Adobe

As an experienced Software Architect excelling in the intricate landscape of concurrent projects, I orchestrate seamless execution from project inception to delivery. My proficiency lies in architecting intricate solutions, embracing cutting-edge technologies, and facilitating knowledge sharing. 

Swift context switching, impactful team mentorship, meticulous code reviews, and future-proof scoping are integral components of my approach. Whether navigating technical complexities or driving business value, I am an architect dedicated to building excellence.

Key Achievements:
•	Technical Responsible for considerable ARR through strategic tech partnerships and innovative architecture design. 
•	Recognised for operational excellence, saving  million + on cloud expenses.
•	Architected Ingestion framework that process 50+ billions events used by 1600 + users 
•	Architected AI-powered chat applications, elevating user experience and boosting engagement.
•	Developed a text-to-PPT Generative AI solution (hackathon winner), showcasing innovative problem-solving skills.
•	Spearheaded a successful cloud migration of 1000+ assets & 100+ pipelines, achieving a 30% cost reduction and 5x scalability.
•	-Passionate about leveraging ML to solve complex data challenges and drive continuous improvement.

Leadership and Empowerment:

•	Established quarterly targets, fostering a culture of continuous improvement and exceeding expectations.
•	Empowered teams through mentoring ,coaching, grooming ,earning the Team Builder Award.

Cross-Functional Expertise:

•	Led cross-functional initiatives demonstrating strong communication and delivery skills.
•	Facilitated data collection for campaign success metrics, ensuring a holistic approach and maximising impact.

Architect / Senior Computer Scientist 

Designed and architected end-to-end event-based ingestion framework utilising distributed cloud processing and cutting-edge technologies.Processes ~50 billion events and ~50 TB data daily, supporting 1000+ assets for 1600+ users.

Unified Customer Profile: Architected a comprehensive customer profile for targeted campaigns, delivering accurate and timely information throughout the journey. Optimised data flow on Azure for a holistic view.

Real-time Personalization: Designed and built a multi-threaded microservices system for real-time event processing, transforming data 

Scalable Data Management: Managed millions of daily events, developed effective storage strategies for diverse systems, and established end-to-end architecture for batch processing in Azure 

MPS: Involved in designing and building the Central System of Truth for marketing communication permissions, handling high-volume data with flexibility and scalability.

Additional Highlights:

Reduced latency in the Experience Cloud with a unified customer profile.
Developed single point of integration for data delivery to multiple customers.
Implemented configuration-based architecture for batch transformation.
Integrated gateway using IMS service for secure access and authorization.
Designed caching strategies for token management and robust monitoring.

Computer Scientist 2

Rules Engine Service : The microservice based rules services operates by streaming data from a source and processing events in real-time and  update the user profile status based on the current and previous states. The process incorporates deduplication ,applies data derivation rules to determine profile attributes, records user state changes, updates the in-memory user profile 

Roles & Responsibilities:

Contributed to the design of the rules service.
Implemented reading and writing operations from Kafka, ensuring smooth data flow.
Developed a module for manual Kafka offset management and a custom partitioner 
Implemented a module responsible for writing persisting profile attributes 
Designed caching strategies to enhance system efficiency.

Batch Egress empowers users to perform the last-mile data wrangling through SQL, enabling the export of data with multiple configurable options to the system of their choice. This functionality can be executed as a one-time action or scheduled as a batch job, ensuring flexibility and convenience. 

Roles & Responsibilities include:
- Designing end-to-end architecture
- Developing code for the auto-generation of workflows
- Creating code for automated deployment
- Designing and implementing multiple connectors, such as those for S3, SFTP, and AEP.

CAH  serves as the central repository for all  customer-related activities, encompassing both individual and team customers. It aggregates crucial data, including application usage metrics  and entitlements.

Roles & Responsibilities:

- Developed a module for reading incremental data from source and write it to destination 
- Managed the challenge of processing millions of updates on a daily basis, ensuring system scalability and performance.
- Created an Audit framework to facilitate quality checks, ensuring the reliability and accuracy of the data.

Computer Scientist

Senior Member of Technical Staff

Adobe Toastmaster club

President

Adobe Toastmasters 

Vice President Public Relations Adobe ToastMaster Club 

Impetus

Senior Software Engineer

ARICENT TECHNOLOGIES  HOLDING PRIVATE LIMITED

Opinions expressed are solely my own and do not express the views or opinions of my employer.

🚀 Welcome to Rocky Bhatia's Profile!

🎯 Results-Driven Tech Leader: With 14+ years of expertise, Rocky is a dedicated, ambitious, and results-driven technology leader.


