DevOps implementation rises with need to improve reliability & fill loopholes in processes

There have been rising need for DevOps for various applications and the implementation has increased significantly as it helps in enhancing reliability and filling out the collaboration gap between teams.

Enterprises have realized the significance of DevOps and began implementation for various applications. After weighing in its pros, they have made the decision to improve operational efficiency with its implementation. One of the applications is improvement of website reliability. The online gambling company bet365 started new department that would implement DevOps practices. The implementation carries out collaboration of different operational teams to determine new ways of operation, principles, and technologies. This will enable automation, raise monitoring capabilities, and improve deployment pipelines. The technology unit of bet365, Hillside Technology, has been developing site reliability engineering team. Steven Briggs, the Head of DevOps at Hillside Technology, outlined that the complexity of technologies and platform has increased significantly with widening scale and scope of its business. He added that the DevOps approach would help the company in keeping up pace with relentless requirement of releasing software. The company intends to offer dashboard, tooling, and automation required to enhance value. It emphasized on ensuring live system fits the purpose. However, the issues solved by DevOps have not been issue for them. The DevOps implementation would help the company in optimizing release processes, progressing automation, and establishing a monitoring network.   

The tech giant IBM also began implementation of DevOps for development of AI-infused applications. It added drift detection capability to the Watson OpenScale platform to manage AI models. Rohan Vaidyanathan, the Program Director for IBM Watson OpenScale, outlined that one of the largest AI issues faced by organizations is lack of capability to identify the time to update or replace the AI model. This new addition will enable continuous monitoring ability to determine how much the AI model has been shifted from its original parameters. The drift takes place in AI models with time as use cases changes in unexpected ways. Once the drift is determined, the AI models need to be retrained or replaced. The process involves development of AI applications with putting the right data for training the model and then integrate the model in application. Moreover, the results may be different with each interaction with AI model as machine learning algorithms learn with process. However, only one of 20 models proceed to production as organizations have not bridged the gap between data scientists and DevOps teams. This drift detection capability will be a missing link between those two teams and they can collaborate more closely than before.

There have been rising need for DevOps for various applications and the implementation has increased significantly as it helps in enhancing reliability and filling out the collaboration gap between teams of an organization. According to the research firm Allied Market Research, the DevOps market is estimated to reach $9.40 billion by 2023. Organizations have been zoning in DevOps with the need to improve efficiency and maintain operational processes. In the future, there will be more instances of implementation as it solves various issues within the organization and enables smooth operations.

Reference:

information-age.com

devops.com

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