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Cloud migration has become a tech buzzword across enterprises worldwide. However, to be an effective cloud user means not only getting introduced to the concept, but also thoroughly evaluating your existing IT infrastructure and processes, identifying their potential in moving to cloud, and effectively planning your migration strategy. Given the many advantages of migration, businesses are looking to tap into the long-term benefits of cloud computing, which include:

Conducting an objective and accurate assessment of their existing services, applications, security, and network infrastructure has been a challenge for organizations. Numerous discovery tools, including Cloudscape, Cloudamize, Device42, and TSO Logic, can help you understand your on-premise infrastructure.

Though these discovery tools do a good job in terms of understanding the infra estate as well as other basic information like CPU, RAM, disk storage, and OS, they have their own limitations. Mostly, the assessments are far from being accurate during and after migration. This is because the organizations do not go deeper in terms of understanding the applications and the business. The most common challenges of cloud migration are:

Broad basing the discovery

The good news, however, is that none of these challenges are insurmountable. To make the migration process as smooth as possible, we need to discover or analyze the source code, configurations, applications, and databases too and not just focus on infra discovery.

This helps to better understand the internal dependencies of applications and the roadblocks in the migration process. Both static and dynamic analyzers should be used together with the infra discovery tool to have a fail-proof migration.

As static analyzers help understand the components of applications and their dependencies on 3rd-party applications, it helps analyze the impact of re-platforming or refactoring the application. This is where AI and ML can be used in conjunction with these mechanisms to get a better understanding.

The ML and AI journey to cloud

With Artificial Intelligence and Machine Learning (AI/ML) in cloud becoming mainstream, organizations are able to overcome these challenges. AI/ML automatically generate insights from data. From predictive maintenance in manufacturing plants and fraud detection in financial services to accelerating scientific discovery, businesses of all types can benefit from this technology.

This has also given rise to applications such as chatbots, virtual assistants, and search engines that rival human interaction capabilities. As the dynamic and complex business environments of the modern times require a shift to data-driven decision making, there is a growing demand for robust, lineage, governance, and risk mitigation tactics.

ID2C Changing the game of data discovery

ID2C is TCS proprietary ML-driven tool, which combines discovery tool and static analyzers outputs along with other available data and intelligently deduces technology stack and dependencies to derive more value. This enables accurate identification of a variety of different technologies from different vendors even when they are seemingly disconnected. TCS AWS business unit conducts assessment projects worth $5M every year while influencing more than $100M foundation, migration, and operations projects.

AI/ML-driven data discovery combined with anomaly detection is a critical aspect of big data and cloud cost optimization and has the potential to save enterprises significant amounts of money. So why did we create an artificial intelligence-based platform for enhanced data discovery? Benefits include:

As cloud native transformations are being increasingly sought after, TCS ID2C tool built on AWS cloud helps enterprises in their cloud journey by helping understand the on-premise environment better and thereby derives correct strategies to transform their application portfolio now and in the future.

Author Bio

TCS

Ph: +91 9731397076

E-mail: Guruprasad.kambaloor@tcs.com

Guruprasad Kambaloor works as a Chief Architect in the AWSBU division of TCS. Guru has a rich experience of 26+ years in the IT industry spanning many domains like Healthcare, Life Sciences, E&R, Banking, and multiple technologies like Cloud, IoT, Blockchain, Quantum Computing. Currently he heads the Platform Engineering for AWSBU which has built platforms like Cloud Counsel, Cloud Mason, Migration Factory, Exponence to name a few. His current interests are AI/ML, Quantum Computing, and its relevance/usage in Cloud.

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