🏢 Architect @ Adobe: In his dynamic role as an Architect at Adobe, Rocky is entrusted with spearheading the Marketing and Customer Insights domain. This pivotal position demands not only a profound understanding of cutting-edge technologies but also the ability to provide astute technical leadership across a spectrum of projects.

His leadership extends to collaborating with cross-functional teams, ensuring the seamless integration of technical solutions that not only meet but exceed the expectations of clients and stakeholders.

In addition to his architectural duties, he plays a pivotal role in mentoring and guiding the next generation of tech talents within the Adobe ecosystem

Competencies:

🌐 Distributed Architecture
☁️ Cloud Solutions
📊 Big Data Analytics
🚀 Generative AI
🏗️ System Design
🚀 Micro Services
📈 Data Platforms/Lakes
🧠 Advanced Analytics
🚀 Product Development
🌏 Leading Large Global Teams

🏆 Award-Winning Professional: Holder of 20+ professional awards, with extensive Advance courses from prestigious institutions like IIT Delhi/Bombay and the Illinois Institute of Technology, coupled with multiple professional certifications.

🌐 Global Collaboration: Collaborated globally to implement groundbreaking solutions in Digital Experience, Personalisation, Customer Engagement, Marketing Insights, Risk Management, Banking, and Telecom.

🔧 Tech Enthusiast: Passionate about data engineering, system design, architecture, cloud tech, data science, and other cutting-edge areas.

📚 Published Research: Co-authored the research paper "ML-based automation of Resume Recommendation system," presented at an international conference.

🌎 Global Reach: Recognised globally for crafting engaging technical content, Rocky boasts a monthly viewership of over ~2 million and a following in 120+ countries with 320k+ trustful followers.

🎙️ International Speaker: Sharing insights and expertise with global audiences.

🚨 PS: With 20,000+ pending connection requests due to a 30K limit, urgent matters can be directed to him via in mail.

🎙️ Speaker Invitation: Connect with him at rocky.bhatia86@gmail.com for speaking engagements or collaborations.

Technologies used by Netflix 

Netflix, with over 247.15 million subscribers, delivers a top-notch streaming experience through its meticulously crafted architecture.

Designed to be scalable, reliable, and efficient, Netflix's architecture operates on a cloud computing platform, enabling seamless resource management. Leveraging open-source technologies keeps costs in check and ensures future readiness.

Central to Netflix's architecture are microservices—small, autonomous units that scale and deploy independently. This flexibility ensures robustness and adaptability.

Netflix employs diverse caching methods to lighten server loads. A prime example is its content delivery network (CDN), caching frequently accessed content closer to users for enhanced performance and cost efficiency.

Underneath the hood, Netflix's architecture is powered by a suite of technologies:

Frontend: React, GraphQL
Backend: Spring Boot, Zuul, Eureka
Data storage: EVcache, Cassandra, CockroachDB
Messaging/streaming: Apache Kafka, Flink
Cloud computing: Amazon Web Services (AWS)

This sophisticated system evolves continuously to incorporate new features and accommodate expansion into new markets while upholding core tenets of scalability, reliability, and efficiency.

What are your thoughts on Netflix's architecture?

Rocky Bhatia

Navigating the Microservice Lifecycle: From Development to Production


In a microservice architecture, the development, deployment, and management of services are key components of ensuring the reliability, scalability, and performance of the overall system. This approach to software development emphasizes breaking down complex applications into smaller, independently deployable services, each responsible for specific business functions. However, to effectively implement a microservice architecture, a structured workflow encompassing pre-production and production stages is essential.

Pre-Production Steps:
1. Development: Developers write and test code for microservices and test them in their development environments.
2. Configuration Management: Configuration settings for microservices are adjusted and tested alongside development.
3. CI/CD Setup: Continuous Integration/Continuous Deployment pipelines are configured to automate testing, building, and deployment processes.
4. Pre-Deployment Checks: A pre-deployment step is introduced to ensure that necessary checks or tasks are completed before deploying changes to production. This may include automated tests, code quality checks, or security scans.

Production Steps:
1. Deployment: Changes are deployed to production using CI/CD pipelines.
2. Load Balancer Configuration: Load balancers are configured to distribute incoming traffic across multiple instances of microservices.
3. CDN Integration: CDN integration is set up to cache static content and improve content delivery performance.
4. API Gateway Configuration: API gateway is configured to manage and secure access to microservices.
5. Caching Setup: Caching mechanisms are implemented to store frequently accessed data and reduce latency.
6. Messaging System Configuration: Messaging systems are configured for asynchronous communication between microservices.
7. Monitoring Implementation: Monitoring tools are set up to monitor the health, performance, and behavior of microservices in real-time.
8. Object Store Integration: Integration with object stores is established to store and retrieve large volumes of unstructured data efficiently.
9. Wide Column Store or Linked Data Integration: Integration with databases optimized for storing large amounts of semi-structured or unstructured data is set up.

