Episode #52 of the Data Center Go-to-Market Podcast features an interview with Dr. Priyanka Ray, Global GTM Cloud Migration & Modernisation Lead at IBM.
- Explore Priyanka Ray's career journey from software engineering to cloud consulting
- Discover Priyanka's advice for early career professionals in the data center and cloud industries
- Understand the importance of continuous learning and obtaining industry certification
- Identify the gaps between formal education and industry requirements, and strategies to bridge them
- Learn how mid-career professionals can leverage their experience and upskill for emerging technologies
- Evaluate criteria for selecting the right training and certification programs
- Recognize the common business-related challenges in cloud migration and modernization projects
- Gain insights into the typical scope and duration of cloud migration engagements
- Anticipate future trends in data centers, including the shift towards hybrid/multi-cloud and edge computing
- Survey essential tools and technologies used by GTM leads in cloud migration and modernization
Host:
Joshua Feinberg, CEO
DCSMI
Special Guest:
Dr. Priyanka Ray, Global GTM Cloud Migration & Modernisation Lead
IBM
Dr. Priyanka Ray, Global GTM Cloud Migration and Modernization Lead at IBM, discussed her career journey from software engineering to cloud and data center management. She emphasized the importance of continuous learning and certifications in cloud architecture, AI, and edge computing. Key challenges in cloud migrations include underestimating complexity, misalignment with business goals, and change management. A typical mid-size migration project involves 1,000 VMs, takes 4-5 months, and requires 8-10 resources. Future trends include hybrid and multi-cloud solutions, edge computing, sustainability, and AI-driven automation. Essential tools for GTM leads include IBM's AI Watson X tools and third-party solutions like Turbonomic and Appsian.
Outline
Career Path and Early Days in IT
- Priyanka Ray discusses her career journey, starting as a software engineer with languages like COBOL, C, and C++.
- She transitioned to virtualization and cloud computing, moving from traditional software development to cloud software development.
- Priyanka highlights her experience with various cloud platforms, including AWS, Azure, and Google Cloud.
- She emphasizes the importance of continuous learning and staying updated with industry innovations like AI and edge computing.
Advice for Early Career Professionals
- Priyanka advises early career professionals to embrace continuous learning and adaptability, especially in the rapidly evolving cloud and data center landscape.
- She stresses the importance of understanding cloud architecture fundamentals, regardless of whether one chooses a technical or non-technical career path.
- Priyanka recommends gaining certifications from major cloud providers like AWS, Azure, and Google Cloud to stay ahead in the industry.
- She highlights the need for professionals to understand the basic functions of a data center, including operations, cybersecurity, and network engineering.
Challenges in Formal Education and Industry Gap
- Joshua Feinberg and Priyanka discuss the gap between formal education and industry requirements, particularly in cloud and data center fields.
- Priyanka mentions that universities provide theoretical knowledge but lack practical application, which is crucial for industry relevance.
- IBM and other companies are bridging this gap through programs that educate students and recent graduates on industry-specific skills.
- Priyanka advises students to be proactive, seek mentorship, and pursue external certifications to complement their formal education.
Mid-Career Advice and Skill Development
- Priyanka advises mid-career professionals to leverage their experience and marry it with new technologies like AI, edge computing, and sustainability.
- She emphasizes the importance of continuous learning and staying relevant by obtaining certifications in high-growth areas like multi-cloud architecture and AI-driven data center management.
- Priyanka suggests that experienced professionals can pivot into strategic leadership roles, aligning cloud and data center strategies with business objectives.
- She highlights emerging trends like AI-driven automation, edge computing, and sustainability as areas for career growth and development.
Selecting the Right Training and Certifications
- Priyanka explains that the choice of training and certification programs depends on one's current career path and future goals.
- She provides examples of relevant certifications for different career paths, such as AWS certifications for cloud architecture and security.
- Priyanka advises mid-career professionals to focus on basic cloud certifications from major providers like AWS, Azure, and Google Cloud.
- She emphasizes the importance of aligning training with one's career goals and staying updated with industry trends.
Common Challenges in Cloud Migration Projects
- Priyanka identifies several challenges in cloud migration projects, including underestimating complexity, misalignment with business goals, and inadequate change management.
- She highlights the importance of aligning IT strategies with business objectives to deliver tangible business value.
- Priyanka discusses the risks of single vendor or technology lock-in and the need for multi-vendor, multi-technology environments.
- She emphasizes the importance of engaging key stakeholders and maintaining communication to ensure project success.
Typical Project Scope and Duration
- Priyanka provides an overview of a typical cloud migration project, focusing on a mid-size project involving 1000 VMs.
- She explains that such projects can take four to five months, involving eight to ten resources and automated tools.
- The duration and scope of the project depend on the complexity of the environment and the client's timeline.
- Priyanka mentions that IBM's fully automated approach helps manage the project efficiently.
Future Trends and Role Evolution
- Priyanka predicts that future data centers will focus on hybrid and multi-cloud solutions, edge computing, and sustainability.
- She emphasizes the importance of interoperability, security management, and AI-enhanced offerings in GTM strategies.
- Priyanka highlights the growing role of AI and machine learning in automating data center operations and improving efficiency.
- She discusses the trend of moving from traditional data centers to service-oriented models, emphasizing flexibility and consumption-based pricing.
Indispensable Tools for GTM Leads
- Priyanka lists essential tools for managing migration and modernization projects, including IBM consulting accelerators and AI Watson X tools.
- She mentions third-party tools like Cast AI and Turbonomic, which are crucial for workload management and performance monitoring.
- Priyanka highlights the importance of finops tools like Appsian for managing infrastructure and workload optimization.
- She emphasizes the need for continuous learning and staying updated with the latest tools and technologies.
Suggestions for Future Interview Guests
- Priyanka suggests interviewing data center clients to understand their challenges and future expectations from partners.
- She recommends interviewing innovation leaders, such as CTOs and R&D heads, to understand their strategies and industry trends.
- Priyanka also suggests interviewing industry analysts to gain insights into future expectations and industry directions.
- She emphasizes the importance of real-time scenarios and client perspectives in understanding the industry's challenges and opportunities.
Guest Resources
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