A Deep Dive Into Cloud-Agnostic Container Deployments

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A Deep Dive Into Cloud-Agnostic Container Deployments

From our recently-released Containers Guide, take a look at this comparison of Docker and Kubernetes as cloud-agnostic container orchestrators.

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This article is featured in the new DZone Guide to Containers: Development and Management. Get your free copy for more insightful articles, industry statistics, and more! 

Container technology has been evolving from its originally primitive perspective in the late 1970s to the Docker era which debuted in 2013 and now, it's safe to say we're now firmly ensconced in the age of Kubernetes. Since the deployment method's inception — and Docker popularizing the practice — containers have grown in renown and have dramatically enhanced the development landscape. Their usage has drastically improved the manners in which developers can implement distributed applications.

The focus on consistent container deployments across various platforms has made them increasingly embraced by enterprises of all shapes and sizes — especially as the latest in container orchestration's support efforts assist even the greenest developers through development to production and have led to more containers being deployed and managed than ever before. The urge for improved control has attracted various software options as answers to proper container orchestration.

Kubernetes and Docker Swarm remain the two major tools on the market and are used by prominent internet companies for container orchestration. Other players on the scene are Amazon  Elastic Container Service (Amazon ECS), Shippable, Apache Mesos, Marathon, and Azure Container Service (AKS), to name a few.

Kubernetes vs. Docker Swarm: Most Effective Deployment Method

Container orchestration refers to the automated organization, linkage, and management of software containers. These concepts are conventional for most of the tools mentioned above. This article aims to deep dive into a comparison between the two dominating players. Below are the features availed by both Kubernetes and Docker Swarm.

  • Clustering: For synchronized computing ability across multiple machines.

  • High availability: Run code all at once in various locations.

  • Fault tolerance: If a container fails, it can be relaunched automatically.

  • Secret management: Share secrets safely between different hosts.

Advantages of Docker Swarm

There are fundamental differences in the way Kubernetes and Docker swarm operate, though, which pose advantages for one platform over the other for different end users. Here are some pros of Docker Swarm vs. Kubernetes.

Easy, Fast Setup

It is easy to install and also configure Docker Swarm orchestration. You only need to deploy a node and request it to join a cluster. A swarm allows a node to join clusters either as a manager or a worker, thus providing more flexibility. For an idea of how simple this is, check out Creating a High-Availability Docker Swarm on AWS.

Works With Existing Docker APIs

The Swarm API derives most of its functionality from Docker itself. Kubernetes needs its own API, client, and YAML, which are all different from Docker's standards.

Load Balancing

Docker Swarm provides automated load balancing via any node.  In any network that permits connection of any container through any node, all containers within a cluster can join.

Sharing of Data Volumes

Docker Swarm simplifies local data volume sharing. Volumes (directories) can be generated individually or together with the containers, then divided among multiple containers.

Disadvantages of Docker Swarm

Limited Functionality

Docker Swarm performance revolves around the provisions of the Docker API. If the Docker API lacks a specific operation, it can't use Swarm.

Limited Fault Tolerance

Docker Swarm has finite fault resistance.

No Built-In Scalability

At the time of writing, scaling containers and the support infrastructure is achievable but very tricky to do.

Unstable Networking

Docker's underlying raft network has shown many signs of instability and the result is that many production environments are having issues. There's flaky networking underpinning everything.

Advantages of Kubernetes

Simple Service Assembly with Pods

Kubernetes Designates Container Pods as Services to Permit the Concept of Load Balancing. You Can Achieve Each Function by using a set of pods and policies to setup load balancing. This configuration does not use IP addresses.

High Service Availability Retention

Kubernetes monitors the system and clusters progressively to upkeep service health and maintains its availability.

High Scalability

Gain the ability to build clusters across different location and providers, with built-in auto-scaling at the cloud and container levels.

Highly Extensible

Kubernetes was designed to be extremely flexible and support many plugins. This has allowed for very large community growth, and as such, a massive selection of tools and plugins.

Here's a small curated collection of some of the more popular tools for 2018.

  • Elevated data sharing: Kubernetes allows containers to share data within pods. It also allows external data volume managers to exchange data between pods.

  • Cloud integration: Kubernetes is highly extensible and its cloud integrations are awesome. A load balancer service will deploy the matching managed service in GCP, AWS, or Azure. Many other platforms — Docker included — have also added Kubernetes support.

