Containerization holds promise in driving digital transformation for organizations. It is important for CIOs to ensure that their containerization-based projects perform without interference when they go into production. They must consider the way they make changes to the infrastructure for ensuring the availability of enough storage and compute capacity for supporting containerized applications.
The essence of containerization and its management for organizations is being prepared for changes entailed by advances in application development. Organizations that embrace the container technology are touted to realize accelerated cloud and digital transformation. While using containers ensures organizations that their applications are cloud-enabled and ready to seamlessly shift between deployment environments as and when required.
The Blend of Containers and DevOps
Organizations look to automate as many processes as possible by adopting DevOps and depend on automation scripts for moving the code. While automated deployment processes take place, the build is deployed on the next environment, such as QA or integration. Key metrics that the operations team must consider here are performance and impact of changes post-deployment, along with the availability of required compute, memory, networking, and storage capacity.
When organizations deploy cloud-based, modern, containerized applications, the window for changes is much smaller and leads to making IT operations complicated. This is where real-time monitoring of containers comes into play. The operations team can leverage historical and real-time analytics of containers across cloud, virtual, and physical environments. This further helps organizations in creating performance benchmarks and make informed decisions for the infrastructure.
Containerization Is An Indispensable Step for Organizations
Organizations that have embraced digital transformation realize that a decentralized approach is essential for addressing their infrastructure requirements. According to Gartner, close to 75% enterprise-generated data will be created and processed outside traditional centralized data centers. Large amounts of data are gathered and analyzed by organizations for taking impactful decisions.
Containers are lightweight, have a low footprint, and are ideal for running on the cloud. The containerization technology allows legacy services to collaborate with modern cloud services, such as artificial intelligence (AI) and machine learning (ML), and achieve rapid on-demand computation. This is a major reason why several ML models leverage containers. Also, containerization of applications enables the architecture to evolve from waterfall development-based monolithic code bases to independently-deployed and loosely-coupled microservices.
Using containers, organizations can unlock their complete potential, providing the base for exceptional flexibility in meeting internal as well as external business demands. Organizations that eye the adoption of containers realize more than just a technological change, bringing a change in their work culture. Results of containerization have been so immensely beneficial for organizations that they are banking on this technology for new IT strategies.
To Sum Up
It will not be an overstatement to say that the capabilities of containerization to transform development processes are analogous to how physical container shipping changed global commerce. Modern development pipelines are automated and continuous and containers ensure the delivery of reliable and secure applications. They also help in accelerating the onboarding of applications, deploying AI workloads, and enhancing DevOps, while keeping everything under control.