Define a process to improve workload performance

Defining a process to evaluate and incorporate new services and configurations is crucial for maintaining optimal performance in cloud workloads. By regularly assessing emerging standards, architectures, and technologies, teams can enhance their workload efficiency and adapt swiftly to changing demands.

Best Practices

Implement a Performance Evaluation Framework

• Regularly assess your workload performance using automated monitoring tools to capture metrics such as latency and throughput.
• Create benchmarks based on your most critical use cases to evaluate the performance impact of proposed changes in services or configurations.
• Incorporate performance testing into your CI/CD pipeline to ensure that every code change is evaluated for its effect on performance.
• Document the outcomes of performance evaluations to track improvements and make data-driven decisions moving forward.

Stay Updated with New AWS Services

• Maintain a schedule to review AWS announcements and new service features that may enhance performance.
• Engage with AWS blogs, whitepapers, and webinars to learn about the latest performance optimizations and best practices.
• Allocate time in your development cycle to experiment with newly released instance types and services, assessing their impact on existing workloads.

Use Cost and Performance Optimization Tools

• Leverage AWS Trusted Advisor and AWS Cost Explorer to identify underutilized resources that could impact performance negatively.
• Utilize tools such as AWS Compute Optimizer to receive recommendations on optimal resource types based on your usage patterns.
• Evaluate other third-party tools that specialize in workload performance analysis and benchmarking to gain deeper insights.

Conduct Regular Performance Reviews

• Establish a routine for conducting performance reviews that includes cross-functional teams to gather diverse insights.
• Create a performance review checklist that includes key performance indicators (KPIs) relevant to your application’s goals (e.g., response time, resource utilization).
• Use insights from performance reviews to prioritize future development efforts and refine architectural decisions.

Questions to ask your team

• What criteria do you use to evaluate new AWS services and features for your workload?
• How often do you review and update your performance benchmarks to align with new instance offerings?
• Do you have a standardized process for testing workload performance when using new configurations?
• How do you document the results from performance tests on different instance types?
• What role does automated performance monitoring play in your workload efficiency evaluations?
• Are there specific design patterns you have implemented to optimize performance?
• How do you share performance efficiency findings within your team?

Who should be doing this?

Cloud Architect

• Evaluate new AWS services and offerings for performance enhancements.
• Design and implement performance testing frameworks.
• Analyze performance test results and make recommendations for workload adjustments.

DevOps Engineer

• Automate deployment of performance testing environments.
• Monitor workloads for performance metrics and anomalies.
• Collaborate with the Cloud Architect to implement findings from performance evaluations.

Product Manager

• Align performance efficiency improvements with business goals and user needs.
• Prioritize performance-related enhancements in the product backlog.
• Coordinate feedback from stakeholders on performance-related issues.

Data Analyst

• Collect and analyze data from performance tests to identify trends and areas for improvement.
• Provide insights and recommendations based on performance data analysis.
• Support the team in creating dashboards to visualize performance metrics.

What evidence shows this is happening in your organization?

• Performance Evaluation Template: A structured template for documenting performance tests, configurations, and results whenever new services or instance types are evaluated. Includes sections for benchmarking, expected outcomes, and recommendations.
• Performance Improvement Policy: A formal policy outlining the organization’s commitment to continuously evaluate and adopt new technologies to enhance workload performance, including guidelines for conducting performance tests and approving configurations.
• Performance Evaluation Dashboard: An interactive dashboard that visualizes workload performance metrics over time, including comparative analysis of old versus new instance types and configurations, helping stakeholders make informed decisions.
• Workload Performance Improvement Plan: A strategic plan that details the processes and timelines for assessing new services and configurations, including steps for conducting tests and integrating results into workload management workflows.
• Performance Monitoring Checklist: A checklist for regular monitoring and evaluation of workload performance, ensuring that new services and configurations are assessed systematically and efficiently.

Cloud Services

AWS

• Amazon CloudWatch: Provides monitoring and observability of your AWS resources and applications, helping you analyze performance metrics.
• AWS Trusted Advisor: Offers real-time guidance to help you provision your resources following AWS best practices, including performance-related recommendations.
• AWS Cost Explorer: Allows you to visualize, understand, and manage your AWS costs and usage over time, identifying areas where performance and costs can be optimized.
• AWS Auto Scaling: Helps ensure that the right number of Amazon EC2 instances are running to handle demand, optimizing performance while managing costs.

Azure

• Azure Monitor: Collects and analyzes performance metrics and logs from applications, providing insight into their performance and efficiency.
• Azure Advisor: Delivers personalized best practices recommendations, including performance optimization suggestions for your Azure resources.
• Azure Cost Management + Billing: Helps you monitor and manage your cloud spending and usage patterns to ensure efficient resource utilization.
• Azure Autoscale: Automatically adjusts resources to match demand, ensuring optimal performance and cost-efficiency.

Google Cloud Platform

• Google Cloud Monitoring: Provides observability to applications and services running on GCP, helping analyze performance metrics to improve efficiency.
• Google Cloud Asset Inventory: Allows you to discover, manage, and analyze all your cloud resources, making it easier to optimize performance.
• Google Cloud Billing Reports: Helps you analyze your spending on GCP services and identify inefficiencies to improve resource costs and performance.
• Google Cloud Autoscaler: Automatically manages instance groups to optimize performance and reduce costs based on load.

Question: What process do you use to support more performance efficiency for your workload?
Pillar: Performance Efficiency (Code: PERF)