Architect your product to meet availability targets and uptime service level agreements (SLAs)

High availability and low mean time to recovery (MTTR) are crucial for workloads. Ensuring that your architecture can withstand component failures is key to achieving availability targets and meeting service level agreements (SLAs). Architects need to build with resilience in mind, allowing for rapid recovery and continuity.

Best Practices

Design for High Availability

• Use Multi-AZ (Availability Zone) deployments for your databases and applications to ensure that failover can occur without significant downtime.
• Implement load balancing to distribute incoming traffic across multiple instances, ensuring that if one instance fails, others can handle the load.
• Utilize auto-scaling to automatically add or remove compute resources based on demand and health checks, which helps to maintain performance and availability during fluctuations.

Implement Robust Monitoring and Alerting

• Set up comprehensive monitoring to track the health and performance of all components of your architecture, using services like Amazon CloudWatch.
• Configure alerts for critical metrics to notify your operational team automatically when thresholds are crossed, facilitating a quick response to issues.
• Regularly review logs and performance data to identify potential issues before they lead to downtime.

Conduct Failure Simulations

• Perform chaos engineering experiments to simulate component failures in a controlled environment, which helps in understanding the behavior of your system and finding weaknesses.
• Document the outcomes of these tests to refine your incident response and resilience strategies, ensuring continuous improvement.
• Establish a culture of resilience within your team where regular testing of failure scenarios is a norm to continuously validate your architecture’s reliability.

Create and Validate SLAs and RTOs/RPOs

• Clearly define your service level agreements (SLAs) and recovery time objectives (RTOs) / recovery point objectives (RPOs) based on business requirements and communicate these throughout your organization.
• Regularly test your disaster recovery plans and backup strategies to ensure compliance with established SLAs, adjusting processes and technologies as necessary to meet evolving demands.
• Involve stakeholders in SLA discussions to ensure alignment between operational capabilities and business expectations.

Questions to ask your team

• Have you defined clear availability targets for your workloads?
• What methodologies do you use to measure uptime against your SLAs?
• How does your architecture handle component failures to maintain service continuity?
• What redundancy strategies have you implemented to support your availability goals?
• Do you have automated recovery processes in place for your workloads?
• How often do you test your workload’s failover and recovery processes?
• What monitoring tools are in place to alert you of service disruptions?
• Have you conducted a failure scenario analysis to identify potential points of failure in your architecture?

Who should be doing this?

Cloud Architect

• Design high availability and fault-tolerant architectures.
• Define and document availability targets and SLAs for the workload.
• Ensure architecture aligns with operational processes to support SLAs.
• Stay updated with AWS services and best practices for reliability.

DevOps Engineer

• Implement automated deployment and recovery processes.
• Monitor workload performance and availability against defined SLAs.
• Participate in testing of the failover and recovery procedures.
• Collaborate with the Cloud Architect to ensure operational readiness.

Site Reliability Engineer (SRE)

• Establish monitoring and alerting for critical components.
• Analyze incidents and component failures to drive improvements.
• Conduct post-mortems and reliability reviews to identify root causes.
• Optimize system performance and reduce mean time to recovery (MTTR).

Product Manager

• Set availability objectives and communicate them to stakeholders.
• Align product features and requirements with reliability goals.
• Drive cross-functional collaboration to ensure SLA compliance.
• Evaluate customer impact of uptime and outages.

Quality Assurance Engineer

• Ensure thorough testing of components under failure scenarios.
• Collaborate with developers to validate reliability requirements.
• Document validation processes for meeting availability targets.
• Provide feedback on feature designs based on reliability assessments.

What evidence shows this is happening in your organization?

• Availability and SLA Policy Template: A template for defining and documenting availability targets and SLA commitments, detailing the metrics and expectations for uptime in the organization.
• Reliability Checklists: A checklist that outlines critical components and considerations to ensure workloads are designed for resilience against component failures and are aligned with SLA requirements.
• Incident Response Plan: A comprehensive plan that includes procedures to follow in the event of component failures, aiming to minimize downtime and ensure rapid recovery to meet SLAs.
• Architectural Diagrams for High Availability: Visual representations of the architecture designed to support high availability, including redundancy, failover mechanisms, and load balancing strategies.
• Monthly Reliability Dashboard: A dashboard that tracks uptime metrics, mean time to recovery (MTTR), and resilience-related performance indicators to ensure adherence to SLAs.
• Resiliency Training Guide: A guide aimed at training staff on best practices in designing and operating reliable workloads that meet defined availability targets.
• Post-Mortem Analysis Report Template: A template for conducting post-incident reviews that analyze failures, recovery performance, and opportunities for improvement related to SLA commitments.

Cloud Services

AWS

• Amazon EC2 Auto Scaling: Automatically adjusts the number of EC2 instances in your application to maintain performance and availability.
• Amazon Route 53: DNS service that provides reliable routing and health checking, allowing for failover and traffic routing based on availability.
• AWS Elastic Load Balancing: Distributes incoming application traffic across multiple targets, increasing the availability of your applications.
• AWS CloudFormation: Enables you to model and set up your AWS resources in a reliable and predictable manner, facilitating quick recovery.
• Amazon RDS Multi-AZ: Offers synchronous data replication across multiple Availability Zones for enhanced database reliability.

Azure

• Azure Load Balancer: Distributes network traffic across multiple servers to ensure high availability and reliability.
• Azure Traffic Manager: Allows for high availability by directing users to the closest available instance, ensuring optimal performance.
• Azure Resource Manager: Facilitates automated deployment and management of applications for consistent and repeatable operations.
• Azure Site Recovery: Provides disaster recovery capabilities to ensure business continuity and quick recovery from failures.
• Azure SQL Database Geo-Replication: Offers geo-redundancy and automatic failover for increased database availability.

Google Cloud Platform

• Google Cloud Load Balancing: Provides a fully distributed and managed load balancing service that scales your applications with high availability.
• Google Cloud Autoscaler: Automatically adjusts the number of VM instances based on load metrics to ensure application performance and availability.
• Google Cloud Deployment Manager: Enables you to create and manage cloud resources with templates, streamlining deployments and enabling recovery.
• Google Cloud Spanner: A scalable and highly available database service designed for global transactions with strong consistency.
• Google Cloud Backup and DR: Provides backup and disaster recovery services to protect your applications and data against failures.