If you’ve been paying attention to the COBOL arena over the last year, you’ve no doubt seen that this iconic language has been the subject and focus of numerous papers and reports in the financial and public services sectors. However, we now do have a COBOL problem, with a lot of outdated code and fewer employees who know how to deal with it. Do you know COBOL was once the “in” technology or infrastructure, powering the backend systems of a slew of financial organizations and governments? Well, that is not the case now.
COBOL is rarely an organization’s only concern today, and with the correct IT strategy, there are a plethora of alternatives for transforming COBOL development and architecture to tackle ANY modern challenge.
It is projected that in the next “COBOL moment” Kubernetes will be involved. And Kubernetes will ultimately be replaced by something simpler. But who will then maintain the infrastructure that presently relies on it?
Infrastructure as code
This “COBOLization” of code is not common in all software. Companies are migrating their apps to the cloud in large numbers. They are converting monolithic programs into systems of microservices, which are frequently orchestrated by Kubernetes, in addition, to simply lift and shift.
Many of these programs will almost certainly still be operational in 20 or 30 years; they will be the “legacy apps” of the next generation. Kubernetes configuration is difficult, it requires a specialized specialty in its own right. Who will maintain the infrastructure that currently relies on Kubernetes if it gets replaced by something simpler? What happens when knowing Kubernetes isn’t enough to get a new job or a promotion? The YAML files used to configure Kubernetes are not a Turing-complete programming language like Python, but they do include code. The number of people who understand how to work with that code will certainly decrease.
Most businesses are more concerned with updating their existing systems than with looking 10 to 20 years ahead and thinking about skills shortages that may arise as a result of their decisions. And, perhaps, companies are making a wise decision when they develop with an industry standard like Kubernetes.
Kubernetes will become a legacy in the future, with all the talent shortages that entail. However, as enterprises attempt to embrace containers-enabled, microservices-driven designs, they are more concerned about existing Kubernetes talent shortages.
This is perhaps the lesson to be learned here: that organizations should incorporate as much agility into their current infrastructure as possible, and let the future keep hold of itself. To be competitive at scale in a hybrid architecture and enhance customer value, cost-effectiveness, and agility, a vast number of technical, personnel, and process decisions must be made years in advance. Even if you can afford it, you’re not going to get these perfectly. By planning for a hypothetical exodus, you pay for freedom and flexibility with feature velocity and lower your odds of reaching a point where cloud charges are even relevant to your company’s overall success.
To summarise, today’s hot Kubernetes cluster will most likely be tomorrow’s COBOL legacy infrastructure.
Kubernetes has taken off in the industry like wildfire, with more and more companies adopting it each year. Kubernetes is already being used in large-scale production by several major enterprises. This is why businesses all over the world are integrating Kubernetes, resulting in a massive demand for these two key platforms.
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Our online Kubernetes training will cover the fundamentals to advanced concepts of Docker and Kubernetes. This Kubernetes course provides you with the chance to network with industry experts, enhance your skills to meet industry and organizational requirements, and learn about real-world best practices.
In this Docker and Kubernetes Certification course, we will cover the following –
- Essentials of Docker
- Overview of Kubernetes
- Kubernetes Cluster
- Overview Kubernetes Pod
- Kubernetes Client
- Creating and modifying ConfigMaps and Secrets
- Replication Controller and Replica Set
- Exploring the Kubernetes API and Key Metadata
- Managing Specialized Workloads
- Volumes and configuration Data
- Monitoring and logging
- Maintenance and troubleshooting
- The ecosystem
Prerequisites for Docker & Kubernetes Certification
- Basic command knowledge of Linux
- Basic understanding of DevOps
- Basic knowledge of YAML programming language (beneficial, not mandatory)