Kubernetes vs AWS ECS
Container technology has been around since the late 1970s, but Docker was the first to make a name for itself in 2013. Since then, the use of containers has become quite common and altered the DevOps environment as well as the way we create, ship, and operate distributed applications. It’s no coincidence that Docker and container use is increasing at the same time.
Container orchestration applications are useful and effective tools for designing, handling, and upgrading various containers across multiple hosts in a coordinated manner. Furthermore, orchestration enables you to exchange data between resources and perform activities in a synchronous manner. To make an application highly accessible in your production environment, you can run several instances of each service across several servers. The better we simplify orchestration, the more we can dig into the application and break it down into smaller microservices, which also raises the question – which tool or framework to use for container orchestration?
In this article, we will compare the two most popular tools used widely for container orchestration or management. These are AWS Elastic Container Service and Kubernetes.
Who will win between AWS Elastic Container Services and Kubernetes? These two cluster management systems assist microservice applications in handling, installing, autoscaling, and networking their containers.
Kubernetes is a widely-used container management service. This tool, which was developed by Google and is stored in the Cloud, also runs on Docker. It’s worth noting that Kubernetes has a quite vast and active community.
Amazon ECS, on the other hand, is a container orchestration platform that allows apps to scale up easily. As demand grows, it tends to build more containers to operate the application processes smoothly.
Both tools have their own set of advantages and disadvantages when it comes to implementing them, which is why it’s important to compare them before you choose one that can meet your organization’s needs. Even with Kubernetes running on Cloud such as Amazon Kubernetes service, etc., managing it in its entirety would take about 20% more time. In the case of Amazon ECS, which is a free service with the exception of the expenses associated with the instance allocated to the service.
Container adoption is growing, which means there are a lot of tough decisions to make. We need to decide which orchestration tool is best for our needs, as well as how we can control the framework. Although Docker is the industry standard for container runtimes, container orchestration tools come in a range of flavors. AWS ECS and CNCF’s Kubernetes are the industry leaders. According to a poll, 50 percent of companies use Kubernetes as their container orchestration tool, compared to just 23 percent that use ECS.
Since container orchestration is highly reliant on your infrastructure, it’s critical to consider how these technologies work for your existing cloud provider or on-premise solution. Do you need something more diverse or are you able to invest into one cloud provider’s entire toolchain?
Due to its configurability, stability, and strong community, Kubernetes is emerging as the new leader in the container orchestration domain, surpassing Docker Swarm. Kubernetes, a Google open-source initiative, integrates seamlessly with the entire Google Cloud Platform. It also operates with virtually every infrastructure.
Amazon’s proprietary tool, Elastic Container Service (ECS), is planned to operate in combination with other AWS systems. As a result, AWS-centric technologies such as storage, load balancing, and monitoring can be conveniently integrated into the service. ECS is definitely not a good option if you’re using a cloud service other than Amazon, even if you’re running the workload on-premise.
However, from a bird’s eye perspective, both of them are container orchestration technologies that enable you to develop and build containerized software inside a manageable fleet of servers in a fast, efficient, and highly scalable manner. The question still remains the same, which one to choose and why? In this article, we will discuss a few features and shortcomings of both these tools which will probably help you to decide which one to go for.
“Kubernetes is a free-to-use open-source framework for automating the implementation, scaling, and maintenance of containerized applications,” according to the Kubernetes website. Google developed Kubernetes based on their experience of operating containers in production using Borg, their internal cluster management solution. A Kubernetes cluster is built using a variety of different modules. The workloads are placed by the master nodes either in user pods of the worker nodes or on the master nodes themselves. Some other components associated with the Kubernetes architecture are –
- etcd – It allows you to store data related to architecture configuration that the master nodes can access through the API Server using an HTTP protocol or a JSON API.
- Scheduler – It is responsible for placing the container workload onto the right node.
- Controller Manager – It makes sure that the intended state of the cluster aligns with the present state which can be done by performing scale up or down.
