What Is Container Orchestration?
Container orchestration is the automated process of organizing the functions of modular, containerized components that create the infrastructure of an application. Container orchestration is particularly critical to managing the dynamic microservice architectures of enterprise-grade applications.
How Does Container Orchestration Work?
Container orchestration encompasses a variety of methodologies depending on the container orchestration tool used. Generally, container orchestration tools communicate with a user-created YAML or JSON file that describes the configuration of the application.
The configuration file directs the container orchestration tool on how to retrieve container images, how to create a network between containers, and where to store log data or mount storage volumes.
Container orchestration tools also manage deployment scheduling of containers into clusters and can automatically identify the most appropriate host. The best host for each application container may be defined by data including user-defined guidelines, labels, or metadata.
Once a host is assigned, the orchestration tool uses predefined specifications to manage the container throughout its lifecycle.
Essentially, container orchestration tools automate and manage the many moving pieces associated with microservices within a large application, including scheduling and organizing the following tasks:
Configuration and scheduling containers
Provisioning and deployment of containers
Scaling containers to balance workloads
Allocating container resources
Load balancing or traffic routing
Health monitoring for containers and hosts
Shifting containers due to an unavailable host or lack of resources
How to Choose From Container Orchestration Tools
Choosing the right container orchestration tool for your organization involves a variety of factors including the number of containers in your container deployment, the technical experience of your system administrator or IT team, or the specific needs of your containerized application. The three most widely-used frameworks for container management are open-source, and there are benefits and challenges associated with each containerization platform.
Kubernetes Container Orchestration
Kubernetes is a popular choice among large enterprises that emphasize a DevOps approach and is supported by cloud services including AWS, IBM, Microsoft, Intel, and Cisco.
Kubernetes is widely appreciated for its motility. Workloads can be moved without redefining the application or infrastructure since its starting point is the cluster, which increases its portability.
Kubernetes creates an abstract hardware layer that allows DevOps teams to deliver a Platform-as-a-Service (PaaS), and makes it easier to request additional resources to scale an application without the need for more physical machines.
Managing Kubernetes can be challenging due to its vastness. Supplemental technologies and services are often necessary to deliver an end-to-end solution, and deciphering which components are appropriate for your implementation can require a significant amount of research.
Security is another challenge, especially to large enterprises. If a single Kubernetes cluster is compromised by a hacker, other clusters may become vulnerable as well.
Also, organizations who deploy containers to an on-premises server versus a public cloud provider often cite storage as a cause for concern. Monitoring and logging are listed as the primary challenges when deploying solely to the public cloud.
Docker Container Orchestration
The fully-integrated Docker container orchestration tool is known as Docker Swarm and provides a simpler path to container deployment. For organizations that still want the option of using Kubernetes’ more extensive features, the Docker Enterprise Edition offers a bundle of both frameworks and their functions complement each other.
The Docker container orchestration tool ships with Docker and requires one of the easiest configurations. If you’re operating on multiple cloud platforms or if you’re new to container orchestration, Docker Swarm is an appealing orchestration platform due to ease of use and a low learning curve. Docker is an ideal choice for smaller deployments.
Docker is also well-known for providing and maintaining updated documentation, which is helpful if you encounter an issue or are in need of information.
One of the greatest disadvantages of Docker Swarm is the lack of an option to connect containers to storage. Improvising on the host and/or the manual configuration necessary to accommodate data volumes makes it a less user-friendly option when it comes to storage-related issues.
Another obstacle for many is that Docker Swarm supports Windows and Mac OS X, but uses virtual machines to run on non-Linux platforms. Consequently, if an application is designed for a Windows-based docker container, it isn’t compatible with Linux, unlike Kubernetes service which is not operating system-specific.
Mesos Container Orchestration
Apache Mesos was originally developed at UC Berkeley and was adopted for use by large enterprises including Uber, Yelp, AirBnb, Twitter, and Paypal. Mesos has a modular architecture and can manage a broad range of workloads due to “application-aware” scheduling.
Mesos has many advantages, including its lightweight interface and support of a number of programming languages. It also simplifies resource allocation by combining abstract data resources into a single pool without affecting performance.
The greatest benefit of Mesos is its inherent flexibility and scalability; you can easily scale an application or infrastructure to tens of thousands of nodes.
Mesos is not actually a container orchestration tool -- it simply provides cluster management. Container orchestration is one of the many workloads that can run on top of Mesos due to its Marathon framework, which offers container orchestration as a feature.
One of the most significant obstacles to implementing Mesos is its high learning curve; it’s likely to require specialization and technical expertise. While it’s an appropriate choice for large-scale enterprises, it may be overkill for smaller organizations with limited tech resources.