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Operational Excellence
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- Resources have identified owners
- Processes and procedures have identified owners
- Operations activities have identified owners responsible for their performance
- Team members know what they are responsible for
- Mechanisms exist to identify responsibility and ownership
- Mechanisms exist to request additions, changes, and exceptions
- Responsibilities between teams are predefined or negotiated
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- Executive Sponsorship
- Team members are empowered to take action when outcomes are at risk
- Escalation is encouraged
- Communications are timely, clear, and actionable
- Experimentation is encouraged
- Team members are encouraged to maintain and grow their skill sets
- Resource teams appropriately
- Diverse opinions are encouraged and sought within and across teams
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- Use version control
- Test and validate changes
- Use configuration management systems
- Use build and deployment management systems
- Perform patch management
- Implement practices to improve code quality
- Share design standards
- Use multiple environments
- Make frequent, small, reversible changes
- Fully automate integration and deployment
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- Have a process for continuous improvement
- Perform post-incident analysis
- Implement feedback loops
- Perform knowledge management
- Define drivers for improvement
- Validate insights
- Perform operations metrics reviews
- Document and share lessons learned
- Allocate time to make improvements
- Perform post-incident analysis
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Security
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- Separate workloads using accounts
- Secure account root user and properties
- Identify and validate control objectives
- Keep up-to-date with security recommendations
- Keep up-to-date with security threats
- Identify and prioritize risks using a threat model
- Automate testing and validation of security controls in pipelines
- Evaluate and implement new security services and features regularly
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- Define access requirements
- Grant least privilege access
- Define permission guardrails for your organization
- Manage access based on life cycle
- Establish emergency access process
- Share resources securely within your organization
- Reduce permissions continuously
- Share resources securely with a third party
- Analyze public and cross-account access
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- Perform regular penetration testing
- Deploy software programmatically
- Regularly assess security properties of the pipelines
- Train for Application Security
- Automate testing throughout the development and release lifecycle
- Manual Code Reviews
- Centralize services for packages and dependencies
- Build a program that embeds security ownership in workload teams
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Reliability
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- Be aware of service quotas and constraints in Cloud Services
- Manage service quotas across accounts and Regions
- Accommodate fixed service quotas and constraints through architecture
- Monitor and manage quotas
- Automate quota management
- Ensure sufficient gap between quotas and usage to accommodate failover
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- Use highly available network connectivity for your workload public endpoints
- Provision Redundant Connectivity Between Private Networks in the Cloud and On-Premises Environments
- Ensure IP subnet allocation accounts for expansion and availability
- Prefer hub-and-spoke topologies over many-to-many mesh
- Enforce non-overlapping private IP address ranges in all private address spaces where they are connected
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- Monitor end-to-end tracing of requests through your system
- Conduct reviews regularly
- Analytics
- Automate responses (Real-time processing and alarming)
- Send notifications (Real-time processing and alarming)
- Define and calculate metrics (Aggregation)
- Monitor End-to-End Tracing of Requests Through Your System
- Define and calculate metrics
- Send notifications
- Automate responses
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- Monitor all components of the workload to detect failures
- Fail over to healthy resources
- Automate healing on all layers
- Rely on the data plane and not the control plane during recovery
- Use static stability to prevent bimodal behavior
- Send notifications when events impact availability
- Architect your product to meet availability targets and uptime service level agreements (SLAs)
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Cost Optimization
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- Establish ownership of cost optimization
- Establish a partnership between finance and technology
- Establish cloud budgets and forecasts
- Implement cost awareness in your organizational processes
- Monitor cost proactively
- Keep up-to-date with new service releases
- Quantify business value from cost optimization
- Report and notify on cost optimization
- Create a cost-aware culture
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- Perform cost analysis for different usage over time
- Analyze all components of this workload
- Perform a thorough analysis of each component
- Select components of this workload to optimize cost in line with organization priorities
- Perform cost analysis for different usage over time
- Select software with cost effective licensing
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Performance
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- Learn about and understand available cloud services and features
- Evaluate how trade-offs impact customers and architecture efficiency
- Use guidance from your cloud provider or an appropriate partner to learn about architecture patterns and best practices
- Factor cost into architectural decisions
- Use policies and reference architectures
- Use benchmarking to drive architectural decisions
- Use a data-driven approach for architectural choices
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- Use purpose-built data store that best support your data access and storage requirements
- Collect and record data store performance metrics
- Evaluate available configuration options for data store
- Implement Strategies to Improve Query Performance in Data Store
- Implement data access patterns that utilize caching
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- Understand how networking impacts performance
- Evaluate available networking features
- Choose appropriate dedicated connectivity or VPN for your workload
- Use load balancing to distribute traffic across multiple resources
- Choose network protocols to improve performance
- Choose your workload's location based on network requirements
- Optimize network configuration based on metrics
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- Establish key performance indicators (KPIs) to measure workload health and performance
- Use monitoring solutions to understand the areas where performance is most critical
- Define a process to improve workload performance
- Review metrics at regular intervals
- Load test your workload
- Use automation to proactively remediate performance-related issues
- Keep your workload and services up-to-date
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Sustainability
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- Scale workload infrastructure dynamically
- Align SLAs with sustainability goals
- Optimize geographic placement of workloads based on their networking requirements
- Stop the creation and maintenance of unused assets
- Optimize team member resources for activities performed
- Implement buffering or throttling to flatten the demand curve
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- Optimize software and architecture for asynchronous and scheduled jobs
- Remove or refactor workload components with low or no use
- Optimize areas of code that consume the most time or resources
- Optimize impact on devices and equipment
- Use software patterns and architectures that best support data access and storage patterns
- Remove unneeded or redundant data
- Use technologies that support data access and storage patterns
- Use policies to manage the lifecycle of your datasets
- Use shared file systems or storage to access common data
- Back up data only when difficult to recreate
- Use elasticity and automation to expand block storage or file system
- Minimize data movement across networks
- Implement a data classification policy
- Remove unneeded or redundant data
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- Articles coming soon
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Collect compute-related metrics
PostedDecember 20, 2024
UpdatedMarch 21, 2025
ByKevin McCaffrey
Understanding and optimizing your compute resources is crucial to achieving better performance efficiency in your workload. By collecting and analyzing compute-related metrics, organizations can make informed decisions about their compute choices and adapt them to meet the specific demands of their applications.
