Do constant work

Systems are prone to failure when exposed to large, rapid changes in load. To mitigate this, design systems to do constant work regardless of varying conditions. For example, if your workload performs health checks for thousands of servers, it should send the same size payload (a full snapshot of the current state) each time. By maintaining a consistent workload, even when there are significant changes in system health, you can ensure stable performance and avoid sudden spikes that could overwhelm your system.

Establish constant work champions in each team: Assign constant work champions within each workload team to oversee system behavior and ensure that workloads maintain a consistent processing pattern. These champions are responsible for identifying potential areas where workload fluctuations might occur and designing solutions that standardize the amount of work the system does.

Provide training on workload consistency: Train builder teams on best practices for maintaining constant workloads, including how to design systems that handle varying conditions without rapid changes in resource consumption. Training should cover examples like consistent health checks, batch processing, and smoothing techniques. Proper training helps teams understand how constant work can improve reliability and reduce the risk of failures due to workload spikes.

Develop constant workload guidelines and standards: Create clear guidelines for implementing constant work in workloads. These guidelines should include best practices for designing health checks, monitoring systems, and other processes to maintain a steady workload regardless of varying conditions. Documented standards help ensure consistency across workloads and improve system resilience.

Integrate workload stability validation into CI/CD pipelines: Integrate validation checks into CI/CD pipelines to ensure that workloads are designed to perform constant work. Automated checks can simulate different load scenarios and verify that the system maintains consistent behavior, reducing the risk of rapid workload changes that could lead to failures.

Define automated guardrails for workload consistency: Use automated tools to enforce best practices for maintaining consistent workloads across systems. Tools like AWS Lambda, Amazon SQS, and Amazon CloudWatch can help monitor system performance and adjust workload patterns to ensure stability. Automated guardrails help prevent sudden spikes in workload and maintain a consistent amount of work for better reliability.

Foster a culture of stable system behavior: Encourage builder teams to prioritize workload stability when designing systems, especially those that need to handle varying conditions. Recognize and reward teams that effectively design systems to perform constant work, ensuring resilience and stable performance. Open discussions about challenges related to workload fluctuations can help create a culture that values consistent system behavior.

Conduct regular workload reviews: Schedule regular reviews of workloads to evaluate their stability and ensure they maintain a consistent amount of work. These reviews should assess whether the system can handle varying conditions without causing large, rapid changes in load. Regular reviews help maintain a focus on designing stable and resilient systems.

Leverage automation for consistent workload management: Use Infrastructure as Code (IaC) tools like AWS CloudFormation or AWS CDK to automate the deployment of systems designed to perform constant work. Automating these processes helps maintain consistency across environments and ensures that workloads are managed uniformly.

Provide dashboards for visibility into workload patterns: Use dashboards to provide visibility into workload patterns and system behavior under different conditions. Tools like Amazon CloudWatch and AWS X-Ray can help monitor workload consistency and identify any fluctuations. Dashboards help builder teams proactively manage workload stability and identify areas for improvement.

Supporting Questions

• How do you ensure that builder teams design systems to perform constant work and maintain workload stability?
• What mechanisms are in place to validate that workloads remain consistent even under varying conditions?
• How do you align workload management practices with organizational standards for resilience and reliability?

Roles and Responsibilities

Constant Work Champion (within Builder Team)

Responsibilities:

• Promote the implementation of constant work in system design to maintain stability under varying conditions.
• Guide the team in identifying areas where workload fluctuations could occur and designing solutions to prevent them.

Application Developer

Responsibilities:

• Implement features that ensure workloads remain consistent, regardless of varying conditions.
• Use automated tools to validate that workloads maintain stability during development and testing.

Operations Team Member

Responsibilities:

• Assist builder teams with managing workloads to ensure they remain consistent and resilient to changes in load.
• Provide guidance and training to ensure alignment with best practices for constant workload design and management.

Artifacts

Constant Workload Guidelines and Standards: A document outlining best practices for maintaining a consistent workload across systems, including health checks and monitoring processes.

Training Resources for Constant Workload Management: Hands-on labs, workshops, and documentation to help teams understand how to design workloads that remain consistent under varying conditions.

Automated Workload Stability Validation Configurations: Scripts and configurations that help automate the validation of workload consistency across environments.

Relevant AWS Services

Training and Awareness Tools:

• AWS Skill Builder and AWS Well-Architected Labs: Resources for learning about workload stability, maintaining constant work, and designing reliable systems.
• AWS Trusted Advisor: Provides insights into workload configurations and recommendations for improving stability.

Workload Management and Guardrails:

• AWS Lambda: Helps create serverless functions that can be used to maintain constant work, regardless of varying input conditions.
• Amazon SQS: Provides queuing to manage workload consistency by controlling the flow of requests into a system.
• Amazon CloudWatch: Monitors workload performance and ensures that work remains constant, avoiding sudden spikes in load.

Monitoring and Visibility Tools:

• Amazon CloudWatch: Tracks metrics to monitor workload consistency, providing alerts for fluctuations that could indicate instability.
• AWS X-Ray: Traces requests across systems to identify variations in workload and assess the overall stability of services.
• AWS CloudFormation: Codifies workload management configurations to automate and standardize workload consistency across environments.