Virtualization

In the ‘DevOps’ world, organizations are implementing or building processes using Infrastructure as Code (IAC). Ansible, Terraform, and Puppet allow enterprises to scale and create repeatable configurations that test and enforce procedures to continually ensure the right results.

We will examine the differences between these three more in-depth. To guide you through choosing a platform that will work best for your needs. All three are advanced-level platforms for deploying replicable and repetitive applications that have highly complex requirements.

Compare the similarities and differences these applications have in terms of configuration management, architecture, and orchestration and make an informed decision.

Infrastructure as Code

Introduced over a decade ago, the concept of Infrastructure as Code (IAC) refers to the process of managing and provisioning computer data centers. It’s a strategy for managing data center servers, networking infrastructure, and storage. Its purpose is to simplify large-scale management and configuration dramatically.

IAC allows provisioning and managing of computer data centers via machine-readable definition files without having to configure tools or physical hardware. In simpler terms, IAC treats manual configurations, build guides, run books, and related procedures as code. Read by software, the code that maintains the state of the infrastructure.

Designed to solve configuration drift, system inconsistencies, human error, and loss of context, IAC resolves all these potentially crippling problems. These processes used to take a considerable amount of time; modern IAC tools make all processes faster. It eliminates manual configuration steps and makes them repeatable and scalable. It can load several hundred servers significantly quicker. It allows users to gain predictable architecture and confidently maintain the configuration or state of the data center.

There are several IAC tools to choose from, with three major examples being Ansible, Terraform, and Puppet. All of them have their unique set of strengths and weaknesses, which we’ll explore further.

Short Background on Terraform, Ansible, and Puppet

Before we begin comparing the tools, see a brief description below:

• Terraform (released 2014 – current version 0.12.8): Hashicorp developed Terraform as an infrastructure orchestrator and service provisioner. It is cloud-agnostic, supporting several providers. As a result, users can manage multi-cloud or multi offering environments, using the same programming language and configuration construct. It utilizes the Haschorp Language and is quite user-friendly as compared to other tools.
• Ansible (released 2012 – current version 2.8.4): Ansible is a powerful tool used to bring services and servers into the desired state, utilizing an assortment of classes and configuration methods. Additionally, it can also connect to different providers via wrapper modules to configure resources. Users prefer it because it is lightweight when coding is concerned, with speedy deployment capabilities.
• Puppet (released 2005 – current version 6.8.0): Puppet is one of the oldest declarative desired state tools available. It is server/client-based, one which refreshes the state on clients via a catalog. It uses “hieradata”, a robust metadata configuration method. It enforces system configuration with programs through its power to define infrastructure as code. It’s widely used on Windows or Linux to pull strings on multiple application servers simultaneously.

Orchestration vs Configuration Management

Ansible and Terraform have some critical differences, but the two do have some similarities as well. They differ when we look at two DevOps concepts: orchestration and configuration management, which are types of tools. Terraform is an orchestration tool. Ansible is mainly a configuration management tool (CM); they perform differently but do have some overlaps since these functions are not mutually exclusive. Optimized for various usage and strengths, use these tools for situations.

Orchestration tools have one goal: to ensure an environment is continuously in its ‘desired state.’ Terraform is built for this as it stores the state of the environment, and when something does not function properly, it automatically computes and restores the system after reloading. It’s perfect for environments that need a constant and invariable state. ‘Terraform Apply’ is made to resolve all anomalies efficiently.

Configuration management tools are different; they don’t reset a system. Instead, they locally repair an issue. Puppet has a design that installs and manages software on servers. Like Puppet, Ansible also can configure each action and instrument and ensure its functioning correctly without any error or damage. A CM tool works to repair a problem instead of replacing the system entirely. In this case, Ansible is a bit of a hybrid since it can do both, perform orchestration and replace infrastructure. Terraform is more widely used. It’s considered the superior product since it has advanced state management capabilities, which Ansible does not.

The important thing to know here is that there is an overlap of features here. Most CM tools can do provisioning to some level, and vice versa, many provisioning tools can do a bit of configuration management. The reality is that different tools are a better fit for certain types of tasks, so it comes down to the requirements of your servers.

Procedural vs. Declarative

DevOps tools come in two categories that define their actions: ‘declarative’ and ‘procedural.’ Not every tool will fit this mold as an overlap exists. Procedural defines a tool that needs precise direction and procedure that you must lay out in code. Declarative refers to a tool ‘declaring’ exactly what is needed. It does not outline the process needed to gain the result.

In this case, Terraform is wholly declarative. There is a defined environment. If there is any alteration to that environment, it’s rectified on the next ‘Terraform Apply.’ In short, the tool attempts to reach the desired end state, which a sysadmin has described. Puppet also aims to be declarative in this way.
With Terraform, you simply need to describe the desired state, and Terraform will figure out how to get from one state to the next automatically.

Ansible, alternatively, is somewhat of a hybrid in this case. It can do a bit of both. It performs ad-hoc commands which implement procedural-style configurations and uses most of the modules that perform in a declarative-style.

If you decide to use Ansible, read the documentation carefully, so you know its role and understand the behavior to expect. It’s imperative to know if you need to add or subtract resources to obtain the right result or if you need to indicate the resources required explicitly.

Comparing Provisioning

Automating the provisioning of any infrastructure is the first step in the automation of an entire operational lifecycle of an application and its deployment. In the cloud, the software runs from a VM, Docker container, or a bare metal server. Either Terraform, or Ansible is a good choice for provisioning such systems. Puppet is the older tool, so we’ll take a closer look at the newer DevOps programs for managing multiple servers.

Terraform and Ansible approach the process of provisioning differently, as described below, but there is some overlap.

Provisioning with Terraform:

There are certain behaviors not represented in Terraform’s existing declarative model. This setup adds a significant amount of uncertainty and complexity when using Terraform in the following ways:

The Terraform model is unable to model the actions of provisioners when it is part of a plan. It requires coordinating more details than what is necessary for normal Terraform usage to use provisioners successfully.