By following these structured steps, organizations can effectively manage the development, deployment, and maintenance of microservices, ensuring they meet quality standards, performance requirements, and business objectives, can you please add your comments if i have missed ?

🚀 Unleashing the Power of APIs: A Quick Guide for Innovators! 🌐

APIs are the secret sauce in tech, bridging apps to create something extraordinary! REST APIs? They're leading the charge with simplicity and flexibility. 🛠️✨

🔑 Key Takeaways:
 REST 101: They use simple HTTP methods (GET, POST, PUT, DELETE) and are stateless—every interaction is fresh, making them super scalable.
 Design Smart: Keep it simple, cacheable, and secure. Think about pagination for large data sets, filtering/ordering for precision, and how to make your API easy to navigate.
 Build for the Future: Versioning is crucial for smooth updates. Security isn't optional; it's essential. And remember, self-descriptive messages save the day!
 The Finer Details: Dive into Hypermedia (HATEOAS) for self-discoverable APIs, layer your system for easier maintenance, and never underestimate a uniform interface for user happiness.
 CrossDomain Mastery: CORS allows your API to be accessible from anywhere safely. Idempotency ensures consistency, and strong authentication keeps your data locked up tight.

🌟 Why It Matters: In the fast-paced world of tech, well-crafted REST APIs are the cornerstone of innovation and integration. They're not just about connecting systems; they're about building the future of digital interaction. 💡🔗

Let's create, innovate, and integrate with REST APIs leading the way to a more connected, efficient, and exciting digital landscape!  

Did i miss anything ?


𝐃𝐞𝐦𝐲𝐬𝐭𝐢𝐟𝐲𝐢𝐧𝐠 𝐂𝐈/𝐂𝐃 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬: 𝐀 𝐒𝐢𝐦𝐩𝐥𝐞 𝐆𝐮𝐢𝐝𝐞

CI/CD pipelines streamline software delivery, ensuring faster, consistent, and reliable updates. Here's how it unfolds:

1. Code Changes: Developers update the codebase with new features or fixes.
2. Code Repository: Updates are pushed to a version control system (like Git), triggering the pipeline.
3. Build: The CI server compiles the code, resolves dependencies, and prepares executable artifacts.
4. Pre-deployment Testing: Automated tests and static code analysis ensure code integrity without errors.
5. Staging Environment: Artifacts move to a staging area, mirroring the production setup for further testing.
6. Staging Tests: Specific tests in the staging environment validate production-like behaviour.
7. Approval/Gate: Sometimes, a manual check or criteria must be met before proceeding.
8. Production Deployment: With all tests passed and approvals in place, artifacts are deployed to production.
9. Post-Deployment Testing: Further tests in the live environment ensure everything runs smoothly.
10. Monitoring: Continuous monitoring tools track performance, detect issues, and analyze user behaviour.
11. Rollback: If problems arise, the system can revert to a previous version.
12. Notification: Stakeholders are kept informed about the deployment's outcome.

This process not only accelerates delivery but also reduces deployment risks by catching issues early. It embodies a commitment to quality and efficiency in the software development lifecycle.


🔍 Decoding the Digital Confusion: Encoding vs Encryption vs Hashing 🔍


Have you ever found yourself scratching your head trying to figure out the differences between encoding, encryption, and hashing? Well, you're not alone. Let me break it down for you, minus the heavy tech lingo.

Encoding: Your Data's Passport

Think of encoding like giving your data a passport to travel internationally. It's all about converting data into a format that can be easily shared across different systems without confusion. Whether it's Base64, ASCII, or Unicode, encoding ensures that your message arrives intact, no matter where it's headed. Remember, encoding isn't about keeping secrets; it's about making sure your data can be understood anywhere and by anyone it's meant for.

Encryption: The Secret Agent

Now, if encoding is your data's passport, encryption is its secret agent disguise. When you encrypt data, you're scrambling it into a code that only someone with the right key can crack. It's the ultimate protection for your sensitive information, ensuring that only the intended recipient can see your message in its true form. Whether you're sending credit card info, private messages, or sensitive documents, encryption keeps your secrets safe from prying eyes.

Hashing: The One-Way Mirror

Hashing is a bit like a one-way mirror. It transforms your data into a fixed-size string or a "fingerprint," but here's the kicker: you can't reverse the process. It's fantastic for checking if data has been tampered with or keeping passwords secure. If the data changes even a little bit, the hash will be completely different. It's a one-way trip – once your data is hashed, there's no going back.

