Guide To The 20 Best Containerization Software Of 2024
I’ve compiled this list of the best containerization software to help you build and deploy applications faster than traditional methods.
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Best Containerization Software Shortlist
Here are the top tools I’ve found that make developing applications inside containers easier:
- Docker - Best container builder
- Kubernetes - Best container manager
- Azure Container Apps - Best for data-driven companies
- IBM Cloud Kubernetes Service - Best for enterprise applications
- Openshift Container Platform - Best for on-premise deployments
- Amazon Elastic Container Service - Best network control features
- Google Kubernetes Engine - Best user experience
- Apache Mesos - Best for virtual machines
- MicroK8s - Best for setting up Kubernetes
- AWS Fargate - Best for microservice development
- Oracle Container Engine for Kubernetes - Best threat detection features
- Nomad - Best automation features
With operating systems becoming more technologically advanced, I’ve found that building applications that run within containers is a move in the right direction toward ensuring that they operate smoothly on most platforms. For this reason, I’ve come up with this list of the best software for containerization, along with their strengths, features, and the criteria I used to make the list.
What Is Containerization Software?
Containerization software packages an application’s code along with all the components they need to run into a single package called a container. This way, it’s easier to run the application in different environments because you don’t need to install versions of it that are specific to each platform.
Overviews of the 12 Best Containerization Software
I’ve created detailed overviews of each containerization tool below, along with the criteria I used when making the list.
1. Docker - Best container builder
Docker is an open platform for building and running containers, and it’s one of the most popular tools in its category.
Why I picked Docker: The Docker Compose feature made it easy for me to define and run applications that used multiple containers from scratch. I usually work on containers in a CI/CD system and was glad that it could integrate easily into mine, as well as every other stage of the application development lifecycle.
Docker Standout Features and Integrations
Features that made containerization on Docker a pleasant experience for me include Docker Images, an official collection of pre-configured images with in-depth documentation and strong out-of-the-box security; they come in handy when I’m strapped for time, and I’d recommend them for anyone that’s just getting started with containers.
I also liked the audit logs, which showed me all activities in my environments in chronological order, tagged with time stamps and the identities of the team members responsible. In a rapid development environment, this information helped me stay on top of everything without needing to comb through my repositories manually.
Integrations are pre-built for GitHub, VS Code, TeamCity, Jenkins, CircleCI, Kubernetes, Che, Gitpod, Bitbucket, and Theia.
Pricing: From $5/month
Trial: Free plan available
Pros
- Docker Official Images make development faster
- Active developer community for support
- Integrates with CI/CD pipelines
Cons
- Documentation isn't rich enough
- Steep learning curve
2. Kubernetes - Best container manager
Kubernetes, also known as K8s, is a container orchestration platform that was originally developed by a team of engineers at Google before being publicly released as open source.
Why I picked Kubernetes: Because Kubernetes came from Google, it’s built on many of the same ideas that allow the tech giant to operate massive products. With the HorizontalPodAutoScaler, it automatically creates more pods — active containers within a cluster — as demand goes up and spreads the workload across them to increase the overall capacity of the system.
Kubernetes Standout Features and Integrations
Features I relied on a lot for container orchestration in Kubernetes include the self-healing capabilities that kept failing or dead containers from users, restarted, rescheduled and replaced them, and decommissioned ones that failed my preset health checks. With the batch execution function, I could comfortably manage all the containers I had in my CI systems at scale.
Integrations are pre-built for Snyk, New Relic, GitLab, JFrog, Docker, Ansible, Prometheus, IBM Turbonomic, and Rancher.
Pricing: Free
Trial: Free
Pros
- Strong automation capabilities
- Highly scalable
- Robust documentation and training
Cons
- Practical only for large applications
- Difficult to set up
3. Azure Container Apps - Best for data-driven companies
Azure Container Apps is a platform built on Kubernetes that allows you to deploy apps from containers or code.
Why I picked Azure Container Apps: Like several other products and services on the Azure platform, Container Apps offers analytics capabilities for deep insights into your systems. The one I used the most was Log Analytics which gave me access to system and console logs for my apps. I could also query these logs, then process and visualize the results to squeeze more insight from them.
Azure Container Apps Standout Features and Integrations
Features I liked for data analytics with Container Apps include the metrics on resource usage and activity it collected using Azure Monitor, all of which I could access visualized or raw, depending on what I wanted to do with them. It also has a versioning system called revisioning that I used to create multiple snapshots of my containers on which I could run A/B tests.
