[{"data":1,"prerenderedAt":566},["ShallowReactive",2],{"content-svc-lambda-guides-aws-lambda-operator-guide-event-driven-benefits":3},{"markdown":4,"frontMatterAttributes":5,"bodyRaw":8,"menu":9,"menuType":563,"isCollapseableMenu":12,"nextDocItem":41,"previousDocItem":30,"contributorPaths":564,"contentName":565,"slug":40,"readingTime":33},"\u003Ch2>Replacing polling and webhooks with events\u003C\u002Fh2>\n\u003Cp>Many traditional architectures frequently use polling and webhook mechanisms to communicate state between different components. Polling can be highly inefficient for fetching updates since there is a lag between new data becoming available and synchronization with downstream services. Webhooks are not always supported by other microservices that you want to integrate with. They may also require custom authorization and authentication configurations. In both cases, these integration methods are challenging to scale on-demand without additional work by development teams.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"\u002Fassets\u002Fexternal\u002Fservice\u002Flambda\u002Fguides\u002Faws-lambda-operator-guide\u002Fassets\u002Fimages\u002Fevent-driven-architectures-figure-7.png\" alt=\"\">\u003C\u002Fp>\n\u003Cp>Both of these mechanisms can be replaced by events, which can be filtered, routed, and pushed downstream to consuming microservices. This approach can result in less bandwidth consumption, CPU utilization, and potentially lower cost. These architectures can also reduce complexity, since each functional unit is smaller and there is often less code.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"\u002Fassets\u002Fexternal\u002Fservice\u002Flambda\u002Fguides\u002Faws-lambda-operator-guide\u002Fassets\u002Fimages\u002Fevent-driven-architectures-figure-8.png\" alt=\"\">\u003C\u002Fp>\n\u003Cp>Event-driven architectures can also make it easier to design near-real-time systems, helping organizations move away from batch-based processing. Events are generated at the time when state in the application changes, so the custom code of a microservice should be designed to handle the processing of a single event. Since scaling is handled by the Lambda service, this architecture can handle significant increases in traffic without changing custom code. As events scale up, so does the compute layer that processes events.\u003C\u002Fp>\n\u003Ch2>Reducing complexity\u003C\u002Fh2>\n\u003Cp>Microservices enable developers and architects to decompose complex workflows. For example, an ecommerce monolith may be broken down into order acceptance and payment processes with separate inventory, fulfillment and accounting services. What may be complex to manage and orchestrate in a monolith becomes a series of decoupled services that communicate asynchronously with event messages.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"\u002Fassets\u002Fexternal\u002Fservice\u002Flambda\u002Fguides\u002Faws-lambda-operator-guide\u002Fassets\u002Fimages\u002Fevent-driven-architectures-figure-9.png\" alt=\"\">\u003C\u002Fp>\n\u003Cp>This approach also makes it possible to assemble services that process data at different rates. In this case, an order acceptance microservice can store high volumes of incoming orders by buffering the messages in an SQS queue.\u003C\u002Fp>\n\u003Cp>A payment processing service, which is typically slower due to the complexity of handling payments, can take a steady stream of messages from the SQS queue. It can orchestrate complex retry and error handling logic using AWS Step Functions, and coordinate active payment workflows for hundreds of thousands of orders.\u003C\u002Fp>\n\u003Ch2>Improving scalability and extensibility\u003C\u002Fh2>\n\u003Cp>Microservices generate events that are typically published to messaging services like \u003Ca href=\"https:\u002F\u002Faws.amazon.com\u002Fsns\u002F\">Amazon SNS\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Faws.amazon.com\u002Fsqs\u002F\">Amazon SQS\u003C\u002Fa>. These behave like an elastic buffer between microservices and help handle scaling when traffic increases. Services like \u003Ca href=\"https:\u002F\u002Faws.amazon.com\u002Feventbridge\u002F\">Amazon EventBridge\u003C\u002Fa> can then filter and route messages depending upon the content of the event, as defined in rules. As a result, event-based applications can be more scalable and offer greater redundancy than monolithic applications.\u003C\u002Fp>\n\u003Cp>This system is also highly extensible, allowing other teams to extend features and add functionality without impacting the order processing and payment processing microservices. By publishing events using EventBridge, this application integrates with existing systems, such as the inventory microservice, but also enables any future application to integrate as an event consumer. Producers of events have no knowledge of event consumers, which can help simplify the microservice logic.\u003C\u002Fp>\n\u003Cp>To learn more, read \u003Ca href=\"https:\u002F\u002Fstackoverflow.blog\u002F2020\u002F03\u002F16\u002Fhow-event-driven-architecture-solves-modern-web-app-problems\u002F\">How event-driven architecture solves modern web app problems\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fpages.awscloud.com\u002FAWS-Learning-Path-How-to-Use-Amazon-EventBridge-to-Build-Decoupled-Event-Driven-Architectures_2020_LP_0001-SRV.html\">How to Use Amazon EventBridge to Build Decoupled, Event-Driven Architectures\u003C\u002Fa>.