How To Face Changes In The Management Of Technological Resources In Companies
The management of technological resources in companies has changed significantly throughout the short (but intense) history of computing. Until a few years ago, when embarking on a new development, one of the biggest headaches was the management of machines associated with the project. This problem became even more complicated when working in Big Data since the resources required for such projects are much higher.
From the purchase to the rental of technological resources
When purchasing a new server, a balance had to be found. On the one hand, the server had to provide enough resources to allow the product to grow in the future. On the other hand, the more resources it had, the higher the cost the company had to assume if it wanted to embark on a new development.
In this way, there was the risk of paying a large amount of money for resources that would never be used or of falling short in the estimates and having to purchase a new server in the future so that the project could continue to grow. Today, companies such as Amazon (Amazon et al.), IBM (IBM Cloud), and Microsoft (Azure), among others, offer their “server farms” as a service (Platform as a Service or PaaS).
With this new model, a company can contract a machine with certain technological resources, entirely abstracting from its physical management. In addition, this service can be contracted for as long as desired, so if a software product reaches the end of its useful life, the company will not be left with physical resources that are not being used. If, on the contrary, said project begins to grow and requires more resources, it is as easy as contacting the provider and modifying the servers so that they better fit the product at all times.
However, all these changes in server management also have their drawbacks. Today it is much easier to manage servers with resources that are better suited to the project’s needs at all times, and therefore, you work with many more machines than before.
The problem of the configuration of technological resources
Each server we work with needs to be configured for our project to work correctly: software dependencies, version dependencies, QR codes, security management in accessing them, etc. Moreover, this task consumes much time and can lead to unexpected problems when deploying a project (inaccessible servers, components incompatible with certain Operating Systems, outdated programs without technical support, etc.).
Docker to save company resources.
This is where tools like Docker can save a company many resources. Docker is a lightweight virtualization tool that makes it possible to package software with its dependencies, thus considerably simplifying its deployment on different servers.
Docker also makes it easy to split a project into different packages and manage the transfer of information between them easily (using tools like Docker Compose and Kubernetes), simplifying the management of scalability in a project.
In addition, other tools, such as Jenkins, allow us to easily automate the production deployment of new versions of our project. This automation process is also known as continuous integration. Monitoring this process makes it easy to detect any problems that may occur quickly and act accordingly.
Thanks to these new services and technologies, Software process management continues to streamline. This optimization brings more value to the company’s software solutions, so it is essential that the company stays up-to-date and analyzes new technologies in search of opportunities. In this way, Big Data projects become more manageable, making it easier for the company to manage its resources efficiently.
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