Integrations are available natively for other Azure services, including Active Directory, DevOps, Monitor, and VNet.
Pricing: From $0.1296/month
Trial: Free plan available
Pros
- Built-in analytics
- Scalability
- Strong security
Cons
- Complex pricing model
- Difficult to deploy on-premise
4. IBM Cloud Kubernetes Service - Best for enterprise applications
IBM Cloud Kubernetes Service is a fully managed container orchestration tool for running applications on IBM Cloud.
Why I picked IBM Cloud Kubernetes Service: I picked IBM Cloud Kubernetes Service because it takes advantage of IBM Watson to implement automation based on the status of your clusters. I can see the system scaling well into an enterprise setting with several moving parts, with developers essentially being able to leave it to handle most low-level tasks soon after deployment.
IBM Cloud Kubernetes Service Standout Features and Integrations
Features I’d recommend enterprise application developers try in IBM Cloud Kubernetes Service include the option to set up global availability in both multi and single zones depending on how you want to distribute your nodes. For large teams, the platform offers cluster role-based access control (RBAC) that you can implement with IBM Cloud’s IAM policies scoped to different groups depending on their levels, roles, etc.
Integrations are available natively with other products on IBM Cloud, including Watson, Db2, and Object Storage. There’s also an API you can use to connect your own solutions, such as CI/CD workflows.
Pricing: Pricing upon request
Trial: 30-day free trial
Pros
- Highly scalable
- Robust automation features
- Strong security
Cons
- Not stable outside IBM Cloud
- Only one node and cluster each in free trial
5. OpenShift Container Platform - Best for on-premise deployments
OpenShift Container Platform is a Platform-as-a-Service (PaaS) container management offering from Red Hat, one of the top contributors to Kubernetes.
Why I picked OpenShift Container Platform: I picked OpenShift Container Platform because it’s both open source and built on Red Hat Enterprise Linux. This made it easy to deploy on-premises both on physical hardware that I had running Linux as well as on a few VMs, all while maintaining full configurability.
OpenShift Container Platform Standout Features and Integrations
Features that stood out to me while testing OpenShift Container Platform include the source-to-image (S2I) function that allowed me to go from code to complete containerization faster. Coupled with the built-in support for Argo CD, I developed a comprehensive GitOps pipeline for rapid development right within my on-premise environment.
Integrations are pre-made for Ansible, New Relic, Argo CD, Flagsmith, Cado, CloudCasa, Instana, Pagerduty, Kasten K10, Docker, and Response.
Pricing: Pricing upon request
Trial: 60-day free trial
Pros
- Consistent updates
- Source-to-image functionality
- Decent documentation
Cons
- Poor logging features
- Difficult to troubleshoot
6. Amazon Elastic Container Service - Best network control features
Amazon Elastic Container Service (ECS) is a container orchestration platform that makes up part of the AWS family of products and services.
Why I picked Amazon Elastic Container Service: I chose ECS because of the ECS Service Connect feature that I used to manage communications between my active services. It handled the lion’s share of my networking infrastructure, with functions such as spreading out traffic across tasks, implementing resilience, and controlling how applications connect to their respective dependencies.
Amazon Elastic Container Service Standout Features and Integrations
Features I recommend for network management in ECS include task networking, which allows you to isolate containers and have more control over how they connect to external traffic and services. If traffic to your applications is too much for Service Connect to handle, you can access full load balancing with AWS’s Network and Application Load Balancers and have ECS automatically add or remove containers to meet the system’s needs.
Integrations are available natively for other AWS products and services, including Fargate, Outposts, CloudFormation, Systems Manager, Elastic Container Registry (ECR), Config, Elastic Compute Cloud (EC2), Elastic Load Balancer (ELB), ECS Anywhere, and Cloudtrail.
Pricing: Pricing upon request
Trial: Free plan available
Pros
- Robust network and traffic management features
- Several native AWS integrations
- High availability
Cons
- Poor logging
- Struggles outside AWS
7. Google Kubernetes Engine - Best user experience
Google Kubernetes Engine (GKE) is a fully managed Kubernetes-based orchestration solution that runs on Google Cloud.
