«Don’t go over to the cloud without truly understanding what you are getting into.»

Unlock the secrets of cloud migration with industry expert Jonah Andersson, a senior Azure consultant and Microsoft MVP from Sweden. Learn how to seamlessly transition your data systems to the cloud. Jonah shares her knowledge on cloud infrastructure, AI integration, and the balance between Edge AI and Cloud AI, providing a comprehensive guide to building resilient cloud systems.

Explore the intersection of IT consulting, Data Governance, and AI in cloud computing, with a specific focus on security and agile workflows. Understand the critical impact of GDPR on data management and the essential collaboration between IT consultants and data governance experts. Jonah and I delve into the growing trend of edge AI, driven by security and latency concerns, and discuss responsible AI usage, emphasizing security and privacy. Learn how to navigate the complexities of multi-cloud strategies and manage technical debt effectively within your organization.

Jonah offers tips on avoiding common migration mistakes and highlights the significance of using tools like Azure's Cloud Adoption Framework. Whether you're modernizing outdated systems, merging companies, or transitioning to a new cloud provider, this episode equips you with the essential knowledge and resources to ensure a successful and strategic cloud migration journey. Join us for a deep dive into the future of cloud computing with an industry leader.

Here are my key takeaways:

• Azure services can be tailored to use cases and service needs. But you need to understand your requirements and needs.
• Once you understand what you need to do, you need to gain perspective in the how - what methods and processes are supported?
• Think security at every step.
• Security with integrations is an important part, we need to focus more on.
• Bringing different competencies together is a vital ingredient in building resilient applications.
• Cloud is about where your data resides, how you protect it and how you handle big data.
• Cloud should support the entire data lifecycle.

Cloud and AI

• «Cloud computing is the backbone of AI.»
• AI pushed for Edge AI, in addition to cloud. Reasons for Edge AI are latency, but mainly security.
• Cloud can provide an attack surface for eg. data poisoning, lack of control for training data, etc.
• AI tools can pose concerns on what and how you are exposing data.
• Awareness and education are important, when building something with AI.
• You need to at least understand your input to track your output - explainability starts with understanding of your data sources.
• There is a risk to Model Governance by on-perm due to the level of competancy needed.

Multi-Cloud vs. Single Cloud

• This is one of the questions to consider at the beginning of a cloud migration.
• Drivers for multi cloud strategy are:
   
  • Avoiding proprietary vendor lock-in,
  • Existing applications or infrastructure in another platform,
  • Choosing according to the quality of services offered by cloud vendors.
• If you choose multi cloud for automated resource management, you need to consider support platforms.

Cloud Migration

• Reason for cloud migration boil often down to gaining resiliency in the cloud, due to redundancy.
• You need to uphold Data Quality not just after the migration but also during the transit.
• Cloud migration requires strategy.
• There are great resources to help with your cloud migration, like the Cloud Adaption framework or the Well-Architected framework.
• Use observability and orchestration tools for your migration process.
• Ensure you understand your cost, and can optimize it to fit with your needs.