Best Application Development Software for AWS X-Ray

New Relic empowers enterprise application developers with a comprehensive, data-driven approach to planning, building, deploying, and managing software. Our unified data platform aggregates all telemetry data, providing robust full-stack analysis tools that offer valuable insights across every stage of the development lifecycle. Built for large-scale environments, New Relic enables swift issue identification and resolution, ensuring optimal performance and enhanced reliability. Streamline workflows, uncover root causes, and foster continuous improvement and innovation. With New Relic, deliver exceptional customer experiences, speed up development cycles, and drive growth with powerful capabilities tailored to enterprise application development.

Engineered for peak performance and efficient resource use, KrakenD can manage a staggering 70k requests per second on just one instance. Its stateless build ensures hassle-free scalability, sidelining complications like database upkeep or node synchronization. In terms of features, KrakenD is a jack-of-all-trades. It accommodates multiple protocols and API standards, offering granular access control, data shaping, and caching capabilities. A standout feature is its Backend For Frontend pattern, which consolidates various API calls into a single response, simplifying client interactions. On the security front, KrakenD is OWASP-compliant and data-agnostic, streamlining regulatory adherence. Operational ease comes via its declarative setup and robust third-party tool integration. With its open-source community edition and transparent pricing model, KrakenD is the go-to API Gateway for organizations that refuse to compromise on performance or scalability.

Amazon Elastic Container Service (Amazon ECS), is a fully managed container orchestration and management service. ECS is used by customers such as Duolingo and Samsung, GE and Cook Pad to run their most sensitive and critical mission-critical applications. It offers security, reliability and scalability. ECS is a great way to run containers for a variety of reasons. AWS Fargate is serverless compute for containers. You can also run ECS clusters with Fargate. Fargate eliminates the need for provisioning and managing servers. It allows you to specify and pay per application for resources and improves security by application isolation by design. ECS is also used extensively in Amazon to power services like Amazon SageMaker and AWS Batch. It is also used by Amazon.com's recommendation engines. ECS is extensively tested for reliability, security, and availability.

AWS App Mesh provides service mesh to facilitate communication between your services across different types of computing infrastructure. App Mesh provides visibility and high availability to your applications. Modern applications often include multiple services. Each service can be developed using different types of compute infrastructure such as Amazon EC2, Amazon ECS and Amazon EKS. It becomes more difficult to spot errors and redirect traffic after they occur, and to safely implement code changes. This was done by creating monitoring and control logic in your code and then redeploying your services whenever there were changes.

You can run code without worrying about servers. Only pay for the compute time that you use. AWS Lambda allows you to run code without having to provision or manage servers. You only pay for the compute time that you use. Lambda allows you to run code for any type of backend service or application - and all this with zero administration. Upload your code, and Lambda will take care of scaling your code with high availability. Your code can be set up to trigger automatically from other AWS services, or you can call it directly from any mobile or web app. AWS Lambda runs your code automatically without you having to manage or provision servers. Simply write the code and upload it directly to Lambda. AWS Lambda automatically scales the application by running code according to each trigger. Your code runs in parallel, processing each trigger separately, scaling exactly with the workload.