It requires additional measures such as granting direct network access to the user’s servers, installing essential external software, and issuing Terraform credentials for logging in.

Provisioning with Ansible:

Ansible can provision the latest cloud platforms, network devices, bare metal servers, virtualized hosts, and hypervisors reliably.

After completing bootstrapping, Ansible allows separate teams to connect nodes to the storage. It can add them to a load balancer, or any security patched or other operational tasks. This setup makes Ansible the perfect connecting tool for any process pipeline.

It aids in automatically taking bare infrastructure right through to daily management. Provisioning with Ansible, allows users to use a universal, human-readable automation language seamlessly across configuration management, application deployment, and orchestration.

Differences between Ansible and Terraform for AWS

AWS stands for Amazon Web Services, a subsidiary of Amazon, which provides individuals, companies, and business entities on-demand cloud computing platforms. Both Terraform and Ansible treat AWS management quite differently.

Terraform with AWS:

Terraform is an excellent way for users who do not have a lot of virtualization experience to manage AWS. Even though it can feel quite complicated at first, Terraform has drastically reduced the hurdles standing in the way of increasing adoption.

There are several notable advantages when using Terraform with AWS.

• Terraform is open-source, bringing with it all the usual advantages of using open-source software, along with a growing and eager community of users behind it.
• It has an in-built understanding of resource relationships.
• In the event of a failure, they isolate to dependent resources. Non-dependent resources, on the other hand, continue to be created, updated, and destroyed.
• Terraform gives users the ability to preview changes before being applied.
• Terraform comes with JSON support and a user-friendly custom syntax.

Ansible with AWS:

Ansible has offered significant support for AWS for a long time. This support allows interpretation of even the most complicated of AWS environments using Ansible playbooks. Once described, users can deploy them multiple times as required, with the ability to scale out to hundreds and even thousands of instances across various regions.

Ansible has close to 100 modules that support AWS capabilities. Such as Virtual Private Cloud (VPC), Simple Storage Service (S3), Security Token Service, Security Groups, Route53, Relational Database Service, Lambda, Identity Access Manager (IAM), AMI Management and CloudTrail to name a few. Also, it includes over 1300 additional modules for managing different aspects of a user’s Linux, Windows, UNIX, etc.

Here are the advantages when using Ansible with AWS.

• With Ansible Tower’s cloud inventory synchronization, you will find out precisely which AWS instances register despite no matter how they launched.
• You can control inventory by keeping track of deployed infrastructure accurately via their lifecycles. So, you can be sure systems manage properly, and security policies execute correctly.
• Safety in automation with its set of role-based access controls ensuring users will only have access to the AWS resources they need to fulfill their job.
• The same simple playbook language manages infrastructure and deploys applications on a large scale and to different infrastructures easily.

Comparison of Ansible, Puppet, and Terraform

Puppet, Terraform, and Ansible have been around for a considerable period. However, they differ when it comes to set up, GUI, CLI, language, usage, and other features.

You can find a detailed comparison between the three below:

Three Comprehensive Solutions To Consider

After looking at the above comparisons, Ansible is quite beneficial for storage and configuring systems in script-like fashion, versus the others. Users can efficiently work in short-lived environments. It also works seamlessly with Kubernetes for configuring container hosts.

Puppet is more mature when it comes to its community support. Puppet has superior modules that allow it to work more as an enterprise-ready solution. Its robust module testing is easy to use. Ansible is suitable for small, temporary, and fast deployments. Whereas, Puppet comes recommended for longer-term or more complex deployments and can manage Docker containers and container orchestrators.

Terraform performs better when it comes to managing cloud services below the server. Ansible is excellent at provisioning software and machines; Terraform is excellent at managing cloud resources.

All three have their benefits and limitations when designing IAC environments for automation. Success depends on knowing which tools to use for which jobs.

Find out which platform can best help redefine the delivery of your services. Reach out to one of our experts for a consultation today.

Orchestration tools help users manage containerized applications during development, testing, and deployment. They orchestrate the complete application life cycle based on given specifications. Currently, there is a large variety of Container Orchestration Tools. Do not be surprised if many are Kubernetes related, as many different organizations use it for their production environments. Let’s compare some of the top tools available in 2020.

Introduction to Container Orchestration

Container orchestration is the process of automating the management of container-based microservice applications across multiple clusters. This concept is becoming increasingly popular within organizations. Alongside it, a wide array of Container Orchestration tools have become essential in deploying microservice-based applications.

Modern software development is no longer monolithic. Instead, it creates component-based applications that reside inside multiple containers. These scalable and adjustable containers come together and coordinate to perform a specific function or microservice. They can span across many clusters depending on the complexity of the application and other needs such as load balancing.

Containers package together application code and their dependencies. They obtain the necessary resources from physical or virtual hosts to work efficiently. When complex systems are developed as containers, proper organization and prioritization are required when clustering them for deployment.

That is where Container orchestration tools come in to play along with numerous advantages, such as:

• Better environmental adaptability and portability.
• Effortless deploying and managing.
• Higher scalability.
• Stabler virtualization of OS resources.
• Constant availability and redundancy.
• Handles and spread application load evenly across the system.
• Improved networking within the application.

Comparing the Top Orchestration Tools

Kubernetes (K8s)

Google initially developed Kubernetes. It has since become a flagship project of the Cloud Native Computing Foundation. It is an open-source, portable, cluster managed orchestration framework. Most importantly, Kubernetes is backed by google. The design of Kubernetes allows containerized applications to run multiple clusters for more reliable accessibility and organization.

Kubernetes is extremely popular within DevOps circles because tools like Docker offer Kubernetes as Platform as a Service (PaaS) or infrastructure as a Service (IaaS).

Key Features

• Automated deployment, rollouts, and rollbacks.
• Automatic scalability and controllability
• Isolation of containers.
• Ability to keep track of service health
• Service discovery and load balancing
• It works as a platform providing service.