- API Server – This can be used to manage the master node. It allows communication between the different components.
- Kubelet – It inputs configurations and specifications related to the pods from the API server and then manages the running pods.
Let’s discuss some other common terminologies that are frequently used in Kubernetes.
Containers are deployed and scheduled by Kubernetes in pods. Containers in a pod share resources like namespaces in the kernel, file systems of the nodes, and the IP address since they operate on the same node. The deployments are components that can be used to generate and control a cluster of pods. They may be used in conjunction with a service tier to allow horizontal scaling or to deliver the services on-demand. Endpoints that can be labeled by their names, attached to the pods through the label selectors are referred to as services. The service would round-robin requests between pods automatically. For the cluster, Kubernetes can establish a DNS server that can monitor for different resources and enables them to be labeled by their names. Container workloads have an “external face” in the form of services. Objects are given labels, which are key-value pairs. They can be used to scan and modify a group of objects at once.
The implementation of Kubernetes is the most complicated of the two, but it can be made easier with the right software. Kubeadm is a good option for interacting with current orchestration schemes or bare-metal environments. Helm is a well-known platform for deploying and handling Kubernetes software. One of Kube’s greatest strengths is that you have full control over its setup, and more traditional platforms have lots of documentation to help you set it up the way you like. Furthermore, if you run into any difficulties, Kubernetes has a wide group of users and support to turn to for assistance on Git, StackOverflow, and Slack.
Benefits of Kubernetes
Let’s discuss a few benefits that Kubernetes brings along with it.
- Without needing to re-architect the container orchestration plan, it can be used on-premise or in the cloud. The platform is completely open-source and even can be re-used without the need for traditional software licenses. Kubernetes clusters can also operate through public and private clouds, offering a layer of virtualization between public and private infrastructure.
- If you have critical revenue-generating software, Kubernetes is an excellent way to fulfill high availability criteria while maintaining reliability and scalability. Kubernetes gives you fine-grained control of how the workloads grow. When you need to upgrade to a more efficient platform, you can escape vendor lock-in with ECS or several other container services.
- Kubernetes was created to address framework and infrastructure availability, making it important when deploying containers in development. It protects the containerized application from failures by monitoring the health of nodes and containers regularly. It also has self-healing and auto-replacement capabilities. Kubernetes keeps you protected whether a container or pod fails due to a mistake. Requests are routed to the necessary containers via traffic routing. It also has built-in load balancers that spread the workload through several pods, allowing you to easily rebalance resources in response to outages, high or accidental traffic, and processing in batches.
- Kubernetes is well-known for allowing effective use of infrastructure services and for having a variety of useful scaling functions. It introduces horizontal scaling that can be invoked right onto the server level independently. New servers can be quickly installed or deleted. You may use auto-scaling to adjust the number of running containers depending on CPU usage or other measurements offered by the application. A command or the GUI may be used to manually scale the number of operating containers. The replication controller ensures that your cluster is running with a defined number of identical pods. The Replication Controller halts the additional pods if there are too many. If there aren’t plenty, it will start some more pods.
- One of the most significant advantages of containerization is the potential to accelerate the development, testing, and release of applications. It’s designed for deployment and comes with several helpful features. Do you want to upgrade your app’s configuration or release a new version? It will take care of it without causing any downtime, while still checking the health of the containers during the deployment. In the event of a loss, it reverts to the prior condition.
- Canary deployments allow you to test a new deployment in development alongside an older version prior to scaling up the new deployment while concurrently scaling down the older one. Kubernetes is compatible with a wide range of computer languages and platforms, including Java, Go, .Net, and many others. Also, it has a great deal of support from the developer community and is responsible for managing additional computer languages and platforms. Kubernetes should be able to run any application that can run in a container.
