Distributed Computing
A computing paradigm that utilizes multiple interconnected computing resources to solve complex problems efficiently.
Description
Distributed computing in the context of AWS (Amazon Web Services) refers to the use of a network of interconnected servers and services to perform tasks collaboratively. Instead of relying on a single machine, distributed computing leverages the power of multiple systems to process data, run applications, and store information. AWS provides various services that facilitate distributed computing, including Amazon EC2 for scalable compute power, Amazon S3 for distributed storage, and AWS Lambda for serverless computing, which allows developers to execute code in response to events without provisioning servers. This approach enhances performance, enables fault tolerance, and improves resource utilization. For instance, large-scale data analytics can be achieved more efficiently by distributing data processing tasks across multiple EC2 instances. Additionally, distributed computing supports microservices architecture, allowing different components of an application to run on separate servers while communicating over the network, thus improving scalability and resilience.
Examples
- Using Amazon EMR (Elastic MapReduce) to process big data workloads by distributing tasks across a cluster of EC2 instances.
- Deploying a web application on AWS Elastic Beanstalk that utilizes multiple EC2 instances to handle incoming traffic and provide redundancy.
Additional Information
- Distributed computing can significantly reduce the time required for computational tasks by parallelizing workloads.
- AWS provides tools like AWS CloudFormation to automate the deployment and management of distributed computing resources.