Skill your team to increase performance efficiency of Azure and AI projects

The cost and performance benefits of moving your workload to the cloud are clear — reduced latency, improved elasticity, and great agility of resources — but it’s also critical to learn to manage ongoing performance efficiency beyond initial migrating to see optimal results. Best practices in performance efficiency go beyond designing your workloads so you only pay for what you need; it’s building the best of cloud computing into every design choice. Ideally, a workload should meet performance targets without overprovisioning, which makes the resources, skilling and how-to guidance offered by Azure Essentials crucial considerations for any team looking to scale efficiently.

Built to provide help at your point of need, the resources available in Azure Essentials have helped clients complete their app migrations 30% faster (an average of 2.7 weeks) from normal, according to a November 2024 research study by IDC. They also experienced 73% fewer unplanned outages, leading to a 94% decrease in associated revenue losses.

In this blog, we’ll review how Azure Essentials skilling, tools and frameworks can help your team build resilient, efficient workloads, and introduce self-paced training on Microsoft Learn to help you Elevate reliability, security, and ongoing performance of Azure and AI projects.

Maximize Azure efficiency with free tools and expert guidance

Achieving basic operational status is challenging enough— scaling introduces additional complexity that can compromise user experience and exasperate latency issues. Teams tap into free training and comprehensive guidance to improve workload performance efficiency by optimizing migration speed, operational effectiveness, and system resiliency. Azure Essentials provides all these resources in one place to accelerate efficiency and monitor workloads to optimize ongoing performance. 

Tools like Azure Monitor and Azure Advisor that provide continuous monitoring with real-time insights and automated recommendations, while automated testing and remediation using Azure Automation and Azure Functions proactively address performance bottlenecks. These tools collect telemetry data from workloads and their supporting resources to give architectural recommendations and performance metrics that are aligned to the guidance routed in best practices.

Learn to apply efficiency principles to achieve and sustain performance

Learning to monitor performance efficiency and applying them at each stage of your workload’s lifecycle are equally important. Recognizing this challenge, our Plan on Microsoft Learn titled Elevate reliability, security, and ongoing performance of Azure and AI projects offers curated skilling to help your team improve reliability, security, and performance in your Azure projects, and explore best practices for deploying Azure landing zones and designing optimized workloads. After completing the Plan, you should be able to:

• Use Azure Well-Architected Framework to build effective solutions that balance performance efficiency, security, reliability, cost optimization, and operational excellence and learn about the model of shared responsibility with your cloud provider.
• Make effective decisions about how to implement FinOps, use available Microsoft resources and solutions for FinOps, and conduct a FinOps iteration.
• Utilize Azure savings plans to save your organization money on compute.
• Purchase and use the right reserved instance for your cloud needs and perform basic reporting on your cloud needs.

Maximize workload efficiency with Azure Well-Architected Framework

In the skilling modules shared here, developers learn to maximize workload performance efficiency through a comprehensive approach in the Azure Well-Architected Framework. It emphasizes scalability planning and resource optimization, enabling applications to handle increased demands while maintaining cost effectiveness.

Rather than treating performance as an afterthought, the framework integrates it into the early design process, allowing developers to build optimization directly into their applications. This approach balances performance with other critical factors like cost, reliability, and security to create well-rounded solutions that meet business needs.

The framework views performance efficiency as an ongoing journey, providing tools like Azure Advisor and Well-Architected Review for continuous assessment and improvement. By establishing clear performance targets based on business requirements and promoting regular testing and monitoring, it ensures applications maintain their efficiency as they evolve. This systematic approach helps your team create and maintain high-performing workloads that adapt to changing business demands while optimizing resource usage.

Scale your workloads with a design checklist and assessment

In addition to the curated lessons in our Plan on Microsoft Learn, we also created an Azure Quickstart guide with additional learning resources to help you build a comprehensive strategy for performance efficiency, including:

> Performance efficiency design principles

Get crucial insight on establishing realistic performance targets and designing for capacity requirements to ensure sustained performance. This document explores optimization strategies, including dedicated cycles for performance enhancement and the utilization of monitoring tools for trend analysis. You’ll also learn the importance of technology adoption in driving performance improvements and the mitigation of adverse effects from updates, enabling you to construct resilient and high-performing cloud solutions.

> Design review checklist for performance efficiency

This checklist helps you scale your system to meet growing workload demands while maintaining efficient performance. When designing for performance, consider how cost, complexity, new requirements, technical debt, reporting, and operational work affect your system's efficiency.

> Performance efficiency tradeoffs

When setting performance targets and designing for efficiency, it’s important to consider how your decisions affect other architectural pillars. Performance optimizations may enhance some aspects while requiring tradeoffs in others. This article lists example tradeoffs you might encounter when designing for performance efficiency, including:

• Reliability: Optimizing for performance efficiency can compromise reliability by reducing redundancy and increasing complexity.
• Security: Security controls may be weakened by performance optimizations that reduce security measures, expand the attack surface, or decrease segmentation.
• Cost optimization: Cost saving measures like avoiding overprovisioning, managing the cost of added components, and ensuring investments align with functional requirements can limit efficiency.
• Operational excellence: Performance optimizations can reduce observability, increase operational complexity, and create culture stress.

Azure Well-Architected Review assessment

This Microsoft Assessment helps you examine the performance efficiency of your workloads through the lens of the Azure Well-Architected Review Framework. The self-guided assessment takes about an hour to complete, after which you will receive pragmatic recommendations based on your specific needs.

Ensure a positive user experience while optimizing resources

Performance efficiency is crucial when developing workloads as it directly impacts user experience and operational costs. You’ll find all of the Azure Essentials resources you need to get started in the Azure Essentials resource kit.

Ready to get started? Begin the Plan on Microsoft Learn to Elevate reliability, security, and ongoing performance of Azure and AI projects, and ensure your applications scale effectively while maintaining responsiveness and optimizing resource utilization.