Moving business applications, IT infrastructure, and platforms to the cloud is a vital part of digital transformation, expanding organizations’ storage repositories and giving them greater computing power, flexibility, security, and access to the latest AI, machine learning, and automation capabilities. It also has the potential to create a competitive advantage, drive operational efficiency and enable innovation and growth.

The shift towards a Cloud-native, data-first model requires enterprises to shift their workloads rapidly and cost-effectively from traditional RDBMS and other legacy data stores, which are spread disparately across the enterprise into a single data lake and involves shifting towards a cloud-native distributed computing architecture. Some of the key characteristics of this architecture include:

• dynamic (real-time data ingestion and extraction), scalable and performant
• Seamless data access by SaaS applications
• Interactive BI insights at scale and with high performance
• All data is curated and ready for ML and AI-based workloads
• Allows distributed developer teams to work more efficiently and not have to worry about scale and performance and focus their efforts on feature development
• Leverages open-source technologies combined with cloud vendor proprietary services while avoiding vendor lock-in ensuring a low total cost of ownership for its customers

The IT industry today lacks the skills and talent to fill this gap with many enterprise customers and this trend is unlikely to change for the next 3-5 years.

Citridot intends to fill this gap by leveraging its deep technical skills and knowledge in this area as follows:

• Provide continuous one-stop leadership, architecture, and design services for its customers and map them to their specific industry vertical and application use case for leveraging a data-first application model.
• Create technical frameworks and accelerators by pre-integrated and pre-configured specific design patterns for the application at hand to abstract the big data tech from the application.
• Adopt a proven process-driven model for consistently developing, deploying, monitoring, and optimizing the overall customer grid on a single or across multiple public, and private clouds.
• Assemble agile self-contained delivery cells (one or more ) that can continuously develop and manage customer systems and act as an extension to their development teams.