The way we write, ship, and maintain software today has evolved drastically in the last few years. How we consume underlying infrastructure to run our software has matured significantly, in that we have seen a transition from bare metal to virtual machines to containers to micro-VMs.
The rise in the adoption of microservices has certainly paved the way for containers to be the primary approach for organizations to package and ship their applications. Amid this evolution, we have seen Docker become almost synonymous with containers and Kubernetes emerging as the gold standard of orchestrating those containers. Some of the primary benefits of this transition include fault isolation, resource utilization, and scaling of workloads, all of which have a direct impact on the business.
In this post, we’ll get into the what and why of container orchestration. We’ll also take a look at some of the leading tools out there and stack them up against each other with the aim to help you choose the right tool for the job.
Last year, we provided a list of Kubernetes tools that proved so popular we have decided to curate another list of some useful additions for working with the platform—among which are many tools that we personally use here at Caylent. Check out the original tools list here in case you missed it.
According to a recent survey done by Stackrox, the dominance Kubernetes enjoys in the market continues to be reinforced, with 86% of respondents using it for container orchestration.
And as you can see below, more and more companies are jumping into containerization for their apps. If you’re among them, here are some tools to aid you going forward as Kubernetes continues its rapid growth.
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What’s the difference between popular Container-Centric OS choices, Google’s Container-Optimized OS, and AWS’s Bottlerocket? The concepts underlying containers have been around for many years. Container technologies like Docker, Kubernetes, and an entire ecosystem of products, as well as best practices, have emerged in the last few years. This has enabled different kinds of applications to be containerized.
Web service providers like Amazon AWS and Google are giving a further boost to container innovation, for enterprises to adopt and use containers at scale. This will help them to reap the benefits containers bring, including increased portability and greater efficiency.
Linux-based OS, AWS Bottlerocket is a new option, designed for running containers on virtual machines (VMs) or bare-metal hosts. In this article, you will learn the core uses and differences between the two open-source OS.
It is an open-source, stripped-down Linux distribution that’s similar to projects like Google’s Container-Optimized OS. This single-step update process helps reduce management overhead.
_It makes OS updates easy to automate using container orchestration services such as Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS). _
It’s an OS image for Google Compute Engine VMs that’s optimized for running Docker containers. It allows you to bring up your Docker containers on Google Cloud Platform securely, and quickly. It is based on the open-source Chromium OS project and is maintained by Google.
But before diving into the core differences, let us give you a basic overview of containers, VMs, and container-optimized OS, and its underlying challenges to better understand the differences.
If you are already aware of all the underlying processes of containers, then you can skip to the main differences for AWS Bottlerocket vs Google Container-Optimized OS.
#containers #amazon-aws #google-cloud #container-optimized-os #aws-containers #docker-containers #linux-based-os #orchestration
The DevOps methodology, a software and team management approach defined by the portmanteau of Development and Operations, was first coined in 2009 and has since become a buzzword concept in the IT field.
DevOps has come to mean many things to each individual who uses the term as DevOps is not a singularly defined standard, software, or process but more of a culture. Gartner defines DevOps as:
“DevOps represents a change in IT culture, focusing on rapid IT service delivery through the adoption of agile, lean practices in the context of a system-oriented approach. DevOps emphasizes people (and culture), and seeks to improve collaboration between operations and development teams. DevOps implementations utilize technology — especially automation tools that can leverage an increasingly programmable and dynamic infrastructure from a life cycle perspective.”
As you can see from the above definition, DevOps is a multi-faceted approach to the Software Development Life Cycle (SDLC), but its main underlying strength is how it leverages technology and software to streamline this process. So with the right approach to DevOps, notably adopting its philosophies of co-operation and implementing the right tools, your business can increase deployment frequency by a factor of 30 and lead times by a factor of 8000 over traditional methods, according to a CapGemini survey.
This list is designed to be as comprehensive as possible. The article comprises both very well established tools for those who are new to the DevOps methodology and those tools that are more recent releases to the market — either way, there is bound to be a tool on here that can be an asset for you and your business. For those who already live and breathe DevOps, we hope you find something that will assist you in your growing enterprise.
With such a litany of tools to choose from, there is no “right” answer to what tools you should adopt. No single tool will cover all your needs and will be deployed across a variety of development and Operational teams, so let’s break down what you need to consider before choosing what tool might work for you.
