When planning a lift and shift migration of legacy applications to Azure IaaS, what are the best practices for optimizing cost and performance immediately after migration, and how do they differ from strategies used in a cloud native PaaS deployment?

When planning a lift-and-shift migration of legacy applications to Azure IaaS, here are some best practices for optimizing cost and performance immediately after migration:

Best Practices for Cost Optimization:

1. Reserved Instances: Consider purchasing reserved instances for your virtual machines (VMs) to save costs compared to pay-as-you-go pricing. This is especially beneficial if you have predictable workloads.
2. Right-Sizing: Analyze the resource utilization of your VMs post-migration and adjust their sizes accordingly. This ensures that you are not over-provisioning resources, which can lead to unnecessary costs.
3. Auto-Scaling: Implement auto-scaling for your applications to automatically adjust the number of VMs based on demand. This helps in managing costs effectively by scaling down during low usage periods.

Best Practices for Performance Optimization:

1. Storage Tiers: Utilize different storage tiers based on the access frequency of your data. For example, use premium storage for high-performance needs and standard storage for less critical data.
2. Networking: Optimize your network settings by using Azure Virtual Network (VNet) for secure and efficient communication between your resources. Consider using Azure ExpressRoute for high-throughput and low-latency connections if necessary.
3. Monitoring and Diagnostics: Use Azure Monitor and Azure Log Analytics to track performance metrics and diagnose issues. This will help you identify bottlenecks and optimize resource allocation.

Differences in Strategies for PaaS Deployment:

• In a cloud-native PaaS deployment, the focus shifts from managing the underlying infrastructure to leveraging platform features. PaaS solutions often include built-in scaling, load balancing, and automated backups, which reduce the need for manual intervention in cost and performance management.
• PaaS also allows for more granular resource management and optimization, as applications can be designed to take full advantage of cloud-native features like microservices architecture, which can lead to better resource utilization and cost efficiency over time.

In summary, while lift-and-shift to Azure IaaS requires careful planning and management of resources to optimize costs and performance, a cloud-native PaaS approach inherently provides tools and features that simplify these processes and enhance application performance.