- It’s crucial that all the services communicate with one another in a predictable manner. However, since containers in Kubernetes are generated and discarded regularly, a given service will not be accessible at a specific location forever. To keep track of a container’s location, some sort of service register had to be developed or adapted to the application logic in the past. Kubernetes has a built-in service concept that organizes the Pods and makes service exploration easier. Kubernetes can allocate IP addresses for each Pod, a DNS name to every other set of Pods, and then balance a load of traffic for each set of Pods. This allows the discovery of services to be abstracted from containers.
- All the available Pods can connect and communicate among themselves by default. Networking rules can be implemented declaratively by a cluster administrator, and these policies can limit access to unique Pods or Namespaces. Fundamental network policy constraints can be imposed by merely specifying the names of the Pods or Namespaces on which you choose to grant egress and ingress capabilities.
- Kubernetes is a vibrant community with a diverse range of open-source plugins that has the sponsorship of large businesses and organizations such as the CNCF. Kubernetes is the network of choice for new software infrastructure, with thousands of developers and even major companies contributing. This suggests that the group is not only constantly communicating, but also creating features to make it easier to solve modern problems.
Exploring AWS Elastic Container Service
ECS is Amazon Web Services’ Docker-compatible solution for container orchestration. It enables you to run docker containers on Amazon EC2 instances and scale them. Although Docker has won over users for its ease of use, Amazon ECS is a more difficult tool because it requires you to learn a different framework. Let’s discuss some of the most popular services that are most commonly used along with ECS.
- Elastic Load Balancers – These are used to balance traffic among all the containers. You can either use the application or the classic load balancers.
- EBS or Elastic Block Store – It offers block storage which is persistent and used for tasks in ECS or workloads in containers.
- Virtual Private Cloud – You can have more than one subnet in a VPC and an ECS cluster should run inside a VPC.
- CloudWatch – It is used to collect metrics from the Elastic Containers to analyze the performance of containers deployed as services in Amazon ECS. This will also help you to decide whether to scale up or down.
- CloudTrail – It allows you to log all the calls made to the ECS APIs.
There are a ton of components that allows administrators to work with ECS and build clusters, manage them, and work with tasks and services. Let’s discuss a few of them.
- Many EC2 container instances will create a container environment. With dozens or hundreds of containers, it’s crucial to keep track of instances that are available to satisfy new requests based on processor, memory, load balancing, and other variables. The state engine is responsible for keeping track of available hosts, operating containers, and other cluster manager features.
- Schedulers are elements that use state engine knowledge to position containers in the most suitable EC2 instances. For jobs that run for a limited amount of time, the batch work scheduler is used. For long-running apps, the service scheduler is used. It will add new tasks to an ELB automatically.
- Inside an AWS field, a cluster is a logical boundary for a collection of EC2 container instances. A cluster can cover several availability zones (AZs) and can be dynamically scaled up and down. In a dev/test area, there could be two clusters: one for production and one for testing.
- A task is a discrete piece of work. Containers that need to be clustered are defined in JSON task descriptions. While most tasks only have one container, they may also have multiple containers.
- Services are components that determine the number of tasks that should be running in a cluster. You may use the service scheduler to position tasks and communicate with resources using their API.
It’s worth noting that ECS only handles ECS container workloads, which results in vendor lock-in. Containers cannot run on networks other than Elastic Cloud Containers, such as hardware infrastructure or different cloud providers like GCP, Digital Ocean, etc. The ability to collaborate with all other AWS services, such as Load Balancers, EBS, CloudTrail, and CloudWatch is, of course, a plus.
Benefits of using AWS ECS
Let’s discuss a few benefits that Amazon ECS brings along with it.
- The conventional ECS, which is operated by Amazon EC2 Compute, was released in 2015 as a way of running Docker containers on the cloud with ease. It gives you underlying power over the containers’ EC2 compute options. Thanks to the simplicity of AWS ECS, it lets you decide on which elastic container instances or services you want to run the workloads. It also links you to other AWS applications for tracking and recording EC2 instance activity.
