But, you can also use these for Multi-AZ strategies or hybrid (on-premises workload/cloud recovery) strategies. For most examples in this blog post, we use a multi-Region approach to demonstrate DR strategies. This provides business assurance against events of sufficient scope that can impact multiple data centers across separate and distinct locations. Multi-Region strategyĪWS provides multiple resources to enable a multi-Region approach for your workload. Therefore, if you’re designing a DR strategy to withstand events such as power outages, flooding, and other other localized disruptions, then using a Multi-AZ DR strategy within an AWS Region can provide the protection you need. This significantly reduces the risk of a single event impacting more than one AZ. Each AZ consists of one or more data centers, located a separate and distinct geographic location. Scope of impact for a disaster event Multi-AZ strategyĮvery AWS Region consists of multiple Availability Zones (AZs). Therefore, you must choose RTO and RPO objectives that provide appropriate value for your workload. However, lower RTO and RPO cost more in terms of spend on resources and operational complexity. Recovery objectives: RTO and RPOįor RTO and RPO, lower numbers represent less downtime and data loss. This determines what is considered an acceptable loss of data.įigure 1. Recovery point objective (RPO): The maximum acceptable amount of time since the last data recovery point.This determines an acceptable length of time for service downtime. Recovery time objective (RTO): The maximum acceptable delay between the interruption of service and restoration of service.DR objectivesīecause a disaster event can potentially take down your workload, your objective for DR should be bringing your workload back up or avoiding downtime altogether. DR is a crucial part of your Business Continuity Plan. This blog post shows how to architect for disaster recovery (DR), which is the process of preparing for and recovering from a disaster. Ultimately, any event that prevents a workload or system from fulfilling its business objectives in its primary location is classified a disaster. Such events include natural disasters like earthquakes or floods, technical failures such as power or network loss, and human actions such as inadvertent or unauthorized modifications. This helps them prepare for disaster events, which is one of the biggest challenges they can face. This blog post shows how to use AWS App Mesh to implement a canary deployment strategy using AWS Step Functions for orchestrating the different steps during testing and AWS Code Pipeline for continuous delivery of each microservice.As lead solutions architect for the AWS Well-Architected Reliability pillar, I help customers build resilient workloads on AWS. For microservices, this is helpful when testing a complex distributed system because you can send a percentage of traffic to newer versions in a controlled manner.Ī service mesh provides application-level networking so your services can communicate with each other across multiple types of compute infrastructure. This decreases the impact of the bug(s) introduced in the new release. This is known as a “canary deployment.” A canary deployment can automatically switch traffic back to the old version if some inconsistencies are detected. When architects deploy a new version of an application, they want to test it on a set of users before routing all the traffic to the new version. This is implemented by taking advantage of correlation IDs Create a pipeline with canary deployments for Amazon ECS using AWS App Mesh This view from AWS X-Ray shows how a request can be tracked across different services. You’ll learn some fundamental application integration patterns and some of the benefits that asynchronous messaging can have over REST APIs for communication between microservices. This video evaluates several design patterns based on messaging and shows you how to implement them in your workloads to achieve the full capabilities of microservices. Application integration patterns for microservicesĪs Tim Bray said in his time with AWS, “If your application is cloud native, large scale, or distributed, and doesn’t include a messaging component, that’s probably a bug.” In this edition of Let’s Architect!, we explore the advantages, mental models, and challenges deriving from microservices with containers. However, working with microservices can also bring challenges. If applied correctly, there are multiple advantages to using microservices. They speed up software development and allow architects to quickly update systems to adhere to changing business requirements.Īccording to best practices, the different services should be loosely coupled, organized around business capabilities, independently deployable, and owned by a single team. Microservices structure an application as a set of independently deployable services.
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