Advantages

• Provide complete enterprise-level container and cluster management services.
• It’s well documented and extensible.
• Adjust the workload without redesigning the application.
• Lesser resource costs.
• Flexibility in deploying and managing.
• Enhanced portability due to container isolation.

Many cloud providers use Kubernetes to give managed solutions as it’s the current standard for container orchestration tools.

Kubernetes Engine

Kubernetes Engine is part of the Google cloud platform with container and cluster management services. It provides all the functionality of Kubernetes, like deployment, scaling, and management of containerized applications. Also, it’s faster and more efficient as it’s not necessary to handle individual Kubernetes clusters.

Kubernetes engine manages and runs even Google’s applications like Gmail and YouTube. Synonymous with productivity, innovation, resource efficiency.

Key Features

• Support for Kubernetes based container tools like Docker.
• It offers a hybrid networking system where it allocates a range of IP addresses for a cluster.
• It provides powerful scheduling features.
• Utilizes its OS to manage and control the containers.
• Uses Google Cloud Platform’s control panel to provide integrated logging and monitoring.

Advantages

• Automatic scaling, upgrading, and repairing.
• Facilitate container isolation by removing interdependencies.
• Seamlessly load-balanced and scaled.
• Secure with Google’s Network policies.
• Portability between Clouds and On-Premises.

Amazon Elastic Kubernetes Service (EKS)

Amazon EKS is another well managed Kubernetes service. It takes over the responsibility of managing, securing, and scaling containerized applications. Thus, nullifying the need for the Kubernetes control panel. These EKS clusters run in AWS Fargate in multiple zones, which computes containers without a server. Kubernetes based applications can be conveniently migrated to Amazon EKS without any code refactoring.

EKS integrates with many open-source Kubernetes tools. These come from both the community and several AWS tools like Route 53, AWS Application Load Balancer, and Auto Scaling.

Key Features

• Facilitates a scalable and highly available control plane.
• Support for distributed infrastructure management in multiple AWS availability zones.
• Consumer service mesh features with AWS App Mesh.
• EKS integrates with many services like Amazon Virtual Private Cloud (VPC), Amazon CloudWatch, Auto Scaling Groups, and AWS Identity and Access Management (IAM).

Advantages

• Eliminates the necessity of provision and manage servers.
• Can specify the resources per application and pay accordingly.
• More secure with application isolation design.
• Continues healthy monitoring without any downtime upgrades and patching.
• Avoid single point of failure as it runs in multiple availability zones.
• Monitoring, traffic control, and load balancing are improved.

Azure Kubernetes Service (AKS)

AKS provides a managed service for hosted Kubernetes with continuous integration and continuous delivery approach. It facilitates convenient deploying and managing, serverless Kubernetes with more dependable security and governance.

AKS provides an agile microservices architecture. It enables simplified deployment and management of systems complex enough for machine learning. They can be easily migrated to the cloud with portability for its containers and configurations.

Key Features

• Integrated with Visual Studio Code Kubernetes tools, Azure DevOps and Azure Monitor
• KEDA for auto-scaling and triggers.
• Access management via Azure Active Directory.
• Enforce rules across multiple clusters with Azure Policy.

Advantages

• The ability to build, manage, and scale microservice-based applications.
• Simple portability and application migration options
• Better security and speed when Devops works together with AKS.
• AKS is easily scalable by using additional pods in ACI.
• Real-time processing of data streams.
• Ability to train machine learning models efficiently in AKS clusters using tools like Kubeflow.
• It provides scalable resources to run IoT solutions.

IBM Cloud Kubernetes Service

This option is a fully managed service designed for the cloud. It facilitates modern containerized applications and microservices. Also, it has capabilities to build and operate the existing applications by incorporating DevOps. Furthermore, It integrates with advance services like IBM Watson and Blockchain for swift and efficient application delivery.

Key Features

• Ability to containerize existing apps in the cloud and extend them for new features.
• Automatic rollouts and rollbacks.
• Facilitates horizontal scaling by adding more nodes to the pool.
• Containers with customized configuration management.
• Effective logging and monitoring.
• It has improved security and isolation policies.

Advantages

• Secure and simplified cluster management.
• Service discovery and load balancing capabilities are stabler.
• Elastic scaling and immutable deployment
• Dynamic provisioning
• Resilient and self-healing containers.

Amazon Elastic Container Service (ECS)

Amazon ECS is a container orchestration tool that runs applications in a managed cluster of Amazon EC2 instances. ECS powers many Amazon services such as Amazon.com’s recommendation engine, AWSBatch, and Amazon SageMaker. This setup ensures the credibility of its security, reliability, and availability. Therefore ECS can be considered as suitable to run mission-critical applications.

Key Features

• Similar to EKS, ECS clusters run in serverless AWS Fargate.
• Run and manage Docker containers.
• Integrates with AWS App Mesh and other AWS services to bring out greater capabilities. For example:
  • Amazon Route 53,
  • Amazon CloudWatch
  • Access Management (IAM)
  • AWS Identity,
  • Secrets Manager
• Support for third party docker image repository.
• Support Docker networking through Amazon VPC.

Advantages

• Payment is based on resources per application.
• Provision and managed servers are not needed.
• Updated resource locations ensure higher availability.
• End to end visibility through service mesh
• Networking via Amazon VPC ensures container isolation and security.
• Scalability without complexity.
• More effective load balancing.

Azure Service Fabric

ASF is a distributed service framework for managing container-based applications or microservices. It can be either cloud-based or on-premise. Its scalable, flexible, data-aware platform delivers low latency and high throughput workloads, addressing many challenges of native cloud-based applications.

A “run anything anywhere” platform, it helps to build and manage Mission-critical applications. ASF supports Multi-tenant SaaS applications. IoT data gathering and processing workloads are its other benefits.

Key Features

• Publish Microservices in different machines and platforms.
• Enabling automatic upgrades.
• Self-repair scaling in or scaling out nodes.
• Scale automatically by removing or populating nodes.
• Facilitates the ability to have multiple instances of the same service.
• Support for multi-language and frameworks.

