Container Orchestration: k8s vs. AWS ECS

As DevOps engineers, you must have heard two of the popular container orchestration tools – Kubernetes and AWS Elastic Container Service (ECS). Here are some quick notes about the key components of k8s and ECS

Kubernetes, or K8s for short, is the open-source container orchestration. Its rich feature set and flexibility have made it popular among DevOps professionals.

1. Master Node: Think of it as the control center, making decisions about where and how to run containers.
2. Worker Nodes: These are the workhorses, where containers find their home.
3. Pods: These are the smallest deployable units in Kubernetes. They can host one or more containers, sharing resources like networking and storage.
4. ReplicaSet,Deployment: It ensures a specified number of pod replicas are always running. No more counting containers manually! RS is the best friend of Deployment
5. Service: This clever component abstracts networking, allowing us to access sets of pods, offering load balancing and service discovery.
6. Ingress: It takes care of external access to our services
7. ConfigMap and Secret: These components store configuration data securely, away from our application code.
8. Namespace: For those looking to achieve multi-tenancy and resource isolation, namespaces are a blessing.
9. Persistent Volumes: They let us store data safely, even when our pods restart.

AWS Elastic Container Service is Amazon's answer to container orchestration. As a managed service, it simplifies container management.

1. Cluster: Like Kubernetes clusters, these group container instances logically.
2. Task Definition: It's where we specify how our containers should run together, including which Docker images to use and resource allocations.
3. Service: Just like Kubernetes, ECS ensures a set number of tasks are always running.
4. Container Instances: These are EC2 instances running the ECS container agent.
5. Load Balancer: It's the traffic manager, distributing incoming requests.
6. Auto Scaling: This automated feature keeps the number of tasks in check based on metrics like CPU utilization.
7. Task Placement Strategies: These rules determine how tasks are placed on container instances, optimizing resource usage.
8. Volumes: permant data storage, AWS provide EFS as the persisnt volume option

Learning Curve: Kubernetes is more complex and requires more effort to master (my personal experience) :).

Flexibility: k8s has extensive feature set and adaptability for different use cases. You can use EKS on AWS and can be much easier (in genenral) to migrate to AKS on Azure