Cloud deployment today is less about simply “pushing code” and more about deciding how much infrastructure you want to manage, how deeply you need to customize, and what operational trade-offs you’re willing to accept. AWS Elastic Beanstalk and AWS App Runner both sit in the managed application deployment space, but they serve two very different philosophies: hands-on control with automation versus fully abstracted, serverless simplicity.

AWS Elastic Beanstalk: Managed Infrastructure You Can Still Touch

So — What Exactly Is Elastic Beanstalk?

Elastic Beanstalk comes from the early era of “let AWS automate, but don’t take anything away from me.” When you deploy an application, it automatically provisions everything you’d expect in a traditional cloud architecture: EC2 instances, security groups, load balancers, VPC networking, auto scaling, and more. All you do is upload your application package — whether that’s a Docker image, a classic ZIP deployment, or something else — and Beanstalk stands up the environment.

If you want to SSH into a machine, adjust the OS, install a custom agent, or launch with a specific AMI, Beanstalk lets you. It’s managed — but not abstracted.

And here’s the defining trait:

Nothing is hidden from you.

Supported platforms include:

• Java, Python, Node.js, Ruby, Go, .NET, and PHP

• Docker (including multi-container setups)

What stands out:

• You see and control the infrastructure that runs your app

• OS-level debugging and customization are fully available

• Works well for both containerized workloads and older VM-centric applications

• Integrates natively with AWS services like RDS, ElastiCache, and private VPC layouts

Where it can feel heavy:

• Deployments are slower — provisioning EC2-based scaling can take minutes

• Auto scaling requires tuning

• You’re paying for the underlying infrastructure whether traffic is high or nonexistent

AWS App Runner: Serverless Deployment With Almost No Ops

What Is App Runner Designed For?

App Runner aims to deliver a Heroku-like experience for AWS: you give it a container or connect a Git repository, and AWS handles everything else. It builds the image, deploys it, scales it, and automatically exposes a secure HTTPS endpoint.

It’s powered behind the scenes by AWS Fargate — but you never interact with the servers, networking primitives, or container orchestration layers directly.

The platform’s core promise is simple:

Developers shouldn’t have to think about machines.

No SSH.
No instance tuning.
No networking complexity unless you explicitly opt in.

How deployments work:

• Pull code from GitHub/Bitbucket or use a pre-built ECR container

• App Runner builds and deploys automatically

• Each running instance is isolated in an AWS-managed environment

Where it shines:

• Almost zero operational overhead — push code and move on

• Fast, concurrency-based scaling (instead of CPU-based instance scaling)

• Warm instance pools significantly reduce or eliminate cold starts

• Built-in CI/CD integration feels modern and effortless

Where the trade-offs show up:

• Limited ability to customize the runtime or host environment

• Best suited only for stateless HTTP workloads

• Costs can scale quickly for sustained or heavy traffic

Technical Comparison Matrix

+------------------------+---------------------------------+---------------------------------+
| Capability             | Elastic Beanstalk               | App Runner                      |
+------------------------+---------------------------------+---------------------------------+
| Abstraction Level      | Moderate (infra visible)        | High (infra hidden)             |
| Deployments            | ZIP bundles, containers         | High (infra hidden)             |
| Deployment Model       | Instance-based auto scaling     | Concurrency-based scaling       |
| Scaling                | Instance- AMIs, networking ctrl | None (logs + tracing only)      |
| Infrastructure Access  | First-class VPC integration     | Outbound only via VPC Connector |
| Networking             | Full VPC control                | Outbound only unless configured |
| Cost Structure         | Extensive                       | None (instances always running) |
| Customization          | Extensive                       | Minimal                         |
| Operational Overhead   | Moderate                        | Very low                        |
| Cold Starts            | Not applicable                  | (Blank)

Deep Technical Breakdown

Deployment and Day-to-Day Experience

Elastic Beanstalk

• Requires some familiarity with AWS environments and runtime configuration

• Deployments feel traditional — package code, configure, deploy

• Ideal when debugging needs deep inspection

• Works well in migration scenarios where the application expects a full OS environment

App Runner

• Very simple: repo or image → deploy → live URL

• No need to understand instances, scaling groups, or networking paths

• Logs and telemetry come through CloudWatch — not via direct system access

• Perfect for microservices or development teams optimizing for fast iteration

Scaling Behavior

Elastic Beanstalk

• Relies on scaling EC2 instances

• Scaling decisions generally come from CPU or latency metrics

• Startup times can take a while, so teams often overprovision

App Runner

• Designed for traffic-responsive scaling

• Simply set concurrency limits per instance; platform does the rest

• Startup times are fast, avoiding the “burst traffic lag” seen in EC2 scaling

Networking and Security

Elastic Beanstalk

• Integrates into private subnets without extra configuration

• Perfect for services that need internal access to databases or secure networks

App Runner

• Public-first design

• Private networking is possible — but requires explicit VPC Connectors

• Great for public APIs, less ideal for strictly internal workloads unless architected carefully

Cost Reality Check

Elastic Beanstalk

• Costs accumulate whether the application is active or idle

• Great for predictable, steady traffic

• Reserved instances or savings plans can significantly optimize spend

App Runner

• Pay only for compute and memory used

• Ideal for unpredictable or intermittent workloads

• Can become more expensive than EC2-based setups at large scale or constant load

CI/CD and Automation

Elastic Beanstalk

• Flexible, but setup requires deliberate configuration

• Supports advanced deployment patterns like blue/green or rolling upgrades

App Runner

• CI/CD is built directly into the workflow — commit equals deployment

• Rollbacks are automated and handled by the platform

Which One Should You Use?

Elastic Beanstalk is a strong choice if:

• Your application requires OS-level tweaks or dependencies

• You rely on inbound private networking or non-public endpoints

• You’re migrating existing workloads that weren’t built for container-native environments

• You need deep control for compliance, observability, or tuning

App Runner is ideal if:

• Your workloads are stateless and HTTP-based

• You want a fully managed experience with minimal configuration

• Your traffic patterns are unpredictable or spiky

• You’re already working in a container-first development model

Conclusion

There’s no universal winner here. Elastic Beanstalk offers flexibility and control when you still need to shape the environment. App Runner delivers the simplicity and “hands-off” development flow modern cloud teams crave.

Most organizations will land somewhere in the middle — using App Runner for fast-moving containerized services and Elastic Beanstalk for workloads that still require deeper control or legacy compatibility.

In the end, the right choice comes down to what your application needs today — and what flexibility you expect tomorrow. If speed and automation matter most, App Runner fits beautifully. If customization and visibility are non-negotiable, Beanstalk remains a solid and relevant option.