- In contrast, Fargate Elastic Container Service was launched back in 2017 with the purpose of figuring out a way that would allow users to run containers without the need to handle the associated EC2 Compute. Fargate determines the required CPU and other parameters by itself. If you want to start a workload quickly without estimating the associated compute solutions, Fargate is a decent choice.
- ECS is a great option in case you want to run more petite workloads that aren’t supposed to upscale or downscale dramatically. The role descriptions are simpler and easier to recall.
- If the application is made up of just a few microservices that function somewhat separately and the overall design isn’t too complicated, ECS is a good place to start.
- Kubernetes has a steep learning curve, which is one of the key reasons why hosted Kubernetes products are more common than more conventional KOPS and Kubeadm variants. Furthermore, with AWS Fargate, you don’t even have to manage the underlying servers or EC2 instances that run your containers. AWS takes care of almost everything.
- AWS CloudWatch tracking and logging were seamlessly combined with ECS. If you’re running container workloads on ECS, there’s no need to do any extra work to get insight into them.
Kubernetes vs AWS ECS: Head to Head Comparison
|Load Balancing||A service exposes pods that could be used as a load balancer inside the cluster. For load balancing, an ingress resource is normally used.||Inside the cluster, ELB has a CNAME that can be used. This CNAME can work as a front-facing fixable FQDN for several purposes. For ELB, there are two types of utility load balancers: Classic and Application.|
|Auto-Scaling||Deployments are used to describe auto-scaling using a basic number-of-pods objective. Resource metrics-based auto-scaling is also enabled. CPU and memory consumption, requests, etc. are all examples of resource metrics.||ECS resources can be auto-scaled up or down using CloudWatch alerts based on power, memory, and personalized metrics.|
|Rolling upgrades and Rollbacks||Both “rolling-update” and “recreate” methods are assisted by a deployment.
You may have to define a threshold on the number of pods in this case.
|The “minimumHealthyPercent” along with the “maximumPercent” criteria are used to support rolling updates. Blue-green upgrades whose purpose is to incorporate an entirely fresh set of containers along with the original one can be done with the same parameters.|
|Application Deployment||A mixture of pods, deployments, and resources may be used to deploy applications. The atomic unit of a deployment is a pod, which is a set of clustered containers. Many nodes may be used to duplicate a deployment. Service is the container workloads’ “external face,” integrating with the DNS to round-robin the service packets. Incoming request load balancing is provided.||Tasks, which are Docker clusters operating on EC2 instances, can be used to deploy tasks. In a JSON template, task descriptions define the container image, CPU, memory, and permanent storage. Group of tasks that use these descriptions make up a cluster. Containers are automatically positioned around computing nodes in a cluster, which may cover several AZs, by schedulers. You can define tasks and ELBs to build services.|
|Availability||Deployments enable pods to be scattered through nodes for high availability, allowing infrastructure or service failures to be tolerated. Safe pods are detected and removed by load-balanced services. Kubernetes allows you to ensure that your application is highly available. This means that in case of a failure, it provides you with backup so that the entire system does not fail at once. For queries from kubectl and clients, several master nodes and worker nodes could be load balanced. API Servers can be reused and etcd can be grouped.||Tasks made up of one or more containers are placed on EC2 container instances by schedulers. To size, tasks may be manually increased or reduced. Traffic can be distributed among safe containers using elastic load balancers. Amazon is responsible for the high availability of ECS control aircraft. ELB can load-balance requests through multiple tasks.|
|Networking||The networking paradigm is a flat network, which allows all pods to connect with each other. Network policies define how pods interact with one another. In most cases, the flat network is configured as an overlay.||ECS can be used in a VPC, which can have several subnets in different AZs. AWS software cannot be used to limit communication within a subnet.|
Advantages of using Kubernetes over AWS ECS
It’s possible to use Kubernetes on the cloud or hardware infrastructures. On-premises SANs and public clouds are only a handful of the hosting solutions available. It’s focused on Google’s deep familiarity with Linux containers. It may be used on a larger scale within organizations. Kubernetes is now supported by Google (GKE) and RedHat (RHAT) business offerings (OpenShift). Among container orchestration software, it has the largest group; over 1200 supporters with over 50,000 commits.
