[{"data":1,"prerenderedAt":399},["ShallowReactive",2],{"content-svc-lambda-guides-effectively-running-java-on-serverless-challenge":3},{"markdown":4,"frontMatterAttributes":5,"bodyRaw":11,"menu":12,"menuType":390,"isCollapseableMenu":15,"nextDocItem":59,"previousDocItem":44,"contributorPaths":391,"contentName":398,"slug":55,"readingTime":29},"\u003Cp>Java was built with a notion of running a server all the time.\nWith serverless computing like AWS Lambda, that is not the case anymore, as they offer ephemeral compute.\nTherefore, we see some churn when running Java applications on Serverless.\u003C\u002Fp>\n\u003Cp>In AWS Lambda, when a request comes in, the service checks if an execution environment is ready and available.\nIf available, the service assigns the request to that execution environment and the code in the Lambda function \nhandler gets executed.\nThis is termed as a "Warm Start" as the execution environment was already available and warm.\nHowever, if an execution environment is not available, for example,\nthe first request coming in, the service allocates a new\nexecution environment.\nThis involves downloading the Lambda function code to the execution environment, starting the runtime, \ninitializing the function code, and then executing the code.\nThis results in longer than normal response time and is termed as a “Cold Start.” \u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"\u002Fassets\u002Fexternal\u002Fservice\u002Flambda\u002Fguides\u002Feffectively-running-java-on-serverless\u002Fassets\u002Fchallenge_cold_start.png\" alt=\"ChallengeColdStart\">\u003C\u002Fp>\n\u003Cp>Java frameworks like Spring Boot often perform expensive operations during initial JVM startup time.\nTherefore, we witness a longer cold start time than any other Lambda runtime.\u003C\u002Fp>\n\u003Cp>A \u003Ca href=\"https:\u002F\u002Fdocs.aws.amazon.com\u002Flambda\u002Flatest\u002Fdg\u002Flambda-runtime-environment.html\">Lambda execution environment\u003C\u002Fa> \nsupports only one request at a time.\nAn execution environment processes a single request at the same time. \nWhile a single execution environment is processing a request, it cannot process other requests.\nTherefore, for another request a new execution environment will be needed,\nand therefore going through the initialization process again. \u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"\u002Fassets\u002Fexternal\u002Fservice\u002Flambda\u002Fguides\u002Feffectively-running-java-on-serverless\u002Fassets\u002Fchallenge.png\" alt=\"Challenge\">\u003C\u002Fp>\n\u003Cp>There are some interesting projects like \u003Ca href=\"https:\u002F\u002Fopenjdk.org\u002Fprojects\u002Fcrac\u002F\">Project CRaC\u003C\u002Fa> \nand \u003Ca href=\"https:\u002F\u002Fopenjdk.org\u002Fprojects\u002Fleyden\u002F\">Project Leyden\u003C\u002Fa> \nthat you can follow which aims to address some of those challenges.\u003C\u002Fp>\n\u003Cp>Meanwhile, there are best practices and built-in capabilities which AWS Lambda provides that you can incorporate\nto reduce cold start times compared to running on server-based compute options.\u003C\u002Fp>\n",{"title":6,"order":7,"authors":8},"Challenges",5,[9,10],"Dhiraj Mahapatro","Maximilian Schellhorn","Java was built with a notion of running a server all the time.\nWith serverless computing like AWS Lambda, that is not the case anymore, as they offer ephemeral compute.\nTherefore, we see some churn when running Java applications on Serverless.\n\nIn AWS Lambda, when a request comes in, the service checks if an execution environment is ready and available.\nIf available, the service assigns the request to that execution environment and the code in the Lambda function \nhandler gets executed.\nThis is termed as a \"Warm Start\" as the execution environment was already available and warm.\nHowever, if an execution environment is not available, for example,\nthe first request coming in, the service allocates a new\nexecution environment.\nThis involves downloading the Lambda function code to the execution environment, starting the runtime, \ninitializing the function code, and then executing the code.\nThis results in longer than normal response time and is termed as a “Cold Start.” \n\n![ChallengeColdStart](\u002Fassets\u002Fexternal\u002Fservice\u002Flambda\u002Fguides\u002Feffectively-running-java-on-serverless\u002Fassets\u002Fchallenge_cold_start.png)\n\nJava frameworks like Spring Boot often perform expensive operations during initial JVM startup time.\nTherefore, we witness a longer cold start time than any other Lambda runtime.\n\nA [Lambda execution environment](https:\u002F\u002Fdocs.aws.amazon.com\u002Flambda\u002Flatest\u002Fdg\u002Flambda-runtime-environment.html) \nsupports only one request at a time.\nAn execution environment processes a single request at the same time. \nWhile a single execution environment is processing a request, it cannot process other requests.\nTherefore, for another request a new execution environment will be needed,\nand therefore going through the initialization process again. \n\n![Challenge](\u002Fassets\u002Fexternal\u002Fservice\u002Flambda\u002Fguides\u002Feffectively-running-java-on-serverless\u002Fassets\u002Fchallenge.png)\n\nThere are some interesting projects like [Project CRaC](https:\u002F\u002Fopenjdk.org\u002Fprojects\u002Fcrac\u002F) \nand [Project Leyden](https:\u002F\u002Fopenjdk.org\u002Fprojects\u002Fleyden\u002F) \nthat you can follow which aims to address some of those challenges.\n\nMeanwhile, there are best practices and built-in capabilities which AWS Lambda provides that you can incorporate\nto reduce cold start times compared to running on server-based compute options.\n",[13,33,56,185,238,295,311,350,372],{"title":14,"collapsible":15,"isCollapsed":16,"content":17},"Introduction",false,true,[18],{"title":19,"order":20,"authors":21,"callout":22,"prerequisite":26,"time":29,"path":30,"id":31,"link":32},"Getting 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