A container is a piece of software that packages up code and all its dependencies, so the application runs quickly and reliably from one computing environment to another. When used correctly, containers can provide a robust and efficient way to deploy applications. A container isolates an application from its surroundings, for example, by providing an isolated environment on a computer for the application to run. By using containers, developers can focus on writing code without worrying about the systems it will run on. Containers also allow developers to get their hands on new technologies quickly and safely without installing them into their development environment. This approach enables true independence between applications and infrastructure and helps to keep things simple and reliable.
A container image is a self-contained package that contains everything an application needs to run. This includes the code, runtime, dependencies, and other necessary files. Container images are usually pre-packaged and can be pulled from a registry, such as Docker Hub. Once an image is pulled, a runtime like runC, containerd, or Cri-o can use to create and run one or more containers. These runtimes can run containers on a single host, but in practice, we would like to have a fault-tolerant and scalable solution. This can be achieved by building a single controller/management unit with multiple hosts connected together. Using a container image, we can confine the application code and all of its dependencies in a pre-defined format, making it easy to deploy and scale our applications. This controller unit is generally referred to as a container orchestrator.
As more and more businesses move to a microservices architecture, the need for packaging applications together with their dependencies has become increasingly important. This is because microservices are typically written in different programming languages, with dependencies, libraries, and environmental requirements. As a result, it is essential to package each microservice together with everything it needs to run successfully. There are various ways of doing this, but one of the most popular methods is using containers. Containers allow you to package an application with dependencies in a self-contained unit that can be easily deployed and run on any platform. This makes them ideal for microservices, as they can be easily moved between different environments and run on any type of infrastructure. Another advantage of using containers is that they allow you to isolate each microservice from the others, which can help to improve security and performance.
Container orchestration is the process of managing and coordinating the lifecycle of containerized applications. This includes tasks such as deployments, scaling, networking, storage, and security. By automating these tasks, container orchestration can help to improve the efficiency of DevOps teams and reduce the complexity of managing large-scale deployments. Commonly used container orchestration tools include Docker Compose, Kubernetes, and Apache Mesos. Each tool has its own strengths and weaknesses, so it's essential to select the right tool for your specific needs. With the right tool in place, container orchestration can help you deliver applications more quickly and efficiently.
In Development environments, you can run containers on a single host. This is an excellent way to test applications. But when you want to move to production, you need a container orchestrator to manage and coordinate the lifecycle of your containers. This will help you deploy and scale your applications more efficiently.
One of the benefits of container orchestration is the ability to automatically scale and manage a large number of containers. Container orchestration tools such as Docker Swarm and Kubernetes help to keep track of which containers are running on which host and they provide features such as load balancing and resource scheduling. This can be extremely helpful when deploying an extensive application with many different components.
Another benefit of container orchestration is that it can help to simplify the process of rolling out updates and changes. For example, if an update needs to be made to a database container, the orchestration tool can ensure that the updated container is deployed to all of the hosts that need it. This can save a lot of time and effort compared to manually updating each host individually.
Finally, container orchestration can also help to improve security by isolating containers from each other. This isolation ensures that if one container is compromised, the rest of the system will remain unaffected.
Overall, container orchestration provides a number of benefits that can be extremely helpful when deploying and managing large applications. By simplifying tasks such as scaling and updating, container orchestration can save time and improve efficiency. In addition, the isolation provided by container orchestration can enhance security by helping to prevent one compromised container from affecting the rest of the system.
Apart from this Container orchestrator helps you to address problems like,
Fault tolerance: When a host fails, the orchestrator ensures that the containers on that host are restarted on another healthy host.
Load balancing: The orchestrator ensures that the load is evenly distributed across all hosts in the system.
Scalability: The orchestrator can automatically scale up or down the number of containers based on demand.
Service discovery: The orchestrator can help you discover and connect to services that are running in the system.
On-demand scalability: The orchestrator can automatically scale up or down the number of containers based on demand.
Optimal resource usage: The orchestrator can help you use your resources more efficiently by using features like bin packing, resource quota limits, and others
Seamless updates/rollbacks without any downtime: The orchestrator can help you update your applications without any downtime.
Efficient use of hardware: The orchestrator can help you use your hardware more efficiently by making use of features like CPU and memory shares, disk quota limits, and others
Below is a list of a few container orchestration tools and services that are available today.
Amazon Elastic Container Service: Amazon Elastic Container Service (ECS) is a hosted service provided by Amazon Web Services (AWS) to run containers at scale on its infrastructure. ECS provides developers with all of the benefits of running containers on AWS, including seamless integration with other AWS services, Scalability, High Availability, and Security. In addition, ECS provides additional features that make it easy to deploy and manage containerized applications at scales, such as Integrated container orchestration, Task scheduling, Service discovery, and load balancing. As a result, ECS is an ideal solution for customers who want to run containers on AWS without the hassle of managing infrastructure.
Azure Container Instances: Azure Container Instance (ACI) is a basic container orchestration service provided by Microsoft Azure. ACI allows you to deploy and manage containers without the need to provision or manage any infrastructure. Simply create a container group with the desired number of containers, specify a CPU and memory limit, and set up networking. Then, use the Azure portal or the Azure CLI to deploy your application into the container group. ACI will automatically schedule containers across multiple Availability Zones in a region for high availability. For more advanced needs, you can also use Azure Container Instance with Azure Kubernetes Service (AKS). AKS provides additional features such as autoscaling, self-healing, load balancing, and more. By using ACI with AKS, you can get the benefits of both services while only paying for the resources you use.
