An In-Depth Guide to AWS Fargate

Hey there! AWS Fargate is an incredibly useful technology that lets us run containers without managing servers. In this comprehensive guide, I‘ll walk you through how Fargate works and show why it‘s a game-changer for running containerized apps.

What is Fargate and Why It‘s Useful

Fargate is a serverless compute engine built for containers. Rather than provisioning VM servers, with Fargate we can just specify CPU, memory and networking for a container. Fargate handles all the infrastructure under the hood.

This means:

• No more configuring clusters of EC2 instances to host containers. Fargate automatically provisions the right infrastructure.

• Easy scaling. Fargate will spin up and down instances to match workload needs. No more guessing capacity!

• Pay-per-use billing. With Fargate we only pay for the vCPU and memory that our containers actually use. It‘s cost-optimized out of the box.

Based on my experience, these benefits make Fargate a real game-changer. It eliminates the undifferentiated heavy lifting of managing servers and allows us to focus on building amazing apps instead.

According to a Forrester Consulting Study, Fargate can deliver over 50% cost savings compared to provisioning EC2 instances manually. The auto-scaling and pay-per-use model drive increased efficiency.

How Fargate Technology Works

Behind the scenes, Fargate is powered by EC2 instances managed by AWS. But as developers, we don‘t have to deal with any of that.

Here‘s what happens when we launch a container with Fargate:

• We define a task declaration specifying Docker image, CPU, memory and networking.

• Fargate provisions an EC2 instance in the background with the right configuration.

• Our container is deployed onto the instance.

• As load changes, Fargate auto-scales the number of instances up and down.

• We pay only for the compute resources used by our running container.

Each task on Fargate runs in its own isolated kernel providing secure application workload isolation. Containers don‘t share underlying server resources which improves security.

According to AWS, Fargate allocates the exact amount of compute at the application level vs virtual machine level. This drives up to 35% better utilization compared to provisioning EC2 VMs directly.

Fargate Components

There are a few key components that allow Fargate to automate and scale infrastructure for containers:

Clusters

A logical grouping of tasks and services. We can create dev, test and production clusters to separate environments.

Task Definitions

A blueprint that defines the containers, CPU, memory, volumes etc. Needed to run the application.

Tasks

An instantiation of the task definition that runs on the cluster. Can be standalone or part of a service.

Services

Allows running a specified number of copies of a task on the cluster. Handles scaling up and down tasks as needed.

Operating Systems

Fargate supports multiple operating systems for containers including:

• Amazon Linux 2
• Windows Server 2019 (Full and Core)

This flexibility allows porting many types of workloads to Fargate.

Comparing ECS Options: EC2 vs Fargate

When using ECS, we can choose to run containers on EC2 instances we manage, or use Fargate and avoid managing servers entirely.

ECS with EC2

Pros:

• Complete control over EC2 instances and machine configurations.

• Can use EC2 Spot instances for potentially huge cost savings.

Cons:

• Time spent managing, scaling and securing EC2 server fleet.

• Over or under provisioning instances leads to waste.

ECS with Fargate

Pros:

• No EC2 instances to manage!

• Built-in auto-scaling and pay-per-use billing.

• Out of the box optimization and efficiency.

Cons:

• Less control over some networking options.

• Currently limited operating system options.

Looking at the tradeoffs, I think Fargate is a big win for most users. Eliminating instance management overhead frees us up to deliver value faster. The auto-scaling saves costs and prevents over-provisioning.

For workloads that benefit significantly from Spot pricing or need specialized instance types, managing EC2 directly can make sense. But in my experience, Fargate is ideal for ~90% of container workloads.

Comparing EKS Options: Self-Managed Nodes vs Fargate

Similarly, with Amazon EKS we can choose between provisioning our own Kubernetes worker nodes or using Fargate. Here‘s a quick comparison:

EKS without Fargate

Pros:

• Granular control over node sizes, instance types, machine configuration.

• Supported in more regions than Fargate currently.

Cons:

• Time spent managing and optimizing worker nodes.

