When tasked with answering the question are cloud containers really more effective, factors that should be taken into account before deciding upon an answer include the purpose of deploying cloud containers, the circumstances in which cloud containers are deployed, and the desired outcomes.
Containerization has been a buzzword in the cloud computing industry since Docker was launched in 2013. Although not the first platform for creating, deploying, and running cloud containers, the launch of Docker came at a time when organizations were looking for a more effective method than Virtual Machines for deploying applications. Docker appeared to fit the bill.
Containers are faster to load, cheaper to run, and more portable than Virtual Machines because container host environments are consistent. Docker made it easier to scale cloud containers and break complex monolithic applications into smaller, modular microservices. Docker also had the advantages of being open source and coinciding with an increased demand for agility, flexibility, and scalability in software delivery.
Since 2013, the use of cloud containers has exploded. Orchestration tools have been developed to help manage vast numbers of connected containers; and, whereas the original Docker platform only supported Linux, it is now possible to build and run containers on selected Windows and Mac operating systems using Linux-compatible Virtual Machines.
But are cloud containers really more effective? The answer is it depends on why you are using them, when you are using them, and what you hope to achieve by using them. The following advantages and disadvantages should help you understand the appropriate purposes, circumstances, and objectives of cloud containers in order to determine whether they are really more effective for the tasks you have in mind.
In addition to the advantages of cloud containers mentioned above, one of the biggest benefits of containerization is the ability to optimize operating efficiency by running multiple applications in the same Virtual Machine and specifying the right amount of resources to use. This not only saves you money, but also ensures the performance of your applications is optimized as well.
The isolated nature of containerization means you can analyze different versions of application code, keep track of the differences and roll back if necessary without disrupting the whole operating system. Together with the speed of deployment, the opportunity to update and amend individual components of an application quickly improves business continuity and productivity.
The disadvantages of cloud containers vary according to who you speak with and what they are using containerization for. For example, most industry experts believe cloud containers are not suitable for scaling up and down in large volumes despite enterprises such as Google and Netflix exclusively using containers to support continuous integration and content delivery.
In most cases the industry experts are right. Network resources can come under severe stress when a significant number of large containers move throughout the network. Google and Netflix have the network resources to cope with such scenarios, but smaller enterprises will likely face issues with network configurations and capacity requirements in large-scale DevOps projects.
A further issue with large-scale container deployments occurs when containers have to interact with legacy systems that were not developed for the cloud. In these circumstances, it may be necessary to move applications or data sources from legacy systems to the cloud before cloud containers can function correctly. Then you have to ask yourself, is this an effective way to work?
When asking yourself the question are cloud containers really more effective, other factors you may need to consider are security, data storage and monitoring. Although container security is not the issue it once was, the recent discovery of more than twenty thousand unprotected container orchestration and API management systems emphasizes the need for robust security controls to be put in place.
With regard to data storage, the current generation of solutions to manage application data stored in containers can be labor intensive. Generally, storing application data in containers is not recommended and, until user-friendlier solutions are developed to overcome container data storage issues, most operations involving containers should exchange data with persistent repositories on Virtual Machines.
Finally, monitoring. Docker (and other containerization platforms) provides only very basic information about your cloud container deployments. If you need advanced data for analysis, planning and budgeting, you will need to implement a cloud management platform—ideally with policy-driven automation that can detect cloud containers with network, compatibility or security issues in order to terminate offending containers and trigger rebuilds where possible.
Are you ready for containers?