Azure Service Fabric: Azure Service Fabric is an open-source container orchestrator provided by Microsoft Azure. Service Fabric enables developers to package, deploy, and manage their microservices and containers as a single application. Service Fabric has been designed to meet the needs of both developers and operations teams, making it easy to deploy and manage microservices in the cloud. Azure Service Fabric is a fully managed service, meaning that Microsoft takes care of all the underlying infrastructure, making it easy to get started with microservices without having to worry about provisioning or managing servers. In addition, Service Fabric provides built-in monitoring and logging, making it easy to detect and diagnose issues with your microservices.
Kubernetes: Kubernetes is an open-source orchestration tool that helps manage containerized workloads and services. Initially developed by Google, Kubernetes is now a part of the Cloud Native Computing Foundation (CNCF) project. Kubernetes provides a platform for automating deployment, scaling, and operations of application containers across clusters of hosts. It supports a range of container tools and runtimes, including Docker, rkt, and CRI-O. Kubernetes is designed to be extensible and pluggable, allowing developers to use the tools and frameworks they are already familiar with. In addition, Kubernetes has strong community support, with contributions from leading companies such as Red Hat, IBM, and Microsoft.
Marathon: Apache Mesos is a powerful tool for managing and running applications at scale. However, it can be challenging to run containers on Mesos due to the complex resource management that is required. Marathon is a framework that makes it easy to run containers on Mesos by simplifying the process of resource allocation and application management. As a result, Marathon provides an easy way to run containers at scale on Apache Mesos. In addition, Marathon integrates with other frameworks such as Hadoop and Spark, making it easy to run big data applications on Mesos. As a result, Marathon is an essential tool for any organization that is looking to run containers at scale on Apache Mesos.
Nomad: Nomad is a highly scalable, secure, and production-ready container and workload orchestrator that simplifies and automates deployments. Initially designed for simple applications and single-server deployments, Nomad is now used in production by some of the largest companies in the world to deploy complex applications across multiple regions. With Nomad, you can safely and efficiently manage your containers, microservices, and stateful applications. Nomad makes it easy to scale your applications and ensures that your deployment process is repeatable and consistent. In addition, Nomad integrates seamlessly with other HashiCorp products such as Consul and Vault, making it easy to deploy a complete infrastructure stack. Whether you're just getting started with containers or are looking for a more reliable and automated way to manage your deployments, Nomad is an essential tool for any infrastructure engineer.
Docker Swarm: Docker Engine is an open-source project that provides a set of tools for containerd, a low-level runtime container deployment service. These tools include container runtime, container orchestrator, container registry, and more. The Docker Engine project was started by Solomon Hykes in March 2013. The first public release was in July of that year. Version 1.0 was released in December 2014. The current version is 18.09.1, released on April 30th, 2019.
Docker Swarm is a tool provided by Docker, Inc., for Orchestrating and deploying applications within Containers. It is part of the Docker Engine project. The tool was first released in November 2017 as part of Docker Engine 17.11.
Anybody who has ever tried to maintain deployment for microservice applications knows that it can be a lot of work. The same is true of containerized applications. Although we can manually preserve a couple of containers or write scripts to manage the lifecycle of dozens of containers, orchestrators make things much easier for users, especially when it comes to managing hundreds and thousands of containers running on a global infrastructure. Orchestrators such as Kubernetes and Docker Swarm provide many features that are essential for running large-scale applications, such as container scheduling, self-healing, service discovery, and load balancing. In addition, they also allow users to roll out updates and scale applications with ease. As a result, orchestrators have become an essential tool for anybody looking to run large-scale containerized applications.
Most container orchestrators can:
Group hosts together while creating a cluster
Provision and deploy containers on the hosts in the cluster
Monitor the health of containers and hosts
Make sure that containers in a cluster can communicate with each other, regardless of the host they are deployed to.
Replace or restart containers that have failed
Schedule containers to run on specific hosts in the cluster depending on the resources that are available.
Bind containers and storage resources; for example, you can bind a container to a specific host where data is located for that container.
Group containers together: This makes it easier for clients to access the containers. The clients only need to know about the interface, not the individual containers.
Load balance requests across a group of containers.
Make sure you are using your resources in the most effective way possible. This means taking advantage of all the tools at your disposal and changing how you work to match the new world of containerized applications.
Make sure that you have policies in place to secure access to the applications running inside containers.
In addition to the features that are common to most container orchestrators, each one has its own unique set of features that sets it apart from the others.
When it comes to container orchestration, there are two main deployment options: on-premises and cloud. Each option has its own benefits and drawbacks that you should consider before making a decision.
On-premises deployments can offer better performance, security, and compliance than cloud deployments. However, they are typically more expensive and less flexible.
Cloud deployments can offer better Scalability and flexibility than on-premises deployments. However, they are typically less secure and have less control over the environment.
There are many factors to consider when deciding whether to deploy in the cloud or on-premises. Some of these factors include:
Cost: Because you must purchase and maintain the hardware and software yourself, on-premises installations are often more expensive than cloud deployments. For on-premises data centers, maintenance is challenging compared to the public cloud.
performance: Because data does not travel over the internet, on-premises deployments can provide more excellent performance than cloud deployments.
security: Because you have more control over who has access to the data, on-premises installations can provide better security than cloud deployments. However, cloud providers are following suit and introducing more and more security mechanisms, ensuring that the cloud is also safe.
compliance: Because you have more control over who has access to the data and how it is utilized, on-premises installations can provide better compliance than cloud deployments.
flexibility: Because you have more control over the environment, on-premises installations can offer more flexibility than cloud deployments.
Scalability: In comparison to an on-premises data center, scaling in the cloud is simple. Cloud offers well-defined protocols for scaling up and down infrastructure on demand, but we have to install extra hardware as needed in on-premises data centers.