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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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Security
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- Evaluate and implement new security services and features regularly
- Automate testing and validation of security controls in pipelines
- Identify and prioritize risks using a threat model
- Keep up-to-date with security recommendations
- Keep up-to-date with security threats
- Identify and validate control objectives
- Secure account root user and properties
- Separate workloads using accounts
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- Analyze public and cross-account access
- Manage access based on life cycle
- Share resources securely with a third party
- Reduce permissions continuously
- Share resources securely within your organization
- Establish emergency access process
- Define permission guardrails for your organization
- Grant least privilege access
- Define access requirements
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- Build a program that embeds security ownership in workload teams
- Centralize services for packages and dependencies
- Manual code reviews
- Automate testing throughout the development and release lifecycle
- Train for application security
- Regularly assess security properties of the pipelines
- Deploy software programmatically
- Perform regular penetration testing
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Reliability
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- How do you ensure sufficient gap between quotas and maximum usage to accommodate failover?
- How do you automate quota management?
- How do you monitor and manage service quotas?
- How do you accommodate fixed service quotas and constraints through architecture?
- How do you manage service quotas and constraints across accounts and Regions?
- How do you manage service quotas and constraints?
- How do you build a program that embeds reliability into workload teams?
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- How do you enforce non-overlapping private IP address ranges in all private address spaces?
- How do you prefer hub-and-spoke topologies over many-to-many mesh?
- How do you ensure IP subnet allocation accounts for expansion and availability?
- How do you provision redundant connectivity between private networks in the cloud and on-premises environments?
- How do you use highly available network connectivity for workload public endpoints?
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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
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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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- Optimize geographic placement of workloads based on their networking requirements
- 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
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- Articles coming soon
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Use optimized hardware-based compute accelerators
PostedDecember 20, 2024
UpdatedDecember 20, 2024
ByKevin McCaffrey
Selecting optimized hardware for your compute resources can significantly enhance performance efficiency. By leveraging hardware accelerators, specific computational tasks can be executed more rapidly than using traditional CPU-based processing. This ensures resource optimization based on application requirements and boosts overall system performance.
Best Practices
- Identify Workload Characteristics: To implement optimized hardware accelerators, first understand your workload’s specific computational needs. Profiling application performance can help identify bottlenecks where accelerators can provide gains in efficiency.
- Evaluate Accelerator Options: Research and choose the right type of hardware accelerator based on your workload. Options like GPUs for parallel processing or custom ASICs for specialized tasks can enhance performance exponentially.
Supporting Questions
- Are you monitoring performance metrics to identify potential areas for hardware acceleration?
Roles and Responsibilities
- Architect: The architect is responsible for evaluating workload requirements and selecting appropriate compute resources, including hardware accelerators.
- DevOps Engineer: The DevOps engineer implements and monitors the infrastructure, ensuring that the selected compute resources are effectively utilized for optimal performance.
Artifacts
- Workload Performance Report: A document that outlines the performance metrics of current workloads, helping stakeholders understand where hardware accelerators can be implemented for improved efficiency.
- Accelerator Configuration Guide: A guide detailing the configuration settings of selected hardware accelerators, tailored to specific workloads.
Cloud Services
AWS
- Amazon EC2 with Inferentia: AWS’s EC2 instances powered by Inferentia accelerate machine learning inference workloads, allowing for efficient execution of deep learning models.
- Amazon Elastic Inference: This service enables you to attach low-cost GPU-powered inference acceleration to CPU instances, providing flexibility in optimizing performance and cost.
- Amazon Elastic Kubernetes Service (EKS): EKS supports the use of GPU instances for Kubernetes workloads, allowing for enhanced compute efficiency for data-intensive applications.
Question: How do you select and use compute resources in your workload?
Pillar: Performance Efficiency (Code: PERF)
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