 Why This Matters to You
Grasping these concepts is key in our digital age, especially if you're dabbling in digital communications, cybersecurity, or just want to keep your online presence safe. Each of these processes has its role, whether it's ensuring your data can travel safely, keeping your information private, or verifying that what you're seeing hasn't been messed with.

Let's all be a bit more digital-savvy and protect our digital footprints. Stay curious and stay secure, folks!


𝐇𝐨𝐰 𝐝𝐨𝐞𝐬 𝐚𝐧 𝐀𝐏𝐈 𝐰𝐨𝐫𝐤?

An API, or Application Programming Interface, acts as a bridge between software applications, enabling them to communicate and share data seamlessly. Here's a quick breakdown of how APIs work:

1. Request: One software component sends a request to another component, often referred to as the client and server, respectively.

2. Communication Protocol: APIs follow predefined rules and conventions for communication, such as HTTP or HTTPS.

3. API Endpoint: The server provides specific URLs, known as endpoints, for accessing its services or data.

4. Request Parameters: Clients can send additional information along with their requests, like query parameters or request headers.

5. Processing: The server executes the requested operation, like fetching data from a database.

6. Response: After processing, the server sends back a response containing the requested data and an HTTP status code.

7. Data Format: Data exchanged between client and server is typically in standardized formats like JSON or XML.

8. Authentication and Authorization: APIs often require authentication to ensure security, using methods like API keys or tokens.

APIs play a crucial role in modern software development, facilitating communication and integration between various applications and services. From accessing external services to enhancing internal systems, APIs drive efficiency and collaboration in today's tech landscape.

𝐀 𝐌𝐢𝐧𝐝𝐌𝐚𝐩 𝐭𝐨 𝐑𝐞𝐟𝐞𝐫 𝐟𝐨𝐫 𝐃𝐚𝐭𝐚 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭

In today's data-driven landscape, effective data management is essential for business success. From ensuring accurate insights to protecting sensitive information, every aspect of data management is crucial.

Let's explore the key components of a strong data management strategy:

1. Data Quality: Quality is paramount. High-quality data is the bedrock of meaningful analysis and innovation. Regular data profiling, cleansing, and validation are vital to maintain accuracy and reliability.

2. Data Security: In an age of data breaches, security is critical. Encryption, access controls, and strict protocols ensure only authorized personnel access sensitive data, preserving customer trust and regulatory compliance.

3. Master Data Management (MDM): MDM offers a unified view of master data, like customer or product information, eliminating redundancy and ensuring consistency across the organization.

4. Testing Data: Just like software, data needs rigorous testing. Organizations must ensure data accuracy and reliability before making decisions, preventing flawed insights.

5. Data Governance: Governance establishes rules and processes for data usage, defining ownership, responsibilities, and guidelines for handling data.

6. Data Architecture: A well-designed architecture supports efficient data management, akin to a solid foundation for a building.

7. Metadata Management: Metadata provides context to data, ensuring users understand its source and meaning.

8. Data Reporting: Data becomes valuable when transformed into actionable insights. Reporting tools visualize data, enabling stakeholders to make informed decisions swiftly.

Data management is an ongoing journey. As data volumes and complexity increase, an adaptable strategy becomes essential. Stay vigilant, iterate, and continuously improve practices to thrive in the data-driven era.

Credit: Diagram recreated from Henrik Liliendahl's original.


Exploring API Architecture Styles: An In-Depth Guide


Rocky Bhatia on LinkedIn • 4 min read

Exploring API Architecture Styles: An In-Depth Guide

I just got my hands on the latest Gen AI global survey & research report from ClearML called “The State of AI Infrastructure at Scale 2024: Unveiling Future Landscapes, Key Insights, and Business Benchmarks.”


This enormous survey of 1,000 global AI, ML and GenAI leaders, conducted with FuriosaAI and AI Infrastructure Alliance, focuses on the myriad challenges organizations face in managing and scaling their current AI workloads.

The survey found that 40% of respondents, regardless of company size, are planning to use orchestration and scheduling technology to maximize their existing compute infrastructure. 

When asked about peak periods for GPU usage, 15% of respondents report that less than 50% of their available and purchased GPUs are in use. 53% believe 51-70% of GPU resources are utilized, and just 25% believe their GPU utilization reaches 85%. Only 7% of companies believe their GPU infrastructure achieves more than 85% utilization during peak periods.

Find out more by downloading the report here:

https://lnkd.in/gmTDMMDT



#ai #aiinfrastructure #gpu #gpus #gpucomputing #aicompute #machinelearning #llm #llms #llmops #mlops #orchestration #genai #gai #generativeai

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