Kumar Pallav ๐ฎ๐ณ
@kumar_pallav
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Avid follower of Sanatan Dharm ๐๐| Runner ๐โโ๏ธ| 12 YOE | Java โ | Spring ๐ | Quarkus โด๏ธ | Micronaut ๐ฉโ๐ | Open source | Microservices ๐ฆ
Bangaluru,Karnataka
Joined May 2010
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This is just the beginning, but I see it as a strong foundation for building AI assistants that can connect with real-world tools and APIs. ๐ Repo link:
github.com
Contribute to CODINGSAINT/agentic-ai-demo development by creating an account on GitHub.
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Hereโs what it does: ๐งฉ Blends conversational AI with utility functions (like date/time operations). โก Streams responses using Spring Boot + Reactor for a smooth experience.
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โจ Letโs explore how to build agentic AI systems โ AI that doesnโt just chat, but can also use tools, fetch data, and perform real tasks. As a starting point, I created this project: Agentic AI Demo.
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#WATCH | Delhi | On the launch of 'Para Emojis' at Khelo India Para Games 2025, FIT India Ambassador Pankhuri Srivastava says, "...We are promoting inclusivity of para-athletes. Here, we are celebrating the enthusiasm and zeal of all the para-athletes. In this second edition of
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Key benefits and challenges of event-driven systems. โ
How it differs from message-based communication. โ
Real-world use cases in e-commerce, banking, and ride-sharing apps.
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https://t.co/EqkOyhqbZx Event-Driven Architecture, explain why it has gained popularity, and how it differs from traditional REST-based microservices. Youโll learn: โ
What is Event-Driven Microservices? โ
Why microservices need event-driven communication?
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Mastering Spring Boot HTTP POST request https://t.co/xA2coW55Eb via @YouTube
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Donโt cache everything! ๐ Caching the wrong data can lead to bloated memory and slower performance. Focus on high-read, low-write data for maximum impact. Whatโs your caching philosophy? ๐ญ #TechTalk #Caching #Optimization"
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Distributed caching is a game-changer for scalable systems! ๐ Tools like Redis Cluster or Hazelcast can help you scale horizontally while keeping your cache consistent. Whatโs your favorite distributed caching tool? ๐งฐ #Scalability #Caching #Microservices
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Server-side caching vs. client-side caching: Know the difference! ๐ค Server-side: Reduces backend load. Client-side: Speeds up repeat visits. Combine both for the ultimate performance boost! ๏ฟฝ #WebPerformance #Caching #FrontendDev
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Database query caching can save you tons of load! ๏ฟฝ But beware: stale data can creep in if not managed properly. Use query-level TTLs or manual invalidation to keep things fresh. How do you handle DB caching? ๐ก #Database #Caching #BackendDev
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Redis vs. Memcached: Which caching solution is right for you? ๐ค Redis: Rich data structures, persistence, and scalability. Memcached: Simplicity and speed for key-value storage. Whatโs your pick and why? ๏ฟฝ #Redis #Memcached #Caching"
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Schema Evolution: Changing event structures requires backward compatibility. Debugging Complexity: Tracing issues in an asynchronous system is harder than in monolithic architectures.
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Challenges of Event Driven Services Event Ordering: Kafka guarantees ordering per partition, but cross-partition ordering needs extra handling. Idempotency: Consumers must handle duplicate events gracefully.
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