Disadvantages of  Kubernetes

Potentially Overwhelming to Install and Configure Manually

Kubernetes necessitates a set of manual configurations to tie its components to the Docker engine. It comes with unique installations for every operating system. Before installation, Kubernetes requires information like node IP addresses, their roles, and numbers. There are many tools available to simplify the install and config process, though.

A New Level of Complex

Kubernetes is considered relatively white-box, i.e. you can get a lot more out of it, but you really need to have a deep understanding of what makes Kubernetes tick to achieve this. The platform is not designed for novices and the faint of heart to navigate.

Throughout the pros and cons of Docker Swarm, you can note that Swarm's focus is on the ease of adoption and integration with Docker. Kubernetes, on the other hand, stands open and flexible. The K8s platform delivers top support for highly complex demands. This versatility is behind the preference for Kubernetes by many high-profile internet companies.

Three Major Kubernetes Object Management Techniques

There are three Kubernetes deployment techniques to make your work plan faster and smoother. Among the three, you should choose only one method at a time to manage a Kubernetes object. Use of multiple techniques can cause unstable performance. Here are the three types of Kubernetes object management techniques that you can use.

Imperative Commands

These are "easier-to-use" commands, and they're simple to recall over and over again. The commands deliver a one-step change to a cluster, and you work directly on live objects. Type operations into the kubectl command line as flags or arguments. This technique does not provide any history of earlier configuration, though. Hence, previous commands can't be used in change review processes. Imperative commands are ideally applicable in development projects.

Imperative Object Configuration

With imperative object configuration, the kubectl commands mainly focus on an operation like create, replace, and others. It also defines an optional flag and at least one file name. Alongside the file name, it gives a complete definition of an object in YAML or JSON format. This technique is preferred by many developers, as it allows commands storage in a source control system.

It is also useful in change review processes, as commands can be integrated. Furthermore, configurations can serve as templates for new objects.

Just as a captain steers a ship, Helm offers greater control for Kubernetes clusters. It can be thought of as a package manager that offers greater flexibility in the creation of Kubernetes definition YAMLs through a templating language and structure.

Declarative Objects Configuration

Declarative objects configuration allows you to operate on object setup files stored locally. However, you can't specify the operations to carry on the files. This mandate rests with kubectl, and it can automatically create, update, or delete operations per object. The kubectl functionality enables working directories where you will need different processes for different objects.

Leverage Kubernetes Performance with Helm Charts

What Are Helm Charts?

Just as a captain steers a ship, Helm offers greater control for Kubernetes clusters. It can be thought of as a package manager that offers greater flexibility in the creation of Kubernetes definition YAMLs through a templating language and structure. There are both client-side and the server-side segments of Helm for Kubernetes (Helm is the package manager and the Tiller is the in-cluster component that works with the K8s API server). The client collaborates with the server to effect changes to the Kubernetes cluster.

In a standard Helm sequence, the user initiates the Helm install command. The Tiller server responds by setting up the relevant install package into the Kubernetes cluster. Such packages are known as charts, and they offer a convenient approach to distribute and install packages.

Helm fulfills the need to efficiently and reliably provision Kubernetes orchestration without all the individual configuration involved. Charts are the software equivalent of development templates. Therefore, you can quickly achieve installation, updates, and removal without any fuss. Helm charts will even help you override the Kubernetes disadvantages as addressed earlier. Your team can concentrate its focus on developing applications and improving productivity instead of deploying dev-test environments. Helm takes care of all of that for you.

In addition to these benefits, your team doesn't need to preserve service tickets during Kubernetes deployments and you also eliminate the complexity of maintaining an App Catalogue too. GitHub/Kubernetes/Helm has a huge repository of communal charts in storage to be used in a matter of clicks. Among the most reliable Helm charts you could consider are ones for MySQL and MariaDB, MongoDB, and WordPress.


In conclusion, if containers are discouraging you at all, use Kubernetes to scale them. Kubernetes is highly extensible and comes with a lot of plugins to support your productivity. Furthermore, deploy all your containers and clusters using Helm and

Helm charts to further boost efficiency.

This article is featured in the new DZone Guide to Containers: Development and Management. Get your free copy for more insightful articles, industry statistics, and more! 

cloud, docker, docker swarm, helm, kubernetes, pros and con

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