Now, these devs no longer have to choose. Before SnapStart, if these developers wanted to implement serverless Lambda functions, they faced a dilemma: Suffer the slow cold starts of their Java functions or refactor their code in another language. Developers no longer have to choose preference or performanceĪnother unique benefit of SnapStart is that developers no longer need to choose between the tools they prefer and good performance. This ensures an organization's applications are always available and responsive, even during peak usage times. Because Lambda functions are fully managed by AWS, organizations can easily scale their applications up or down in response to demands, without worrying about managing infrastructure or provisioning new resources. ![]() On the operations side, Lambda also offers significant benefits, particularly when it comes to managing evolving usage patterns. ![]() Efficiently manage evolving usage patterns With a simple programming model and seamless integration with other AWS services, developers can quickly and easily create applications that are scalable and secure. One key benefit of using AWS Lambda functions is the ease with which developers can build and deploy powerful serverless applications. Seamless deployment of powerful serverless applications What are the unique benefits of working with SnapStart?ġ. ![]() The feature also requires minimal code changes by developers. With SnapStart, AWS handles initialization ahead of time in a way that speeds up Java functions considerably. This is one reason why AWS created SnapStart. Even though latency during cold starts isn't a Java-specific problem, when paired with one of the many popular frameworks, Java functions on Lambda can be a headache for developers. For developers building user-facing APIs or synchronous apps with Java, these numbers are not a good fit for some below-latency requirements. In the case of Java apps built with frameworks, cold starts on Lambda are significant. Depending on the size and complexity of the function as well as the dependencies it uses, the process can take several seconds from start to finish. This requires downloading the function's code and initializing any external frameworks or libraries. If there is a requirement to persist the data after execution, make sure to offload it to an external storage system (such as EFS drive or Amazon S3).Put simply, SnapStart is designed to improve the startup times of Java-based Lambda functions.Įvery function goes through an initialization stage when it's invoked for the first time. For each function invocation, the function should assume availability of additional local storage provided via the Ephemeral storage option and after execution is complete, it disappears afterwards. ![]() This way, users get access to a secure, low-latency temporary file system within Lambda Functions, with the flexibility of reconfiguring the storage as required up to 10 GB.Important thing to note, Ephemeral storage is a temporary file system available within each Lambda function execution and not shared across all function invocations. Even though it solved issues associated with storage, users still faced performance degradations through cold start and significantly extra cost for having to use EFS, not to mention the general complexity of having to manage more moving pieces.Īll of this is now solved as AWS introduced the Ephemeral storage option included in Lambda, which allows users to configure temporary storage required during each execution between 512 MB and 10 GB. If you have ever used AWS Lambda for processing large files (such as PDFs, images, etc.) or running ETLs on massive dataset or for operationalizing Machine Learning models, you know the pain of putting up with runtime storage requirements and performance.Īs a workaround to get more local storage, users had to mount an Elastic File System (EFS) to the Lambda function or use S3 as intermediary storage to read/write data during execution. Benefits of new feature Lambda Ephemeral storage
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