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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
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- Use version control
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Security
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- Evaluate and implement new security services and features regularly
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- Analyze public and cross-account access
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- Build a program that embeds security ownership in workload teams
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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?
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- How do you enforce non-overlapping private IP address ranges in all private address spaces?
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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
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- Automate healing on all layers
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Cost Optimization
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- Establish ownership of cost optimization
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- Perform cost analysis for different usage over time
- Analyze all components of this workload
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- 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
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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
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- Choose network protocols to improve performance
- Choose your workload's location based on network requirements
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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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Collect and record data store performance metrics
PostedDecember 20, 2024
UpdatedDecember 20, 2024
ByKevin McCaffrey
Understanding the performance of your data management solutions is crucial for maintaining optimal efficiency. By tracking performance metrics, you can identify bottlenecks, ensure that workload requirements are consistently met, and adapt your strategies to enhance overall performance.
Best Practices
- Establish Key Performance Indicators (KPIs): Define KPIs relevant to your data storage and access needs, such as latency, throughput, and error rates. Regularly review these metrics to ensure your data store meets the evolving demands of your applications.
- Automate Performance Monitoring: Utilize automated monitoring tools to continuously collect performance data. This enables real-time insights and allows for quick detection and resolution of performance issues.
Supporting Questions
- What performance metrics are currently monitored for your data store?
- How often are performance reviews conducted?
- Are there established thresholds for performance that trigger alerts?
Roles and Responsibilities
- Data Engineering Team: Responsible for setting up performance monitoring frameworks and ensuring the data storage solutions are optimized according to the recorded metrics.
- DevOps Team: Manages the deployment of monitoring tools and integrates them with existing infrastructure to ensure data store performance is consistently tracked.
Artifacts
- Performance Monitoring Dashboard: A centralized dashboard displaying real-time performance metrics of data stores, allowing for visual analysis and quick decision-making.
- Performance Review Reports: Regularly generated reports summarizing the data store performance based on collected metrics, highlighting trends and areas for improvement.
Cloud Services
AWS
- Amazon CloudWatch: Provides a powerful monitoring solution to collect and track metrics, set alarms, and initiate actions based on performance indicators of your AWS resources.
- AWS X-Ray: Helps analyze and debug distributed applications by tracking requests as they travel through your application, providing insights into data store performance.
Question: How do you store, manage, and access data in your workload?
Pillar: Performance Efficiency (Code: PERF)
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