Today businesses are drowning in data. To stay afloat they need to make sense of it all. Artificial Intelligence (AI) and Machine Learning (ML) are the tools that make this possible. They automate, find hidden patterns and predict future trends. So companies can optimise, save time and win in the market. The way they operate is changing and AI and ML are at the heart of it. Josson Paul Kalapparambath is a tech leader who is driving this change. His Senior IEEE membership is a testament to his commitment to technology. As a SARC Editorial Board contributor he shapes the field and standards. He is an active participant and deeply involved in exploring AI and ML in complex systems. This is why he’s a leading voice on these technologies.
“In the age of information, efficiency is not just about processing data but architecting intelligence. We need to design systems that not only handle the volume but illuminate the path to success.” – Josson Paul.
Transforming Network Data with the Power of AI and ML
The amount of network data being generated daily is enormous—by 2025 it’s going to be 181 zettabytes. AI and ML are needed to manage this data. AI driven analytics platforms have already improved network operations by 95% reduction in downtime and 40% increase in efficiency. Businesses using AI for network automation have tripled troubleshooting speed, reduced cost and improved performance. Instead of just collecting raw data, AI turns it into predictive insights so failures can be prevented.
Josson Paul has been a part of this journey, shaping the Cisco DNA Center’s Network Data Platform and Assurance since 2017. He has ensured AI and ML transforms raw data into actionable insights for proactive network management. His key contributions include:
- AI powered analytics for real time network data categorization and analysis.
- Automated troubleshooting and predictive issue detection with ML.
- Intelligent scheduling algorithms for resource allocation.
- AI driven anomaly detection and decision making in Cisco DNA Center Assurance.
Josson Paul’s expertise in data flow and system stability shared in Dzone and Hackernoon has strengthened Cisco DNA Center’s AI/ML platforms. His focus on foundational technologies has turned network data into actionable intelligence and improved management.
“Information is not in the data, it’s in the transformation.” – Josson Paul
Advancing AI and ML to Solve Networking Challenges
When building Cisco DNA Center’s data processing and storage platform, Josson Paul needed expertise in cloud computing, AI-driven analytics and software engineering. He was responsible for scalability, efficiency and real-time processing across hybrid environments. He solved two big problems: scalability in the cloud and large scale data processing in resource constrained on-premises clusters.
Unpredictable data surges in cloud environments like AWS required a balance of performance and cost efficiency. Static infrastructure provisioning was inefficient. Josson Paul introduced dynamic auto-scaling for real-time adjustments. AI-driven workload distribution allocated computing power as needed to prevent bottlenecks and reduce costs. Predictive analytics predicted congestion and enabled proactive resource allocation. He optimized data routing, filtered out unnecessary data and prioritized critical insights.
On-premises environments had hardware limitations making real-time analytics difficult. Java based applications underperformed due to resource constraints. Josson Paul re-engineered data pipelines to prioritize essential telemetry, reduced latency. He optimized storage mechanisms for faster access and fine-tuned ML models for better performance. He made open-source technologies work seamlessly with Cisco’s infrastructure.
To improve efficiency Josson Paul introduced AI-powered scheduling algorithms that enabled network automation. These algorithms allowed Cisco DNA Center to:
- Prioritize high impact tasks, reduce delays and optimize response times.
- Automate issue resolution and enable self-healing networks.
- Distribute resources evenly to prevent congestion.
Using AWS-based solutions and Python and Java frameworks, Josson Paul built a scalable, high-performance architecture for hybrid environments. His work enabled real-time analytics and built a foundation for self-sustaining AI-driven networks, saving costs and enabling predictive decision-making.
The Impact of AI and ML on Business Efficiency
Josson Paul’s work on Cisco DNA Center has greatly improved network management for Cisco and its users. His contributions have optimized networks, reduced downtime, and boosted operational efficiency. By transforming data into insights, he has streamlined processes and driven commercial success. Also improved user experience and security compliance.
“AI is not a concept; it’s a force that turns data into decisions and decisions into competitive advantage.”- Josson Paul.
What’s Next in Network Optimization?
As AI and ML move forward Josson Paul sees a future where network infrastructure keeps up with digital complexities. He foresees a move from reactive troubleshooting to proactive orchestration where AI optimizes performance and security on its own. He believes organizations will:
- Use AI to allocate network resources based on real time needs and priorities to be more cost efficient and performant.
- Connect the dots between issues across network, application and security to get clarity for quick problem resolution.
- Build systems to manage network service chains to deploy new features fast.
- Apply algorithms to historic data to predict future needs and scale infrastructure proactively.
AI doesn’t replace human intelligence – it amplifies it. Make businesses smarter, faster and stronger – Josson Paul
By combining the power of AI and ML, Josson Paul is helping organizations turn their network into a strategic asset and win in the digital game.
