Guide To The 20 Best Containerization Software Of 2024
10 Best Containerization Software Shortlist
Here's my pick of the 10 best software from the 20 tools reviewed.
Our one-on-one guidance will help you find the perfect fit.
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.
Best Containerization Software Summary
| Tools | Price | |
|---|---|---|
| Docker | From $5/user/month (billed annually) | Website |
| Azure Container Apps | From $0.1296/month | Website |
| IBM Cloud Kubernetes Service | Pricing upon request | Website |
| Google Kubernetes Engine | From $0.10/hour | Website |
| Kubernetes | Open source project and available for free | Website |
| Oracle Container Engine for Kubernetes | From $0.015/hour | Website |
| MicroK8s | Free | Website |
| AWS Fargate | From $0.00356/GB/hour | Website |
| Amazon Elastic Container Service | Pricing upon request | Website |
| Apache Mesos | Free | Website |
Compare Software Specs Side by Side
Use our comparison chart to review and evaluate software specs side-by-side.
Compare SoftwareBest Containerization Software Reviews
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.
Pros and cons
Pros:
- Integrates with CI/CD pipelines
- Active developer community for support
- Docker Official Images make development faster
Cons:
- Steep learning curve
- Documentation isn't rich enough
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.
Pros and cons
Pros:
- Strong security
- Scalability
- Built-in analytics
Cons:
- Difficult to deploy on-premise
- Complex pricing model
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.
Pros and cons
Pros:
- Strong security
- Robust automation features
- Highly scalable
Cons:
- Only one node and cluster each in free trial
- Not stable outside IBM Cloud
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.
Pros and cons
Pros:
- Autopilot can manage most production workloads
- User-friendly interface
- Release channels make Kubernetes updates easy to install
Cons:
- Poor customer support
- Complex pricing system
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.
Pros and cons
Pros:
- Robust documentation and training
- Highly scalable
- Strong automation capabilities
Cons:
- Difficult to set up
- Practical only for large applications
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.
Pros and cons
Pros:
- Transparent pricing model
- Easy to deploy after initial setup
- Comprehensive security features
Cons:
- Expensive
- Complex initial setup
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.
Pros and cons
Pros:
- Easy to install
- Strong local performance
- Very lightweight
Cons:
- Requires extensive configuration
- Linux only
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.
Pros and cons
Pros:
- Comprehensive out-of-the-box functionality
- Effective task isolation for microservices
- Robust infrastructure management features
Cons:
- Expensive
- Long cold start times
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.
Pros and cons
Pros:
- High availability
- Several native AWS integrations
- Robust network and traffic management features
Cons:
- Struggles outside AWS
- Poor logging
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.
Pros and cons
Pros:
- Multiple APIs
- Completely free
- Strong resource management features
Cons:
- Not as lightweight as other solutions
- Most users would need a framework
Other Containerization Software Options
I’ve also compiled this list of containerization tools that didn’t make the top 10 but are still good enough for specific scenarios:
- OpenShift Container Platform
For on-premise deployments
- Nomad
Automation features
- Amazon Elastic Kubernetes Service
Availability
- Rancher
Kubernetes management
- Buildah
For on-premise development
- Portainer
Governance features
- Terraform
Docker container deployment features
- Linode
Customer service
- Mirantis
For ZeroOps development
- Azure Kubernetes Service
For agile 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.
Subscribe to The CTO Club newsletter for more guides and tips like these.