\u003C\u002Fp>\n",{"title":6,"order":7},"The benefits of event-driven architectures",4,"## Replacing polling and webhooks with events\n\nMany traditional architectures frequently use polling and webhook mechanisms to communicate state between different components. Polling can be highly inefficient for fetching updates since there is a lag between new data becoming available and synchronization with downstream services. Webhooks are not always supported by other microservices that you want to integrate with. They may also require custom authorization and authentication configurations. In both cases, these integration methods are challenging to scale on-demand without additional work by development teams.\n\n![](\u002Fassets\u002Fexternal\u002Fservice\u002Flambda\u002Fguides\u002Faws-lambda-operator-guide\u002Fassets\u002Fimages\u002Fevent-driven-architectures-figure-7.png)\n\nBoth of these mechanisms can be replaced by events, which can be filtered, routed, and pushed downstream to consuming microservices. This approach can result in less bandwidth consumption, CPU utilization, and potentially lower cost. These architectures can also reduce complexity, since each functional unit is smaller and there is often less code.\n\n![](\u002Fassets\u002Fexternal\u002Fservice\u002Flambda\u002Fguides\u002Faws-lambda-operator-guide\u002Fassets\u002Fimages\u002Fevent-driven-architectures-figure-8.png)\n\nEvent-driven architectures can also make it easier to design near-real-time systems, helping organizations move away from batch-based processing. Events are generated at the time when state in the application changes, so the custom code of a microservice should be designed to handle the processing of a single event. Since scaling is handled by the Lambda service, this architecture can handle significant increases in traffic without changing custom code. As events scale up, so does the compute layer that processes events.\n\n## Reducing complexity\n\nMicroservices enable developers and architects to decompose complex workflows. For example, an ecommerce monolith may be broken down into order acceptance and payment processes with separate inventory, fulfillment and accounting services. What may be complex to manage and orchestrate in a monolith becomes a series of decoupled services that communicate asynchronously with event messages.\n\n![](\u002Fassets\u002Fexternal\u002Fservice\u002Flambda\u002Fguides\u002Faws-lambda-operator-guide\u002Fassets\u002Fimages\u002Fevent-driven-architectures-figure-9.png)\n\nThis approach also makes it possible to assemble services that process data at different rates. In this case, an order acceptance microservice can store high volumes of incoming orders by buffering the messages in an SQS queue.\n\nA payment processing service, which is typically slower due to the complexity of handling payments, can take a steady stream of messages from the SQS queue. It can orchestrate complex retry and error handling logic using AWS Step Functions, and coordinate active payment workflows for hundreds of thousands of orders.\n\n## Improving scalability and extensibility\n\nMicroservices generate events that are typically published to messaging services like [Amazon SNS](https:\u002F\u002Faws.amazon.com\u002Fsns\u002F) and [Amazon SQS](https:\u002F\u002Faws.amazon.com\u002Fsqs\u002F). These behave like an elastic buffer between microservices and help handle scaling when traffic increases. Services like [Amazon EventBridge](https:\u002F\u002Faws.amazon.com\u002Feventbridge\u002F) can then filter and route messages depending upon the content of the event, as defined in rules. As a result, event-based applications can be more scalable and offer greater redundancy than monolithic applications.\n\nThis system is also highly extensible, allowing other teams to extend features and add functionality without impacting the order processing and payment processing microservices. By publishing events using EventBridge, this application integrates with existing systems, such as the inventory microservice, but also enables any future application to integrate as an event consumer. Producers of events have no knowledge of event consumers, which can help simplify the microservice logic.\n\nTo learn more, read [How event-driven architecture solves modern web app problems](https:\u002F\u002Fstackoverflow.blog\u002F2020\u002F03\u002F16\u002Fhow-event-driven-architecture-solves-modern-web-app-problems\u002F) and [How to Use Amazon EventBridge to Build Decoupled, Event-Driven Architectures](https:\u002F\u002Fpages.awscloud.com\u002FAWS-Learning-Path-How-to-Use-Amazon-EventBridge-to-Build-Decoupled-Event-Driven-Architectures_2020_LP_0001-SRV.html).",[10,21,137,245,312,382,486,555],{"title":-1,"collapsible":11,"isCollapsed":12,"content":13},false,true,[14],{"title":15,"order":16,"time":17,"path":18,"id":19,"link":20},"Introduction",1,"4 min","intro","intro.md","\u002Fcontent\u002Fservice\u002Flambda\u002Fguides\u002Faws-lambda-operator-guide\u002Fintro",{"title":22,"collapsible":12,"isCollapsed":11,"content":23},"Event-driven 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