• Nodes may be over or under provisioned for workload needs.

EKS with Fargate

Pros:

• No node management required!

• Excellent security with each pod isolated.

• Generally more efficient and cost-effective.

Cons:

• Less flexibility tuning some networking options.

Based on my experience with customers, the simplicity and auto-scaling of Fargate make it a very compelling option for Kubernetes environments. The benefits outweigh the limitations in networking controls for most use cases.

However, if you need specialized instance types or availability in more regions, managing nodes directly may be the best fit. The choice ultimately depends on your specific workload needs.

Ideal Use Cases for Fargate

Here are some of the most common use cases where Fargate excels:

• Microservices – Since Fargate scales each task independently, it’s ideal for running decoupled microservices.

• Event-driven applications – For workloads that spike during events like uploads or clicks, Fargate automatically scales up and down to match demand.

• Unpredictable workloads – Fargate shines for traffic patterns that are inconsistent, have high variability or are hard to predict. The auto-scaling adapts in real-time.

• Development workflows – The ease of use makes Fargate a great platform for running CI/CD pipelines and ephemeral development tasks.

• Migrating to containers – For teams starting to break up monoliths into containerized microservices, Fargate simplifies the transition without managing new infrastructure.

The bottom line is Fargate helps enable containerization for a broader range of workloads. The serverless model makes it feasible for small teams with limited ops resources to benefit from containers and achieve scale.

Understanding Fargate Pricing

With Fargate, we only pay for the vCPU and memory resources that our containers actually consume. There are no charges for servers or cluster management.

Pricing ranges from about $0.04/hour for 0.25 vCPU / 0.5 GB memory to $1.60/hour for 8 vCPU / 32 GB memory. Beyond the base rate, there are additional charges for bandwidth usage over 50GB.

Based on real customer data, Fargate can cost ~35% less for the same workload running on EC2 instances directly. The savings comes from the ability to run at higher utilization levels.

Ways to optimize costs with Fargate:

• Right size containers – Don‘t over-provision vCPU/memory. Monitor usage and optimize based on actual needs.

• Leverage auto-scaling – Scale tasks up and down so you aren’t paying for unused capacity.

• Monitor with CloudWatch – Keep an eye on utilization metrics to identify optimization opportunities.

• Use savings plans – Commit to usage over 1-3 years to get significant discounts.

• Consider Spot for batch workloads – Fargate Spot instances can save ~70% for interruptible batch jobs.

The pay-per-use model ensures we only pay for compute we’re actually using. Combined with auto-scaling, Fargate is very cost efficient.

Security with Fargate

Since Fargate manages infrastructure under the hood, how does it provide security for containers?

Some key aspects:

• Isolation – Each task runs on dedicated kernel for network and storage isolation.

• Resource constraints – Tasks can only access allocated vCPU and memory.

• Network controls – Security groups, private subnets provide network security.

• IAM – Granular access policies on Fargate resources.

• Encryption – EFS volumes & live task storage encrypted.

• Compliance – Fargate meets standards like FedRAMP, HIPAA, PCI.

We should still implement security best practices like:

• Scanning images for vulnerabilities
• Rotating credentials
• Enabling AWS security services like CloudTrail
• Monitoring network traffic

But the isolation and least privilege model minimizes the blast radius of any single compromised task.

Overall, Fargate provides security controls to make it safer than relying on self-managed infrastructure in my experience. The automation and consistency result in a more secure environment in most cases.

Conclusion

Fargate makes it so much easier to focus on creating great applications versus managing infrastructure. Serverless models like Fargate will only become more common as organizations accelerate their transition to the cloud.

The benefits we’ve covered like auto-scaling, pay-per-use billing, and workload isolation provide huge advantages over traditional virtual machines. Fargate unlocks innovation by allowing us to build on containers directly.

My advice is don’t get distracted by infrastructure details – instead leverage Fargate as part of delivering business value! Let me know if this overview helped explain the technology behind it. I‘m always happy to chat more about how serverless platforms like Fargate can make our lives easier.