Amazon Elastic Compute Cloud
Amazon Elastic Compute Cloud (EC2) is an Amazon Web Services service that provides resizable virtual computing capacity through configurable virtual machine instances.
Amazon Web Services in Action, Third Edition: An in-depth guide to AWS
Amazon Elastic Compute Cloud is an AWS service that provides resizable virtual servers on demand.
- How it is used
- Hosts web applications on virtual machines, including WordPress web servers behind a load balancer.
- How deep it goes
- Defines instances and their console attributes, then develops deployment, monitoring, regional placement, and failure planning rather than virtualization internals.
- Examples
- Uses a two-instance WordPress deployment, EC2 console inspection, and an additional virtual machine in Sydney.
- What you can do after
- Operate/configure it by inspecting instances, selecting deployment settings, monitoring usage, and designing around single-instance failure.
Build Python Web Apps with Streamlit
Amazon EC2 is an AWS service that provides resizable virtual machines for running applications.
- How it is used
- Hosts Dockerized applications on resizable cloud virtual machines within an AWS deployment.
- How deep it goes
- Explains EC2 through request routing, containers, load balancing, provisioning, and SSH troubleshooting, but not instance administration internals.
- Examples
- Uses a Dockerized Streamlit application deployed through Elastic Beanstalk to illustrate EC2 instances and request handling.
- What you can do after
- Operate a containerized application on EC2 through Elastic Beanstalk and diagnose selected instance-level deployment problems using SSH.
Read how Build Python Web Apps with Streamlit explains Amazon Elastic Compute Cloud →
Machine Learning System Design
A cloud computing service that provides resizable virtual compute instances.
- How it is used
- Deploys batch and real-time inference workers when sustained load, low latency, scaling, and AWS integration matter.
- How deep it goes
- Specifies deployment patterns, Spot tradeoffs, scaling, and monitoring, but defers exact instance and GPU selection to experiments.
- Examples
- Runs queue-driven batch inference and stateless real-time workers for a high-load image-serving system.
- What you can do after
- Operate/configure EC2-backed inference services with load balancing, replaceable workers, cost controls, and resource monitoring.
Read how Machine Learning System Design explains Amazon Elastic Compute Cloud →
Related concepts
- virtual machinekind of · A virtual machine is a software-defined execution environment that presents an abstract computer or machine model for running an operating system or programs.
- load balancingused by · Load balancing is the distribution of requests or computational work across multiple resources to manage demand, reduce workload imbalance, and improve utilization or availability.
- single point of failurekind of · A single point of failure is a component, dependency, person, or condition whose failure can prevent a system or critical capability from functioning because no adequate alternative is available.
- AWS consoleused by · The AWS console is a web-based graphical interface for configuring, operating, and managing Amazon Web Services resources and services.
- CloudFormation templateconfigured by · A CloudFormation template is a declarative JSON or YAML document that specifies AWS resources, their configuration, and their dependencies.
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