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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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Implement Strategies to Improve Query Performance in Data Store
PostedDecember 20, 2024
UpdatedDecember 20, 2024
ByKevin McCaffrey
Optimizing query performance is critical for ensuring that applications scale seamlessly and respond quickly to user requests. Proper data management strategies enable applications to handle varying workloads efficiently while maintaining performance standards.
Best Practices
- Optimize Indexing Strategies: Implementing the right indexing strategies is crucial for enhancing query performance. By choosing appropriate primary and secondary indexes and regularly analyzing index usage, you ensure that queries are executed efficiently and reduce unnecessary data retrieval.
- Use Caching Mechanisms: Utilizing caching layers, such as Amazon ElastiCache, can significantly improve query response times. By storing frequently accessed data in memory, you minimize latency and reduce the load on your primary data store.
- Leverage Data Partitioning: Data partitioning distributes data across multiple nodes, improving read and write performance. Carefully designing partition strategies based on access patterns ensures that your workload maintains high throughput and low latency.
- Analyze and Optimize Query Patterns: Regularly analyzing query patterns can identify bottlenecks. Utilize AWS services like Amazon Athena or Amazon Redshift for running performance insights, allowing for iterative improvements in your query design and resource allocation.
Supporting Questions
- Are you regularly analyzing your query performance metrics?
- Have you implemented caching for frequently accessed data?
- Are your indexes optimized for the most common query patterns?
- Is there a data partitioning strategy in place to distribute load effectively?
Roles and Responsibilities
- Database Administrator: The Database Administrator is responsible for implementing indexing strategies, optimizing queries, and managing database performance to ensure efficient data retrieval.
- Cloud Architect: The Cloud Architect oversees the overall system design, ensuring that the chosen data storage solutions align with performance requirements while considering scalability.
Artifacts
- Query Performance Reports: Detailed reports generated from monitoring tools provide insights into how queries are performing, helping identify areas for optimization.
- Indexing Strategy Documentation: A living document outlining the indexing strategy for your data stores, detailing which indexes are in place, their purpose, and their performance impact.
Cloud Services
AWS
- Amazon RDS: Amazon RDS provides managed relational database services, allowing users to implement optimized query structures and automatic scaling based on workload demands.
- Amazon DynamoDB: DynamoDB offers a fully managed NoSQL database service that allows for high performance and scalability, with built-in optimization features like adaptive capacity and global secondary indexes.
- Amazon ElastiCache: ElastiCache enhances performance by caching data in-memory, allowing for quicker access compared to traditional data storage solutions.
- Amazon Athena: Athena enables you to analyze large datasets stored in Amazon S3 using standard SQL, helping optimize query patterns and performance insights.
Question: How do you store, manage, and access data in your workload?
Pillar: Performance Efficiency (Code: PERF)
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