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Corporate Success in the Era of Cloud Adoption

Ashutosh Dixit, Senior Director, LTIMindtree

Ashutosh Dixit is a tech-savvy and dynamic leader in the technology. With an illustrious career spanning several pivotal roles, Ashutosh has been an instrumental force for LTIMindtree Consulting, with great expertise in shaping innovative cloud architecture solutions. Presently, he spearheads digital transformation within the CIO Advisory orchestrating the convergence of technology and business strategies.

CIO Insider had the chance to engage with Ashutosh, during which he offered valuable insights into diverse elements surrounding cloud adoption, particularly within the present business landscape. Let’s read below.

What are the advantages of cloud computing, and how can a company effectively prioritize these benefits in its cloud adoption strategy?
Let's start with the key benefits of cloud computing that are commonly sought after by organizations. Firstly, cloud computing significantly reduces technology operational burdens. This allows companies to concentrate on their primary objectives associated to running their core business, and not managing IT Infrastructure.

Second, is the predictability of performance that cloud services offer. This doesn’t just mean faster or enhanced performance, but rather an assurance of what you would receive. Cloud services are controlled by engineers who provide instructions that significantly impact performance, which can be adjusted based on price and performance, as well as, a variety of available options.

In a traditional on-premise setup, companies were stuck with the same hardware for all workloads, irrespective of adequacy or excess power. But in the cloud, selecting the right performance for the right price becomes possible, ensuring expected performance—another significant benefit of cloud computing.

A company must understand its business case of why it initially opted for a cloud data center. It might have been to reduce capital expenditure, cut operational overheads, or embrace advanced technologies not previously available on-premises, such as AI/ML models or scalable systems. The company needs to align its strategy with these business cases, establishing use cases and pursuing strategies step by step.

How significant is scalability in cloud technology, and how should professionals ensure that cloud solutions can expand along with an organization's needs?
Scalability is incredibly important in cloud technology. It changed the way companies viewed data centers. Previously, the mindset was to anticipate the future usage of computer power and provision that capacity in advance. Companies would buy hardware, estimating the need for the next five years. Even if a workload required only occasional or short bursts of system use, companies would still purchase hardware sufficient

for continuous use. This created a paradox.

The paradox lies in the fact that if you prepare for future usage that hasn't materialized and buy hardware that remains idle most of the time; it leads to over provisioning and cost in-effectiveness.

On the other hand, if you maintain a baseline and avoid over provisioning, you may struggle to meet irregular but high demands. This could result in poor customer experiences, immediate business losses, or an increase in customer churn rates.

With cloud auto scaling capabilities “There would always be just right amount of compute power to run your program. Computing capacity would scale in and out based on the demand and little to none intervention from administrator.” So now you pay nothing for your workload if they are not in use and pay less when there is less customer demand and likewise.

How to deal with a disaster phase and what steps should be taken to overcome it?
My approach to a disaster recovery model involves three primary parts, “Assumptions, Planning & Action”. Firstly, it begins with assumptions. Often, companies lack an effective disaster recovery plan because they fail to anticipate potential disasters. A sound disaster recovery plan assumes that (“Any component that can fail, will fail”). Any system component can fail. This includes cloud regions, availability zones, internal hardware, compute resources, virtual machines, databases, storage, networking devices, and other critical elements. Check each one for any single point of failure, and where identified, strive to make these areas redundant to avoid complete system breakdown.

A competent architect always foresees potential disasters and maintains a well-prepared disaster recovery plan.

The second phase, the pre-planning stage, is equally crucial. It involves establishing business continuity. One aspect of the pre-planning phase is devising the right backup strategy and ensuring backups are stored in multiple locations. Some companies set up a (harness an alternate) cloud region known as the secondary region, distinct from the primary region where they conduct most of their operations. The secondary region primarily serves as a disaster recovery site, where workload would parallelly exist. This phase involves through check on compliance and data regulations. Sometimes, data must remain within the same country due to regulatory requirements, so it's important to consider this while selecting secondary region. This action directly addresses the mitigation of single points of failure.

The final phase ‘Action’ pertains to managing the actual disaster, as failures are inevitable. As previously stated, anything that can fail may eventually will. When a disaster occurs, provided the pre-planning phase has been executed effectively, handling the situation becomes more manageable. Systems should be in place to automatically detect disasters and execute predefined automation scripts to smoothly transition the entire workload, part of it or whole cloud data center. A competent architect always foresees potential disasters and maintains a well-prepared disaster recovery plan.

What metrics and KPIs do you use to gauge the success of cloud adoption within an organization?
Gauging the success of cloud adoption can be quite complex. One important metric considered is “Cost saved or Return on Investment” when comparing the cloud to traditional on-premises data centers. However, it's tricky calculation due to complex cost structures, variable cost, hidden dependencies & intangible benefits. Companies typically assess the cost-saving benefits over a few years rather than immediately.

Another key metric is the “Time to Market” for a product. Cloud's automation capabilities and swift resource provisioning can significantly expedite product launches, reducing time from months to weeks.

Moreover, ensuring business continuity stands out as a crucial KPI. On-premises centers are vulnerable to city-wide outages, impacting operations. Cloud, built for resilience, generally provides better uptime and fewer outages, improving application stability.

Additional intangible benefits include the impact of automation, SLAs, enhanced customer satisfaction, improved CX scores, and overall business growth compared to competitors post cloud adoption, showcasing the efficiency and effectiveness of the transition.

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