Vendor lock-in is an issue with AWS ECS. Only Amazon can deploy containers, and ECS can only handle containers it has created. Amazon is the only supplier of external storage, like Amazon EBS. Outside of Amazon, ECS is not commercially available for deployment. Many of the ECS code isn’t open to the public. Blox, a platform that lets users create custom schedulers, is one of the open-source components of ECS. It only has around 200 commits and 15 developers, most of whom are Amazon workers.
Challenges with Kubernetes
Knowing the Kubernetes landscape is important for getting started when an end-to-end approach involves the use of a range of technologies and resources. However, the status of each supplementary technology differs greatly. Some alternatives, for example, date back to the days when Unix was king, while others are less than a year old and have poor commercial penetration and funding. You must consider how each part blends into a broader solution in addition to determining which ones you can comfortably use in the implementation. While there is a wealth of knowledge and documents available on this subject, it is dispersed and difficult to distill.
As a consequence, determining the right option for a specific work is challenging. Even once you’ve decided on the technologies, you’ll need a strategy for delivering them as a service and managing them continually.
The challenges don’t stop there. Although finding advice on how to handle a project’s life cycle is helpful but difficult, it doesn’t overcome the uncertainty that occurs when deciding between a Kubernetes product and a Kubernetes community project. The benefit of an open-source tool like Kubernetes is that developers can build and distribute new software easily. The same profit, on the other hand, might muddy the waters. Although special interest groups may build features that are embedded into the core of Kubernetes, independent projects remain beyond the core.
Much of this perplexity is exacerbated by the difficulty of delivering remedies. Kubernetes is a sophisticated tool in and of itself. Organizations, on the other hand, want to provide more complex solutions, such as decentralized data stores-as-a-service. Combining and handling both of these services will add to the difficulties. Not only you must be a specialist in Kubernetes, but also you should be knowledgeable in everything you’ll provide as part of an end-to-end operation.
Having Kubernetes up and running is one thing while maintaining it is another task. Since what you have with Kubernetes is Kubernetes, Kubernetes maintenance is mostly manual. Since the platform doesn’t have anything to run it, you’ll have to find out how to get resources to Kubernetes, which isn’t simple. When it comes to meeting business needs, Kubernetes must be security-hardened and integrated with the current infrastructure. To successfully run and scale Kubernetes, you’ll need the right skills, experience, procedures, and resources, in addition to managing updates, patches, and other infrastructure-specific management activities.
It is quite evident that Kubernetes is leading the race among tools that facilitate container management. It has proved itself as the norm for container management with businesses around the world participating heavily in its adoption.
Although Amazon ECS is a decent choice, it comes up short in several areas. Kubernetes implementation is not only painless with the right toolchain, but it’s actually advantageous in the long term because it makes you fully cloud-native.
Both ECS and Kubernetes are container management systems that are fast and scalable. ECS is an Amazon AWS service that works well with other AWS services including Route 53, EBS, IAM, and ELB. In certain ways, such integration allows you to install and run the codes more easily and quickly. It does have one disadvantage though: if you start using ECS, you must use Amazon services for everything.
Kubernetes, on the other hand, is much more than a container management system. It offers you a professionally organized environment for deploying, operating, handling, and orchestrating containers. Kubernetes has the benefit of being able to run on a combination of public and private clouds as well as on-premises. Since Kubernetes can be deployed on EC2 instances and utilize S3 and Elastic Block Storages for volumes, AWS users can start using Kubernetes on AWS, with the option of switching Kubernetes-managed applications to some other cloud service or an on-premises architecture.
At last, we hope that this article will help you to pick the right container orchestration platform for you.