Advantages

• Low latency and improved efficiency.
• Automatic upgrades with zero downtime
• Supports stateful and stateless services
• It can be installed to run on multiple platforms.
• Allows more dependable resource balancing and monitoring
• Full application lifecycle management with CI/CD abilities.
• Perform leader election and service discovery automatically.

Docker Platform

Docker Orchestration tools facilitate the SDLC from development to production while Docker swarm takes care of cluster management. It provides fast, scalable, and seamless production possibilities for dispersed applications. A proven way to best handle Kubernetes and containers.

It enables building and sharing Docker images within teams as well as large communities. Docker platform is extremely popular among developers. According to a Stack Overflow survey, it ranked as the most “wanted,” “loved,” and “used” platform.

Key Features

• It supports both Windows and Linux OS
• It provides the ability to create Windows applications using the Docker Engine (CS Docker Engine) and Docker Datacenter.
• It uses the same kernel as Linux, which is used in the host computer.
• Supports any container supported infrastructure.
• Docker Datacenter facilitates heterogeneous applications for Windows and Linux.
• Docker tools can containerize legacy applications through Windows server containers.

Advantages

• It provides a perfect platform to build, ship, and run distributed systems faster.
• Docker provides a well-equipped DevOps environment for developers, testers, and the deployment team.
• Improved performance with cloud-like flexibility.
• Smaller size as it uses the same kernel as the host.
• It provides the ability to migrate applications to the cloud without a hassle.

Helios

Helios is an open-source platform for Docker by Spotify. It enables running containers across many servers. Further, it avoids a single point of failure since it can handle many HTTP requests at the same time. Helios logs all deploys, restarts, and version changes. It can be managed through its command-line and via HTTP API.

Key Features

• Fits easily into the way you do DevOps.
• Works with any network topology or operating system.
• It can run many machines at a time or a single machine instance.
• No prescribed service discovery.
• Apache Mesos is not a requirement to run Helios. However, JVM and Zookeeper are prerequisites.

Advantages

• Pragmatic
• Works at scale
• No system dependencies
• Avoid single points of failure

How to Choose a Container Orchestration Tool?

We have looked at several Orchestration Tools that you can consider choosing from when deciding what is best for your organization. To do so, be clear about your organization’s requirements and processes. Then you can more easily assess the pros and cons of each.

Kubernetes

Kubernetes provides a tremendous amount of functionality and is best suited for enterprise-level containers and cluster management. Various platforms manage Kubernetes like Google, AWS, Azure, Pivotal, and Docker. You have considerable flexibility as the containerized workload scales.

The main drawback is the lack of compatibility with Docker Swarm and Compose CLI manifests. It can also be quite complex to learn and set up. Despite these drawbacks, it’s one of the most sought after platforms to deploy and manage clusters.

Docker Swarm

Docker Swarm is more suitable for those already familiar with Docker Compose. Simple and straightforward it requires no additional software. However, unlike Kubernetes and Amazon ECS, Docker Swarm does not have advanced functionalities like built-in logging and monitoring. Therefore, it is more suitable for small scale organizations that are getting started with containers.

Amazon ECS

If you’re already familiar with AWS, Amazon ECS is an excellent solution for cluster deployment and configuration. A fast and convenient way to start-up and meets demand with scale, it integrates with several other AWS services. Furthermore, it’s ideal for small teams who do not have many resources to maintain containers.

One of its cons is that it’s not suitable for nonstandard deployments. It also has ECS specific configuration files making troubleshooting difficult.

Find Out More About Server Orchestration Tools

The software industry is rapidly moving towards the development of containerized applications. The importance of choosing the right tools to manage them is ever-increasing increasing.

Container Orchestration Platforms have various features and solutions for the challenges caused by their use. We have compared and analyzed the many differences between Container Orchestration Tools. The “Kubernetes vs. Docker-swarm” and “Kubernetes vs. Mesos” articles are noteworthy among them.

If you want more information about which tools suit your architecture best, book a call with one of our experts today

What is Container Orchestration?

Container orchestration refers to a process that deals with managing the lifecycles of containers in large, dynamic environments. It’s a tool that schedules the workload of individuated containers within many clusters, for applications based on microservices. A process of virtualization, it essentially separates and organizes services and applications at the base operating level. Orchestration is not a hypervisor since the containers are not separate from the rest of the architecture. It shares the same resources and kernel of the operating system.

Containerization has emerged as a new way for software organizations to build and maintain complex applications. Organizations that have adopted microservices in their businesses are using container platforms for application management and packaging.

The problem it solves

Scalability is the problem that containerization resolves when facing operational challenges in utilizing containers effectively. The problem begins when there are many containers and services to manage simultaneously. Their organization becomes complicated and cumbersome. Container orchestration solves that problem by offering practical methods for automating the management, deployment, scaling, networking, and availability of containers.

Microservices use containerization to deliver more scalable and agile applications. This tool gives companies complete access to a specific set of resources, either in the host’s physical or virtual operating system. It’s why containerization platforms have become one of the most sought-after tools for digital transformation.

Software teams in large organizations find container orchestration a highly effective way to control and to automate a series of tasks, including;

• Container Provisioning
• Container Deployment
• Container redundancy and availability
• Removing or scaling up containers to spread the load evenly across the host’s system.
• Allocating resources between containers
• Monitoring the health of containers and hosts
• Configuring an application in relation to specific containers which are using them
• Balancing service discovery load between containers
• Assisting in the movement of containers from one host to another if resources are limited or if a host expires

To explain how containerization works we need to look at the deployment of microservices. Microservices employ containerization to deliver tiny, single-function modules. They work together to produce more scalable and agile applications. This inter-functionality of smaller components (containers) is so advantageous that you do not have to build or deploy a completely new version of your software each time you update or scale a function. It saves time, resources, and allows for flexibility that monolithic architecture cannot provide.

How Does Container Orchestration Work?

There are a host of container orchestration tools available on the market currently with Docker swarm and Kubernetes commanding the largest user-bases in the community.