Why I picked Google Kubernetes Engine: GKE has a user-friendly interface that’s as easy enough for beginners as a containerization platform can be to navigate while still giving technical users everything they need to get the most out of it. I could manage my clusters just fine from the GUI and rarely needed to dip into the Google Cloud CLI.
Google Kubernetes Engine Standout Features and Integrations
Features that make GKE beginner-friendly, in my opinion, include the Autopilot mode that automatically configured all my clusters, from security to scaling and nodes. I also used the release channels feature to handle updates to my clusters, still on Autopilot, with complete versioning to ensure they remained both available and up-to-date during the process.
Integrations are available natively with Google Cloud products such as Source Repositories, CLI, Container Builder, Build, and Deploy.
Pricing: From $0.10/hour
Trial: Free plan available
Pros
- Release channels make Kubernetes updates easy to install
- User-friendly interface
- Autopilot can manage most production workloads
Cons
- Complex pricing system
- Poor customer support
8. Apache Mesos - Best for virtual machine workloads
Apache Mesos is a cluster management solution managed by the Apache Foundation. Like other products from the group, it’s completely free and open source.
Why I picked Apache Mesos: Mesos' pluggable isolation functionality separates resources like processing and memory, so you have more independent control over each and can configure them to your liking. For the VMs on which I was running Mesos, I could allocate resources more effectively while running tests across my clusters.
Apache Mesos Standout Features and Integrations
Features that made running Mesos on my VMs easier include two-level scheduling, which I used to operate both legacy and cloud-native apps inside the same clusters. This way, I could maintain my preferred resource allocation schedules without worrying about compatibility issues between the applications.
Mesos is also cloud provider agnostic, meaning I worked on my clusters knowing that I could migrate to whatever other environment I wanted, whenever I wanted, without losing anything.
Integrations are available via several APIs that you can use to build your own connections.
Pricing: Free
Trial: Free plan available
Pros
- Strong resource management features
- Completely free
- Multiple APIs
Cons
- Most users would need a framework
- Not as lightweight as other solutions
9. MicroK8s - Best for setting up Kubernetes
MicroK8s is a lightweight Kubernetes distribution for Linux systems developed by Canonical. the same company behind Ubuntu.
Why I picked MicroK8s: MicroK8s is so small it’s named for its lightweight nature. To see just how far I could take this, I decided to test it on one of my Raspberry Pi units, and I’m glad to report that it delivered. I was able to run Kubernetes with very little storage and memory usage, something that IoT-capable appliances could benefit from.
MicroK8s Standout Features and Integrations
Features that make MicroK8s ideal for IoT development include support for snaps, packages that contain an app’s code and dependencies, which work across any Linux distribution out of the box. You can also configure the snaps to be strictly confined, which means they’re fully isolated from the OS, networks, files, and other resources to enforce granular security.
Integrations are pre-built for Kubernetes, SQLite, Chef, Ansible, Puppet, and PostgreSQL.
Pricing: Free
Trial: Free plan available
Pros
- Very lightweight
- Strong local performance
- Easy to install
Cons
- Linux only
- Requires extensive configuration
10. AWS Fargate - Best for microservice development
AWS Fargate is a compute engine that allows you to run containers in a serverless setup. It heavily incorporates Amazon ECS and Elastic Kubernetes Service (EKS).
Why I picked AWS Fargate: All my tasks in Fargate had their own kernel and didn't share their memory, CPU, or elastic network interface, so it was easier to isolate them. This kind of setup was ideal for a couple of microservices I deployed because it improved fault tolerance and made it easy for me to test each one in its own environment.
AWS Fargate Standout Features and Integrations
Features that made me recommend Fargate include comprehensive monitoring through CloudWatch Container Insights, which I used to gather logs and metrics on resource usage across all my microservices. I could also rely on it for diagnostics because it notified me whenever a microservice failed and provided me with enough information to address the issue.
Fargate also supports core and full versions of Windows Server operating systems for anyone that wants some flexibility in their preferred microservice development platform.
Integrations are available natively for other AWS offerings, including ECS, EKS, and CloudWatch Container Insights.
Pricing: From $0.00356/GB/hour
Trial: Free demo available
Pros
- Robust infrastructure management features
- Effective task isolation for microservices
- Comprehensive out-of-the-box functionality
Cons
- Long cold start times
- Expensive
11. Oracle Container Engine for Kubernetes - Best threat detection features
Oracle Cloud Infrastructure (OCI) Container Engine for Kubernetes (OKE) is a managed solution that offers virtual nodes for serverless computing.