With all that in mind, I hope this selection of tools will aid you as your business continues to expand into the DevOps lifestyle.
AWS CloudFormation is an absolute must if you are currently working, or planning to work, in the AWS Cloud. CloudFormation allows you to model your AWS infrastructure and provision all your AWS resources swiftly and easily. All of this is done within a JSON or YAML template file and the service comes with a variety of automation features ensuring your deployments will be predictable, reliable, and manageable.
Azure Resource Manager (ARM) is Microsoft’s answer to an all-encompassing IAC tool. With its ARM templates, described within JSON files, Azure Resource Manager will provision your infrastructure, handle dependencies, and declare multiple resources via a single template.
Much like the tools mentioned above, Google Cloud Deployment Manager is Google’s IAC tool for the Google Cloud Platform. This tool utilizes YAML for its config files and JINJA2 or PYTHON for its templates. Some of its notable features are synchronistic deployment and ‘preview’, allowing you an overhead view of changes before they are committed.
Terraform is brought to you by HashiCorp, the makers of Vault and Nomad. Terraform is vastly different from the above-mentioned tools in that it is not restricted to a specific cloud environment, this comes with increased benefits for tackling complex distributed applications without being tied to a single platform. And much like Google Cloud Deployment Manager, Terraform also has a preview feature.
Chef is an ideal choice for those who favor CI/CD. At its heart, Chef utilizes self-described recipes, templates, and cookbooks; a collection of ready-made templates. Cookbooks allow for consistent configuration even as your infrastructure rapidly scales. All of this is wrapped up in a beautiful Ruby-based DSL pie.
#tools #devops #devops 2020 #tech tools #tool selection #tool comparison
At some point we’ve all said the words, “But it works on my machine.” It usually happens during testing or when you’re trying to get a new project set up. Sometimes it happens when you pull down changes from an updated branch.
Every machine has different underlying states depending on the operating system, other installed programs, and permissions. Getting a project to run locally could take hours or even days because of weird system issues.
The worst part is that this can also happen in production. If the server is configured differently than what you’re running locally, your changes might not work as you expect and cause problems for users. There’s a way around all of these common issues using containers.
A container is a piece of software that packages code and its dependencies so that the application can run in any computing environment. They basically create a little unit that you can put on any operating system and reliably and consistently run the application. You don’t have to worry about any of those underlying system issues creeping in later.
Although containers were already used in Linux for years, they became more popular in recent years. Most of the time when people are talking about containers, they’re referring to Docker containers. These containers are built from images that include all of the dependencies needed to run an application.
When you think of containers, virtual machines might also come to mind. They are very similar, but the big difference is that containers virtualize the operating system instead of the hardware. That’s what makes them so easy to run on all of the operating systems consistently.
Since we know how odd happenings occur when you move code from one computing environment to another, this is also a common issue with moving code to the different environments in our DevOps process. You don’t want to have to deal with system differences between staging and production. That would require more work than it should.
Once you have an artifact built, you should be able to use it in any environment from local to production. That’s the reason we use containers in DevOps. It’s also invaluable when you’re working with microservices. Docker containers used with something like Kubernetes will make it easier for you to handle larger systems with more moving pieces.
#devops #containers #containers-devops #devops-containers #devops-tools #devops-docker #docker #docker-image
Containerd, however, has graduated into its own high-level container runtime. On February 28, 2019, Containerd graduated as a project within the Cloud Native Computing Foundation, which placed this tool alongside Kubernetes, CoreDNS, and Prometheus. The support of thousands of developers behind Containerd made it possible.
As a high-level container runtime, Containerd no longer requires Docker to run properly. It can now run on its own, with runc being its low-level container runtime. When used to deploy and manage Kubernetes, you can see Containerd as replacing Docker and Docker-shim with CRI-Containerd. Containerd has a few tricks up its sleeve too.
Containerd works with both Linux and Windows and can handle on-premise and cloud hardware without a problem. Since Containerd completely abstracts syscalls or OS specific functionality, it is the perfect solution for running containers on top of any OSes it supports. Everything, from service discovery to netlink calls, is made simple.
#blog #containers #container orchestration tools #container security #containerd #docker