to continue to invest in end-user analytics tools to measure employee sentiment and performance, with typical tools including 1E Tachyon, SysTrack, Nexthink, and Qualtrics. These measure UX across devices, applications, and networks.

Digital re-skilling continues at pace

We continue to see traction in digital re-skilling, hyperscaler certifications, and new skill-sets, including machine coaches developing algorithms for AIOps systems, automation, AI architects, cloud-native SMEs, data analytics, and business value specialists. Also, vendors are ramping cloud academies, experience centers, and site reliability engineers (SRE) to monitor cloud ecosystems’ performance through a data-driven approach and building capabilities and enhancements based on what SRE teams learn from operating cloud environments for clients. For example, across cloud operations, TCS takes a service reliability engineering approach with dedicated teams resolving issues and platform and architecture teams automating activities and enabling greater self-service.

TCS also uses its cloud units as a catalyst for talent change across the organization, enabling infrastructure specialists to become full-stack architects. In addition, developing industry-specific skillsets across cloud delivery resources by utilizing TCS’ industry SMEs.

Vendors are now hiring beyond STEM and across tier 2/3 cities in India, with Tech Mahindra recently opening a delivery center in Coimbatore. Vendors are further utilizing AI-enabled learning assistants and platforms to expedite training. For example, Infosys utilizes its Wingspan learning platform to support cloud training, and its talent strategy focuses on emerging technologies, with 350 learning paths and 46 digital skill tags.

Over the next 12 months, the focus on dedicated experience centers will increase, supported by SRE teams that look at the experience aspect of IT service delivery and proactively monitor end-users’ sentiments as they engage across services and XLAs (and work with clients to create specific XLAs by persona). We also expect to see more focus on end-user empowerment using low code/no code platforms and managing, for example, M365 through the Microsoft Power Platform.

Expanding AIOps use cases to meet client-specific requirements

AIOps are being deployed to trigger automation to auto-remediate and fix issues, including utilization of resolver bots (L0, L1, and L1.5 functions). Also, to detect anomalies, reduce noise across operations, and use ML and diagnostics engines to manage L2/L3. End-user outcomes include ~40% improvement in MTTR, ~45% incident elimination, and ~65% of incidents autonomously resolved.

We expect vendors to expand their use cases to enable transitions to future no-ops. Vendors look to orchestrate tasks using AI and automation and use recommendation engines to provide the best-fit SOP for the issue through one-click automation. There is increased focus on standardization through template-based provisioning of environments and standardized monitoring and data collection frameworks. NTT DATA, for example, adopts a data bias in support of cloud transformation where it makes decisions based on data insights to influence new application features, developments, and architectural improvements.

Vendors must build libraries of standard AIOps use cases to meet clients’ business outcomes, manage operations across the full stack, and achieve ~40-50% reusability on standard assets through enterprise bot stores. This includes increasing the use of cloud architects and administrators to develop infrastructure and industry-specific cloud blueprints, including templating application blueprints. They need to focus on developing service patterns that provide repeatability through a combination of hyperscaler technologies and vendor IP to address specific industry and client requirements. In addition, they need to integrate with and utilize client toolsets where required through an agnostic approach. Also, taking a modular approach to reflect clients’ Brownfield automation capabilities.


Investment in end-to-end cloud infrastructure management services will continue at pace, with a greater focus on developing a full-stack organizational structure to deliver cloud transformation through productized offerings. We expect to see increased focus and investment in sustainability and helping clients reduce carbon footprints. This includes continuous monitoring through cloud management platforms, green apps, and observability tools. TCS, for example, adopts a sustainability by design approach to drive configurable, composable, and automated infrastructure to adapt the cloud to environmental, social, and governance needs.

There will be an increase in modernization accelerators and methodologies to enable clients to modernize legacy applications and take advantage of the latest hyperscaler technologies. This includes modernization factory, CoE, and dedicated squads deploying an agile approach and making recommendations for modernization. Application modernization investments will focus on microservices, service mesh, API factory development, and serverless functions.

It will be important to ramp digital re-skilling, hiring, and retention initiatives to ensure the requisite cloud skills are in place to meet specific client requirements and support business outcomes.

Expect vendors to ramp cloud-native services and practices to provide complete end-to-end hybrid services for containerization and move containers off datacenters to the cloud. Also, to provide a unified view of observability, management, and deployment across containers and expand their mainframe as a service capability.

Finally, we expect increased investment in AI-based platforms and tools to enable a self-heal framework, increase autonomous remediation and an SRE-led approach to cloud operations, and a greater focus on joint IP and GTM with hyperscalers.

Find out more about NelsonHall’s ‘End-to-End Cloud Infrastructure Management Services’ market assessment report here or contact Guy Saunders.

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