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Managing the financial heartbeat of a global tech giant involves processing millions of complex transactions across diverse product lines ranging from gaming to cloud services. When Microsoft decided to modernize its core financial infrastructure, it faced the monumental task of
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Managing the financial heartbeat of a global tech giant involves processing millions of complex transactions across diverse product lines ranging from gaming to cloud services. When Microsoft decided to modernize its core financial infrastructure, it faced the monumental task of
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The structural foundation of cloud computing that relied on short-lived, disposable containers is being dismantled by a new generation of autonomous agents that require long-term memory and persistent execution environments. For more than a decade, the architectural blueprint for modern
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Dominic Jainy has spent years translating frontier technologies into practical wins for large enterprises. He’s worked at the messy intersection of AI, machine learning, and blockchain, where governance and scale often make or break ambitious programs. Today he talks through
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Dominic Jainy has spent years at the crossroads of AI, cloud security, and data platforms, helping teams translate complex architectures into resilient, testable recovery plans. In this conversation, we explore how to protect BigQuery, Compute Engine, GKE, Cloud SQL, and
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Dominic Jainy has spent years translating frontier technologies into practical wins for large enterprises. He’s worked at the messy intersection of AI, machine learning, and blockchain, where governance and scale often make or break ambitious programs. Today he talks through
- Cloud
Data cannot roam freely when laws, risk, and mission continuity demand hard boundaries, yet organizations still expect cloud speed, elastic scale, and modern AI—a contradiction Azure Local Sovereign Cloud attempts to resolve without diluting control. Defining Azure Local Sovereign Cloud
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The rapid adoption of artificial intelligence frameworks has unintentionally created a fertile ground for sophisticated cyberattacks targeting the very gateways designed to manage sensitive model interactions. As organizations rush to integrate large language models into their operational workflows, security protocols
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Boardrooms kept hearing the same uncomfortable refrain: mission‑critical IBM i applications were stable and irreplaceable, yet digital initiatives demanded cloud speed, customer‑grade experiences, and continuous delivery pipelines that old playbooks could not easily support, creating a high‑stakes gap between reliability
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Introduction Boards now ask one blunt question when AI pipelines span clouds: can backups stay untouchable and recover at hyperscale? That challenge sits at the crossroads of resilience, compliance, and speed, and it grows sharper as data lands in object
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Dominic Jainy has spent years at the crossroads of AI, cloud security, and data platforms, helping teams translate complex architectures into resilient, testable recovery plans. In this conversation, we explore how to protect BigQuery, Compute Engine, GKE, Cloud SQL, and
Browse Different Divisions
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