Software teams use container orchestration tools to scribe the configuration of their applications. Depending on the nature of the orchestration tool being used, the file could be in a JSON or YAML format. These configuration files are responsible for directing the orchestration tool towards the location of container images. Information on other functions that the configuration file is responsible for includes establishing networking between containers, mounting storage volumes, and the location for storing logs for the particular container.

Replicated groups of containers deploy onto the hosts. The container orchestration tool subsequently schedules the deployment, once it’s time to deploy a container into a cluster. It then searches for an appropriate host to place the container, based on constraints such as CPU or memory availability. The organization of containers happens according to labels, Metadata, and their proximity to other hosts.

The orchestration tool manages the container’s lifecycle once it’s running on the host. IT follows specifications laid out by the software team in the container’s definition file. Orchestration tools are increasingly popular due to their versatility. They can work in any environment which supports containers. Thus, they support both traditional on-premise servers and public cloud instances, running on services such as Microsoft Azure or Amazon Web Services.

What are containers used for?

Making deployment of repetitive tasks and jobs easier: Containers assist or support one or several similar processes that are run in the background, i.e. batch jobs or ETL functions.

Giving enhanced support to the microservices architecture: Microservices and distributed applications are effortlessly deployed and easily isolated or scaled by implementing single container building blocks.

Lifting and shifting: Containers can ‘Lift and Shift’, which means to migrate existing applications into modern and upgraded environments.

Creating and developing new container-native apps: This aspect underlines most of the benefits of using containers, such as refactoring, which is more intensive and beneficial than ‘lift-and-shift migration’. You can also isolate test environments for new updates for existing applications.

Giving DevOps more support for (CI/CD): Container technology allows for streamlined building, testing, and deployment from the same container images and assists DevOps to achieve continuous integration and deployment.

Benefits of Containerized Orchestration Tools

Container orchestration tools, once implemented, can provide many benefits in terms of productivity, security, and portability. Below are the main advantages of containerization.

• Enhances productivity: Container orchestration has simplified installation, decreasing the number of dependency errors.
• Deployments are faster and simple: Container orchestration tools are user-friendly, allowing quick creation of new containerized applications to address increasing traffic.
• Lower overhead: Containers take up lesser system resources when you compare to hardware virtual-machine or traditional environments. Why? Operating system images are not included.
• Improvement in security: Container orchestration tools allow users to share specific resources safely, without risking security. Web application security is further enhanced by application isolation, which separates each application’s process into separate containers.
• Increase in Portability: Container orchestration allows users to scale applications with a single command. It only provides scale specific functions which do not affect the entire application.
• Immutability: Container orchestration can encourage the development of distributed systems, adhering to the principles of immutable infrastructure, which cannot be affected by user modifications.

Container Orchestration Tools: Kubernetes vs. Docker Swarm

Kubernetes and Docker are the two current market leaders in building and managing containers.

Docker, when first became available, became synonymous with containerization. It’s a runtime environment that creates and builds software inside containers. According to Statista, over 50% of IT leaders reported using Docker container technology in their companies last year. Kubernetes is a container orchestrator. It recognizes multiple container runtime environments, such as Docker.

To understand the differences between Kubernetes and Docker Swarm, we should examine it more closely. Each has its own sets of merits and disadvantages, which makes the task of choosing between one of them, a tough one. Indeed, both the technologies differ in some fundamental ways, as evidenced below:

Which Containerization Tool to Use?

Container orchestration tools are still fledgling and constantly evolving technologies. Users should make their decision after looking at a variety of factors such as architecture, flexibility, high availability needs, and learning curve. Besides the two popular tools, Kubernetes and Docker Swarm, there are also a host of other third-party tools and software associated with them both, which allow for continuous deployment.

Kubernetes currently stands as the clear standard when it comes to container orchestration. Many cloud service providers as Google and Microsoft have started offering “Kubernetes-as-a-service” options. Yet, if you’re starting and running a smaller deployment without a lot to scale, then Docker Swarm is the way to go. Read our in-depth article on the key differences between Kubernetes vs Docker Swarm.

To get support with your container development and CI/CD pipeline, or find out how advanced container orchestration can enhance your microservices, connect with one of our experts to explore your options today.

With serverless computing and container technology being at the forefront, the demand for container technology has risen considerably. Container management platforms such as Kubernetes and OpenShift may be well-known, though possibly not as well understood.

Both Kubernetes and OpenShift consist of modern, future proof architecture, which is also robust and scalable. Due to the similarities, the decision to choose one of the two platforms can be difficult. In this article, we compare Kubernetes versus OpenShift in detail and examine the fundamental differences and unique benefits each provides.

What is Kubernetes?

Kubernetes is an open-source container as a service platform (CaaS) that can automate deploying, scaling, and managing containerized apps to speed up the development procedure. Originally developed at Google, the product was later handed over to the Cloud Native Computing Foundation under the Linux Foundation.

Many cloud services tend to offer a variant of a Kubernetes based platform or infrastructure as a service. Here, Kubernetes can be deployed as a platform-providing service, with many vendors providing their own branded distributions of Kubernetes.

Key Features of Kubernetes

• Storage Orchestration: Allows Kubernetes to integrate with most storage systems, such as AWS Elastic Storage.
• Container Balancing: IT enables Kubernetes to calculate the best location for a container automatically.
• Scalability: Kubernetes allow horizontal scaling. This setup allows for organizations to scale out their storage, depending on their workload requirements.
• Flexibility: Kubernetes can be run in multiple environments, including on-premises, public, or hybrid cloud infrastructures.
• Self-Monitoring: Kubernetes provides monitoring capabilities to help check the health of servers and containers.

Why Choose Kubernetes?

A significant part of the industry prefers Kubernetes due to the following reasons:

• Strong Application Support – Kubernetes has added support for a broad spectrum of programming frameworks and languages, which enables it to satisfy a variety of use cases
• Mature Architecture: The architecture of Kubernetes is preferred because of its association with Google’s Engineers, who have worked on the product for almost ten years.
• Developmental Support: Because Kubernetes has a large and active online user community, new features get added frequently. Additionally, the user community also provides technical support that encourages collaborations.

