The role of Containers in Data Storage
Operating system virtualisation has been the method in which software is used to allow computer system hardware to run multiple operating systems simultaneously on one computer. Server virtualisation allows many virtual servers to run on one physical machine without having contact with other software on the system.
The newer mode of operating system virtualisation technologies are mainly focused on providing a moveable, recyclable and automatable method of packaging and running applications. Containers have built-in executables like libraries, binary code, configuration tables and do not contain operating system images. This makes containers more lightweight and cost-effective.
According to a survey conducted by Portworx, IT managers shared their dependence on containers to improve their responsiveness, aid in cost reduction and to monitor system performance for improvement.
Data containers vs. Virtual Machines
Data volume containers are created to be stateless, weightless tools with their sizes and weights are measured in megabytes. The development of data containers has made virtual machines (VMs) out-dated and too cumbersome. A virtual machine server hosts several VMs at once to facilitate the simultaneous processing of tests or procedures – but it is isolated from other software on your computer.
Containers are regarded as a cost-effective, lightweight alternative to VMs in that it runs multiple workloads on a single operating system and use less memory than Virtual machines.
Companies install hundreds of containers to speed up the development process in integrating new product aspects into production. The system, though relatively easy to set up, requires on-going cyber management that comes with its own set of complexities.
Garbage Collection Algorithms
The lifecycle of containers is unstable and they automatically get deleted when its use has expired. The data, however, persists and is termed ‘orphaned volumes’. Garbage Collection algorithms are computer science’s innovative approach to automatic memory management. It involves a process of ‘heap allocation’ whereby dead memory blocks are identified, removed and storage reallocated for reuse.
The Data volume containers (the main catalysts between a myriad of containers) can still be directly accessed by the host to collect orphaned data as required. It is during this process that security issues become relevant in that potentially sensitive data can become vulnerable.
Challenges with the utilization of data containers
- Lack of skilled human resources.( attracting and retaining skilled talent in the industry is a challenge).
- Rapid changeability in Cyber Technology eco-system
- Organisational lethargy and lack of will
- Uninformed choice of Technologies:
- Lack of planning Implementation Strategy
- Container Monitoring and management
- Container Security and data vulnerability
Cyber experts offer the following advice to secure your containers.
- Container’s software cannot always be trusted
- Know exactly what is happening in your containers
- Control the root access to your container
- Container runtime should be checked
- The operating system must be locked down.
- Container lock-down
Recommendations for building persistent storage
It is recommended as a best practice that data management is separated from containers. The thinking behind this is that data will not be terminated with the container’s lifecycle.
Storage plug-ins – The thinking in some tech environments is that the most reliable and manageable choice to ensure data persistence, are storage plug-ins.
Some efficient tools and platforms on the market can build and create software inside containers. The plug-ins simplify the management and consumption of data volumes from any host and to consume existing storage.
Conclusion
The best is for every company to explore the available tools and platforms on the market suited to their requirements to safeguard their containers and data storage.