Why I picked Oracle Container Engine for Kubernetes: OKE can scan, verify, and sign container images before deploying them to clusters to ensure that they don’t still have any known security vulnerabilities.
I got the scan results as soon as the step was done, signatures were encrypted, and only containers with a valid signature got deployed to a cluster. All these combined to give me the peace of mind that my clusters were safe after they went live. OKE also supports DevOps, meaning it could integrate these steps into my pipelines with no hassle.
Features that made implementing security in my OKE deployments include the ability to limit access to the Kubernetes API endpoint and set up private clusters. This way, I was able to completely close off my on-premise environment and run vulnerability tests. OKE also provides various access management and RBAC features for workloads that allowed me to maintain finer control over who could access what and when.
Integrations are available natively with other OCI offerings such as IAM, Vault, Bastion, Audit, Dedicated Region, and DevOps, as well as pre-built for Google Anthos, Argo CD, Gitlab, and Jenkins.
Pricing: From $0.015/hour
Trial: Free plan available
Pros
- Comprehensive security features
- Easy to deploy after initial setup
- Transparent pricing model
Cons
- Complex initial setup
- Expensive
12. Nomad - Best automation features
Nomad is a container management solution from cloud infrastructure automation company HashiCorp that you can use either to replace or supplement Kubernetes.
Why I picked Nomad: I picked Nomad because of the Autopilot feature, which provides a collection of automated management functions. After I set it up, some of the things it could do for me include cleaning up dead servers, running health checks, and introducing stable servers to clusters after a probationary period.
Nomad Standout Features and Integrations
Features I liked for automation in Nomad include batch processing, which I could use for parameterized jobs and workloads at scale, with complete scheduling, to provide additional clusters whenever needed. Nomad also allowed me to deploy legacy apps to a virtual machine and integrate automation via its API.
Integrations are pre-built for Terraform, Packer, Consul, Vault, Boundary, Waypoint, Vagrant, AWS, Google Cloud Platform, and Azure.
Pricing: Pricing upon request
Trial: Free plan available
Pros
- Robust automation features
- Free plan
- Useful integrations
Cons
- Spotty documentation
- Takes a while to catch up to Kubernetes
Other Containerization Software Options
I’ve also compiled this list of containerization tools that didn’t make the top 12 but are still good enough for specific scenarios:
- Linode - Best customer service
- Azure Kubernetes Service - Best for agile development
- Amazon Elastic Kubernetes Service - Best availability
- Buildah - Best for on-premise development
- Terraform - Best Docker container deployment features
- Portainer - Best governance features
- Rancher - Best Kubernetes management
- Mirantis - Best for ZeroOps development
Selection Criteria For Containerization Software
Here’s a short summary of the main selection and evaluation criteria I used to develop my list of the best containerization software for this article:
Core Functionality
A few of the things I needed each containerization tool to be able to do include:
- Be “portable” so I could move containers between host environments
- Provide self-contained runtime environments with as few external dependencies as possible
- Be cloud-native to support deployment to the host
Key Features
To provide the core functionality I highlighted above, I prioritized containerization software with the following features:
- Isolation: This enables applications to run in an environment that’s separate from the host system and other containers.
- Security: I looked for solutions that made it easy to configure security policies and restrictions on containers to ensure software is running securely.
- Lightweight: This would make deployment and execution easier than a traditional application.
- Cross-platform compatibility: This includes both on-host and user systems with no lock-in into one or another.
Usability
I prioritized solutions that weren’t a pain to use because that would defeat the purpose of containerization as a means to simplify development. For tools that use a GUI, I needed them to be user-friendly, whereas solutions that used a code-heavy approach had to leverage features such as comprehensive documentation and readable syntax.
Integrations
I was looking for solutions that allowed you to connect to other tools that were integral to the development and deployment process. These included things like container orchestrators, IDEs, cloud platforms, and CI/CD systems.
People Also Ask
Still stuck on the fundamentals of containerization? I looked around and found some questions you might have and answered them below:
What is the purpose of containerization?
What is the difference between containerization and virtualization?
Is containerization part of DevOps?
Summary
Containerization allows you to move away from depending on an operating system so you can streamline development and potentially build a wider user base, so it makes sense that it’s the technology behind over 50% of apps. I hope the information in this article was enough to get you started with the right containerization solution for your needs.
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