What is OpenShift?

OpenShift is also a containerization software solution, possessing an Apache License. Developed by Red Hat. Its original product is the OpenShift container platform, a Platform-as-a-Service (PaaS), which can be managed by Kubernetes. Termed as the ‘Enterprise Kubernetes,’ the program is written in a combination of both Go and AngularJS languages. Its primary function allows developers to deploy and develop apps directly on the cloud. It also appends tools over a Kubernetes core to quicken the process.

A substantial change came with the recent introduction of OpenShift V3 (released October 2019). Before the release of this version, custom-developed technologies had to be used for container orchestration. With V3, OpenShift added Docker as their prime container technology, and Kubernetes as the prime container orchestration technology, which will be continued in subsequent releases.

OpenShift brings along with it a set of products such as the OpenShift Container Platform, OpenShift Dedicated, Red Hat OpenShift Online, and OpenShift origin.

Key Features of OpenShift

• Compatibility: As part of the certified Kubernetes program, OpenShift has compatibility with Kubernetes container workloads.
• Constant Security: OpenShift has security checks that are built into the container stack.
• Centralized policy management: OpenShift has a single console across clusters. This control panel provides users with a centralized place to implement policies.
• Built-in Monitoring: OpenShift comes with Prometheus, which is a devops database and application monitoring tool. It allows users to visualize the applications in real-time, using a Grafana dashboard.

Why Choose OpenShift?

Popular reason users prefer OpenShift are highlighted below:

• Self-service Provisioning: OpenShift provides users with the capability of integrating the tools they use the most. For instance, as a result of this, a video game developer can use OpenShift while developing games.
• Faster Application Development: Can stream and automate the entire container management process, which in turn enhances the DevOps process.
• No vendor lock-in: Provides a vendor-agnostic open-source platform, allowing users to migrate their own container processes to other operating systems as required without having to take any extra step.

What is the difference Between OpenShift and Kubernetes?

OpenShift and Kubernetes share many foundational and functional similarities since OpenShift is intentionally based on Kubernetes. Yet, there are other fundamental technical differences explained in the table below.

Evident in the comparison table are their similar features. Kubernetes and OpenShift are both open-source software platforms that facilitate application development via container orchestration. They make managing and deploying containerized apps easy. OpenShift’s web console which allows users to perform most tasks directly on it.

Both facilitate faster application development. OpenShift has a slight advantage when it comes to easy installations, primarily since it relies on Kubernetes to a high degree. Kubernetes does not have a proper strategy in place for installation, despite being the more advanced option. Installing Kubernetes requires managed Kubernetes clusters or a turnkey solution.

OpenShift has also introduced many built-in components and out-of-the-box features to make the process of containerization, faster. Below is a broader comparison table of their points of difference:

Making the Decision: Kubernetes or OpenShift?

Which one you decide to use will come down to the requirements of your system and the application you’re building.

The question to ask in the Kubernetes vs. OpenShift debate is figuring out what features take precedence: Flexibility or an excellent web interface for the development process? Notwithstanding IT experience, infrastructure, and expertise to handle the entire development lifecycle of the application.

Want more information? Connect with us, and allow us to assist you in containerizing your development processes.

Cloud interoperability keeps evolving alongside its platforms. Kubernetes and OpenStack are not merely direct competitors but can now also be combined to create cloud-native applications. Kubernetes is the most widely used container orchestration tool to manage/orchestrate Linux containers. It deploys, maintains, and schedules applications efficiently. OpenStack lets businesses run their Infrastructure-as-a-Service (IaaS) and is a powerful software application.

Kubernetes and OpenStack have been regarded as competitors, but in actuality, both these open-source technologies can be combined and are complementary to one other. They both offer solutions to problems that are relatively similar but do so on different layers of the stack. When you combine Kubernetes and OpenStack, it can give you noticeably enhanced scalability and automation.

It’s now possible for Kubernetes to deploy and manage applications on an OpenStack cloud infrastructure. OpenStack as a cloud orchestration tool allows you to run Kubernetes clusters on top of white label hardware more efficiently. Containers can be aligned with this open infrastructure, which enables them to share computer resources in rich environments, such as networking and storage.

Kubernetes and OpenStack still do compete for users, despite their overlapping features. Both have their own sets of merits and use cases. It’s why it’s necessary to take a closer look at both options to determine their differences and find out which technology or combination is best for your business.

To present a more precise comparison between the two technologies, let’s start with the basics.

What is Kubernetes?

Kubernetes is an open-source cloud platform for managing containerized workloads and services. Kubernetes is a tool used to manage clusters of containerized applications. In computing, this process is often referred to as orchestration.

The analogy with a music orchestra is, in many ways, fitting. Much as a conductor would, Kubernetes coordinates multiple microservices that together form a useful application. It automatically and perpetually monitors the cluster and makes adjustments to its components. Kubernetes architecture provides a mix of portability, extensibility, and functionality, facilitating both declarative configuration and automation. It handles scheduling by using nodes set up in a compute cluster. Kubernetes also actively manages workloads, ensuring that their state matches with the intentions and desired state set by the user.

Kubernetes is designed to make all its components swappable and thus have modular designs. It is built for use with multiple clouds, whether it is public, private, or a combination of the two. Developers tend to prefer Kubernetes for its lightweight, simple, and accessible nature. It operates using a straightforward model. We input how we would like our system to function – Kubernetes compares the desired state to the current state within a cluster. Its service then works to align the two states and achieve and maintain the desired state.

How is Kubernetes Employed?

Kubernetes is arguably one of the most popular tools employed when it comes to getting the most value out of containers. Its features ensure that it is a near-perfect tool designed to automate scaling, deployment, and operating containerized applications.

Kubernetes is not only an orchestration system. It is a set of independent, interconnected control processes. Its role is to continuously work on the current state and move the processes in the desired direction. Kubernetes is ideal for service consumers, such as developers working in enterprise environments as it provides support for programmable, agile, and rapidly deployable environments.

