History
Amazon introduced Fargate in 2017 as a serverless compute option for Amazon ECS (Elastic Container Service). Initially, it was only available for ECS, but AWS expanded its capabilities to integrate with EKS in December 2019. This integration allowed Kubernetes users to take advantage of serverless container orchestration without the need to manage individual nodes. AWS’s decision to extend Fargate to EKS was driven by the rapid adoption of Kubernetes and the demand for simplified infrastructure management.
Since its launch, Fargate for EKS has been instrumental in reducing the management overhead for Kubernetes workloads, streamlining operations for microservices, data processing tasks, and burstable workloads that require dynamic scaling.
Value Proposition
- Serverless Experience: Developers deploy pods directly without provisioning EC2 instances, reducing operational complexity.
- Automatic Scaling: Fargate automatically adjusts compute capacity based on workload demands, ensuring optimal resource utilization without manual intervention.
- Pay-as-you-go Pricing: Costs are calculated based on vCPU and memory usage, avoiding overprovisioning expenses typical with traditional instances. This pricing model allows precise control over spending.
- Enhanced Security: Each pod runs in its isolated runtime environment, improving security by design and reducing the blast radius of potential vulnerabilities.
- Simplified Management: AWS handles the patching, scaling, and management of the infrastructure, allowing DevOps to focus on application-level concerns, code deployments, and feature rollouts.
Challenges
- Cost Considerations: Although Fargate removes the overhead of managing nodes, its pay-per-use model can be more expensive for long-running applications compared to self-managed EC2 instances. Cost optimizations often require granular monitoring and workload adjustments.
- Resource Limitations: Fargate has specific vCPU and memory configurations, which may limit resource-intensive workloads. Heavy computational or memory-bound applications might struggle to perform optimally.
- Networking Constraints: With each pod running in its own isolated environment, managing networking between pods can require additional configurations. This isolation can lead to increased VPC costs and more complex routing setups.
- No DaemonSet Support: DaemonSets are not supported in Fargate, which can be a limitation for certain monitoring or logging agents that run across all nodes. Workarounds include sidecar containers or moving to a hybrid model with both EC2 and Fargate nodes.
Key Features
- Serverless Infrastructure Management: No need to provision or manage server instances. AWS automatically manages the underlying compute layer.
- Integrated with EKS: Seamlessly deploy Kubernetes pods with native support for Kubernetes orchestration, enabling the same kubectl commands for management.
- Enhanced Security Model: Pods run in isolated environments, enhancing multi-tenant security and preventing cross-namespace contamination.
- Efficient Auto-scaling: Automatically adjusts resources based on application demand, allowing for elastic scaling during peak loads and cost reductions during idle periods.
- Granular Pricing: Pay only for the vCPU and memory resources consumed during runtime. This is particularly beneficial for batch processing and event-driven workloads.
Types of Fargate Launch Modes
- Fargate (Default): Fully managed by AWS, best for applications that require granular scaling and isolated environments with minimal operational overhead.
- Fargate Spot: A cost-effective version of Fargate, leveraging spare capacity at up to 70% cost reduction but with the possibility of interruption. Ideal for non-critical, batch, or fault-tolerant workloads.
FAQ
What is the difference between Fargate and EKS?
Fargate is a serverless compute engine that lets you run containers without managing the underlying infrastructure, while EKS (Elastic Kubernetes Service) is a managed Kubernetes service that orchestrates and manages containerized applications. EKS allows for more granular control over nodes and networking, while Fargate abstracts those elements entirely, simplifying the deployment process. You can use Fargate as a compute option within EKS to avoid managing nodes. Learn also about other efficient ways to manage nodes here.
What is the difference between Kubernetes and Fargate?
Kubernetes is an open-source container orchestration platform that manages the deployment, scaling, and operation of application containers across clusters of hosts. Fargate, on the other hand, is a serverless compute engine for AWS that allows you to run containers without managing servers. Kubernetes can be used independently on any infrastructure, while Fargate is specific to AWS and works as a compute option for ECS and EKS.
What is AWS Fargate used for?
AWS Fargate is used to run containerized applications without the need to provision or manage EC2 instances. It is ideal for microservices, batch processing, event-driven applications, and any workload where you want to reduce infrastructure management. Fargate simplifies scaling and security by isolating each pod in its environment, providing a secure and highly available platform for container execution.
When should you use Fargate?
You should use Fargate when you want to:
- Avoid managing server infrastructure
- Deploy applications quickly without setting up VMs or EC2 instances
- Scale workloads automatically based on demand
- Enhance security with isolated pod environments
- Optimize costs for short-lived or burstable applications
For long-running, stateful workloads, managing EC2 instances may be more cost-effective.
What is the difference between Lambda and Fargate?
Both Lambda and Fargate are serverless compute services, but they serve different purposes:
- AWS Lambda: Designed for event-driven functions, it runs code in response to triggers without provisioning servers. It is ideal for short-lived tasks (limited to 15 minutes per execution).
- AWS Fargate: Designed for long-running applications and containerized workloads. It allows for custom runtimes, networking configurations, and greater resource control.
Lambda is best for lightweight, stateless operations, while Fargate is ideal for container-based applications that require more processing time and granular resource management.