Best Practices
Monitor Resource Utilization
Set Up Alerts for Anomalies
Perform Regular Reviews
Questions to ask your team
- What specific metrics are you collecting regarding compute resource utilization?
- How frequently are these metrics being recorded and analyzed?
- Do you have alerts set up for any performance thresholds based on the collected metrics?
- Are you using these metrics to make decisions on scaling or adjusting compute resources?
- How do you correlate workload performance with the metrics gathered from your compute resources?
- Have you identified any trends from the metrics that indicate underutilization or overutilization of your compute resources?
- Are these metrics integrated with your monitoring and reporting tools?
Who should be doing this?
Cloud Architect
- Design and implement architecture using appropriate compute resources.
- Evaluate and select compute instances based on workload requirements.
- Ensure different components utilize the optimal compute resources for enhanced performance.
DevOps Engineer
- Monitor and collect compute-related metrics for various services.
- Analyze performance data to identify areas for optimization.
- Implement configurations based on metric insights to improve resource utilization.
Systems Administrator
- Maintain and manage compute resource configurations.
- Assist in the collection and tracking of system performance metrics.
- Ensure the reliability and availability of computational resources.
Data Analyst
- Interpret compute-related metrics to assess performance efficiency.
- Generate reports on compute resource usage and performance trends.
- Provide insights based on data analysis to inform resource selection decisions.
What evidence shows this is happening in your organization?
- Compute Resource Performance Metrics Dashboard: An interactive dashboard that visualizes compute-related metrics such as CPU utilization, memory usage, and I/O performance, allowing teams to monitor and optimize resource allocation in real-time.
- Compute Metrics Collection Checklist: A checklist for teams to follow when setting up metrics collection for compute resources, ensuring that all relevant performance indicators are tracked effectively.
- Performance Monitoring Policy: A formal policy document that outlines the standards and procedures for monitoring compute resource performance, including frequency of reviews and reporting structures.
- Compute Performance Optimization Playbook: A comprehensive guide that provides strategies and best practices for optimizing the performance of compute resources based on collected metrics.
- Resource Utilization Report Template: A standardized template for compiling and presenting resource utilization metrics over a defined period, helping teams understand performance trends and make informed decisions.
Cloud Services
AWS
- Amazon CloudWatch: A monitoring service that provides data and actionable insights to monitor your applications, respond to system-wide performance changes, and optimize resource utilization.
- AWS Cost Explorer: A tool to visualize, understand, and manage your AWS costs and usage over time, which can help in analyzing compute resource utilization.
- AWS Compute Optimizer: A service that recommends optimal AWS resource configurations based on your actual usage, helping you improve performance and reduce costs.
Azure
- Azure Monitor: A service that helps you understand how your applications are performing and can help you analyze metrics and logs.
- Azure Advisor: Provides personalized recommendations to improve the performance and optimize your Azure resources based on usage patterns.
- Azure Metrics: A feature within Azure Monitor that enables you to collect and analyze metrics from various Azure resources for performance evaluations.
Google Cloud Platform
- Google Cloud Monitoring: Provides visibility into your applications and infrastructure, offering insights into the performance of your compute resources.
- Google Cloud Logging: A service that allows you to store, search, analyze, monitor, and alert on log data and helps in understanding resource performance.
- Google Cloud Recommendations AI: Gives suggestions based on usage patterns and can help optimize the configuration of computing resources.
Question: How do you select and use compute resources in your workload?
Pillar: Performance Efficiency (Code: PERF)
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