Kubernetes is used for several different reasons:

1. High Availability: Kubernetes includes several high-availability features such as multi-master and cluster federation. The cluster federation feature allows clusters to be linked together. This setup exists so that containers can automatically move to another cluster if one fails or goes down.
2. Heterogeneous Clusters: Kubernetes can run on heterogeneous clusters allowing users to build clusters from a mix of virtual machines (VMs) running the cloud, according to user requirements.
3. Persistent Storage: Kubernetes has extended support for persistent storage, which is connected to stateless application containers.
4. Built-in Service Discovery and Auto-Scaling: Kubernetes supports service discovery, out of the box, by using environment variables and DNS. For increased resource utilization, users can also configure CPU based auto-scaling for containers.
5. Resource Bin Packing: Users can declare the maximum and minimum compute resources for both CPU and memory when dealing with containers. It slots the containers into wherever they fit, which increases compute efficiency, which results in lower costs.
6. Container Deployments and Rollout Controls: The Deployment feature allows users to describe their containers and specify the required quantity. It keeps those containers running and also handles deploying changes. This enables users to pause, resume, and rollback changes as per requirements.

What is OpenStack?

OpenStack an open-source cloud operating system that is employed to develop public and private cloud environments. Made up of multiple interdependent microservices, it offers an IaaS layer that is production-ready for virtual machines and applications. OpenStack, first developed as a cloud infrastructure in July 2010, was a product of the joint effort of many companies, including NASA and Rackspace.

Their goal since has been to provide an open alternative to the top cloud providers. It’s also considered a cloud operating system that can control large pools of computation, storage, and networking resources through a centralized datacenter. All of this is managed through a user-friendly dashboard, which provides users with increased control by allowing them to provision resources through a simple graphic web interface. OpenStack’s growing in popularity because it offers open-source software to businesses wanting to deploy their own private cloud infrastructure versus using a public cloud platform.

How is OpenStack Used?

It’s known for its complexity, consisting of around sixty components, also called ‘services’, six of them are core components, and they control the most critical aspects of the cloud. These services are for the compute, identity, storage management, and networking of the cloud, including access management.

OpenStack comprises of a series of commands known as scripts, which are bundled together into packages called projects. The projects are responsible for relaying tasks that create cloud environments. OpenStack does not virtualize resources itself; instead, it uses them to build clouds.

When it comes to cloud infrastructure management, OpenStack can be employed for the following.

Containers

OpenStack provides a stable foundation for public and private clouds. Containers are used to speed up the application delivery time while also simplifying application management and deployment. Containers running on OpenStack can thus scale container benefits ranging from single teams to even enterprise-wide interdepartmental operations.

Network Functions Virtualization

OpenStack can be used for network functions virtualization, and many global communications service providers include it on their agenda. OpenStack separates a network’s key functions to distribute it among different environments.

Private Clouds

Private cloud distributions tend to run on OpenStack better than other DIY approaches due to the easy installation and management facilities provided by OpenStack. The most advantageous feature is its vendor-neutral API. Its open API erases the worries of single-vendor lock-in for businesses and offers maximum flexibility in the cloud.

Public Clouds

OpenStack is considered as one of the leading open-source options when it comes to creating public cloud environments. OpenStack can be used to set up public clouds with services that are on the same level as most other major public cloud providers. This makes them useful for small scale startups as well as multibillion-dollar enterprises.

Can Kubernetes and OpenStack work together? This is a common question among potential users.

One of the most significant obstacles in the path of OpenStack’s widespread adoption is its ongoing life cycle management. For enterprises, using OpenStack and Kubernetes together can radically simplify the management of OpenStack’s many components. In this way, users benefit from a consistent platform for managing workloads.

Kubernetes and OpenStack can be used together to reap the combined benefits of both the tools. By integrating Kubernetes into OpenStack, Kubernetes users can access a much more robust framework for application deployment and management. Kubernetes’s features, scalability, and flexibility make ‘Stackanetes’ an efficient solution for managing OpenStack and makes operating OpenStack as easy as running any application on Kubernetes.

Benefits of Leveraging Both OpenStack and Kubernetes

Faster Development of Apps

Running Kubernetes and OpenStack together can offer on-demand and access-anytime services. It also helps to increase application portability and reduces development time.

Improving OpenStack’s lifecycle management

Kubernetes, along with cloud-native patterns, improve OpenStack lifecycle management through rolling updates and versioning.

Increased Security

Security has always been a critical concern in container technology. OpenStack solves this by providing a high level of security. It supports the verification of trusted container content by integrating tools for image signing, certification, and scanning.

Standardization

By combining Kubernetes and OpenStack, container technology can become more universally applicable. This makes it easier for organizations to set up as well as deploy container technology, using the existing OpenStack infrastructure.

Easier to Manage

OpenStack can be complex to use and has a steep learning curve, which creates a hindrance for any users. The Stackanetes initiative circumvents the complexity by using Kubernetes cluster orchestration to deploy and manage OpenStack.

Speedy Evolution

Both are widely employed by tech industry giants, notwithstanding Amazon, Google, and eBay. This popularity drives software applications to develop and innovate faster. They increase the pace of evolution to offer solutions to issues as they crop up. Evolving and simultaneously integrating, creates rapidly upgraded enterprise-grade infrastructure and application platforms.

Stability

OpenStack on its own lacks the stability to run smoothly. Kubernetes, on the other hand, uses a large-scale distributed system, allowing it to run smoothly. By combining the two, OpenStack can use a more modernized architecture, which also increases its stability.

There has always been competition between OpenStack and Kubernetes, both of whom are giants in the open-source technology landscape. That’s why it can be surprising to some users when we talk about the advantages of using these two complementary tools together. As both of them solve similar problems but on different layers, combining the two is the most practical solution for scalability and automation. Combined, more than ever, DevOps teams would have more freedom to create cloud-native applications. Both Kubernetes and OpenStack have their advantages and use cases, making it very difficult to compare between the two, as both of them are used in different contexts.

OpenStack, together with Kubernetes, can increase the resilience and scale of its control panel, allowing faster delivery of infrastructure innovation. These different yet complementary technologies, widely used by industry leaders, will keep both innovating at an unprecedented pace.

Find out how these solutions can work for you, and get your free quote today.

Container orchestration is a fast-evolving technology. There are three current industry giants; Kubernetes, Docker Swarm, and Apache Mesos. They fall into the category of DevOps infrastructure management tools, known as ‘Container Orchestration Engines’. Docker Swarm has won over large customer favor, becoming the lead choice in containerization. Kubernetes and Mesos are the main competition. They have something more to offer in this regard. They provide differing gradients of usability, with many evolving features.

Despite the popularity of Docker Swarm, it has some drawbacks and limited functionalities:

• Docker Swarm is platform-dependent.
• Docker Swarm does not provide efficient storage options.
• Docker Swarm has limited fault tolerance.
• Docker Swarm has inadequate monitoring.

These drawbacks provoke businesses to question: ‘How to choose the right container management and orchestration tool?’ Many companies are now choosing an alternative to Docker Swarm. This is where Kubernetes and Mesos come in. To examine this choice systematically, it’s essential to look at the core competencies both options have. So, one can come to an independently informed conclusion.

Characteristics of Docker Swarm, Kubernetes, and Mesos

What is Kubernetes?

First released in June of 2014, Kubernetes, was also known as k8s. It is a container orchestration platform by Google for Cloud-native computing. In terms of features, Kubernetes is one of the most natively integrated options available. It also has a large community behind it. Google makes use of Kubernetes for its Container as a Service offering, renamed as the Google Container Engine. Other platforms that have extended support to Kubernetes include Microsoft Azure and Red Hat OpenShift. It also supports Docker and uses a YAML based deployment model.

Constructed on a modular API core, the architecture of Kubernetes allows vendors to integrate systems around its proprietary technology. It does a great job of empowering application developers with a powerful tool for Docker container orchestration and open-source projects.

What is Apache Mesos?

Apache Mesos’ roots go back to 2009 when Ph.D. students first developed it at UC Berkley. When compared to Kubernetes and Docker Swarm, it takes more of a distributed approach when it comes to managing datacenter and cloud resources.

It takes a modular approach when dealing with container management. It allows users to have flexibility in the types and scalability of applications that they can run. Mesos allows other container management frameworks to run on top of it. This includes Kubernetes, Apache Aurora, Mesosphere Marathon, and Chronos.

Mesos was created to solve many different challenges. One being, to abstract data center resources into a single pool. Another, to collocate diverse workloads and automate day-two operations. And lastly, to provide evergreen extensibility to running tasks and new applications. It has a unique ability to manage a diverse set of workloads individually, including application groups such as Java, stateless micro-services, etc.

Container Management: Explained

Before we decide on how to choose a container management tool, the concept of Container Management must be explained further.

Container Management is the process of adding, organizing, and replacing large numbers of software containers. It utilizes software for automatically creating, deploying, and scaling containers. Container management requires a platform to organize software containers, known as operated-system-level virtualizations. This platform optimizes the efficiency and streamlines container delivery without the use of complex interdependent system architectures.

Containers have become quite popular, as more enterprises are using DevOps for quicker development and for its applications. Container management gives rise to the need for container orchestration, which is a more specialized tool. It automates deployment, management, networking scaling, and availability of container-based applications.

Container Orchestration: Explained

Container Orchestration refers to the automatic process of managing or scheduling of individual containers used for microservices-based applications within multiple clusters. It works with both Kubernetes and Mesos. It also schedules the deployment of containers into the clusters, determining the best host for the container.

Some of the reasons why a container orchestration framework is required include;

• Configuring and scheduling containers
• Container Availability
• Container Provisioning and Deployment
• Container Configuration
• Scaling applications of containers for load balancing
• Health monitoring of containers
• Securing interactions between containers

How to Select Container management and orchestration tool?

There are many variables to consider when deciding on how to implement container management and orchestration efficiently. The final selection will depend on the specific requirements of the user. Some of which are briefly explained below.

1. CNI Networking: A good tool should allow trivial network connectivity between services. This is to avoid developers having to spend time on special-purpose codes for finding dependencies.
2. Simplicity: The tool in use should be as simple to implement as possible.
3. Active Development: The tool chosen should have a development team that provides users with regular updates. This is due to the ever-evolving nature of container orchestration.
4. Cloud Vendor: The tool chosen should not be tied to any single cloud provider.

Note: Container orchestration is just one example of a workload that the Mesos Modular Architecture can run. This specialized orchestration framework is called Marathon. It was originally developed to orchestrate app archives in Linux cgroup containers, later extended support to Docker containers in 2014.

What are the differences between Kubernetes and Mesos?

Kubernetes and Mesos have different approaches to the same problem. Kubernetes acts as a container orchestrator, and Apache Mesos works like a cloud operating system. Therefore, there are several fundamental differences between the two, which are highlighted in the table below.

Conclusion

Kubernetes and Mesos employ different tactics to tackle the same problem. In comparing them based on several features, we have found that both solutions are equivalent in terms of features and other advantages when compared to Docker Swarm.

The conclusion we can come to is that they are both viable options for container management and orchestration. Each tool is effective in managing docker containers. They both provide access to container orchestration for the portability and scalability of applications.

The intuitive architectural design of Mesos provides good options when it comes to handling legacy systems and large-scale clustered environments via its DC/OS. It’s also adept at handling more specific technologies such as distributed processing with Hadoop. Kubernetes is preferred more by development teams who want to build a system dedicated exclusively to docker container orchestration.

Our straightforward comparison should provide users with a clear picture of Kubernetes vs Mesos and their core competencies. The goal has been to provide the reader with relevant data and facts to inform their decision.

How to choose between them will depend on finding the right cluster management solution that fits your company’s technical requirements. If you’d like to find out more about which solution would suit you best, contact us today for a free consultation.