Scaling and Success of DevOps for Military Essay

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Abstract

The effectiveness of software maintenance depends on different criteria to be taken into account. The (DoD) HQDA Army G-4, a division involved in military logistics analysis, needs a robust system of interaction between developers and maintainers called DevOps. One of the gaps is the lack of precise scaling of the system, and this issue can be addressed by introducing organizational learning and software testing by checking how different workloads influence performance metrics. Relevant resources have been used, which relate to the national military sector, and specialized findings have been summarized to provide real recommendations. This work has identified initiatives to improve the success of DevOps implementation in Army G-4, particularly keeping all software running smoothly and focusing on financial investments to make good use of the available budget.

Introduction

Implementing agile software management practices aims to optimize digital operations and eliminate potential service issues. DevOps, as a practice designed to achieve these goals, is a tool for establishing the interaction between developers and maintainers, which, despite its benefits, is difficult to scale. This work is aimed at identifying the scaling principles and success of DevOps for the (DoD) HQDA Army G-4 as a structure for which a robust mechanism of control over its digital base system is an important aspect of safe activities.

Principles of Introducing DevOps in the DoD

Despite its value from the perspective of the ability to ensure the stable operation of digital infrastructure in the military industry, the introduction of DevOps has not always been considered a convenient solution. According to Kenner (2019), implementing such flexible practices implies moving from traditional management concepts, which, in turn, does not correspond to the military-industrial complex model, where the sustainability of work determines the stability of oversight methods. Nonetheless, with the move towards the innovative principles of national security, the Department of Defense has realized the relevance of the idea of ​​maintaining close contact between developers and maintainers of the digital base. Mathieson et al. (2020) argue that appropriate tools have become common in the DoD to ensure the stability of the internal infrastructure and “keep pace with the ever-increasing complexity of systems” (p. 10). However, DevOps scaling issues have remained relevant due to the lack of a specific assessment framework and approaches to analyzing performance.

Scaling of DevOps for HQDA Army G-4

HQDA Army G-4 is a special unit involved in the development and evaluation of logistics processes, programs, and policies for the national military sector. The need to scale DevOps is a valuable prospect for this department since any innovative digital solutions will inevitably affect logistics efficiency and, therefore, resource allocation. Davis and Daniels (2016) note that one of the most convenient algorithms for scaling change and calculating performance parameters is to build an effective organizational learning system. In other words, the successful training of Army G-4 personnel can help create a sustainable background for measuring DevOps productivity by understanding how the structure works and its unique characteristics. According to Wilde et al. (2016), another scaling approach is to estimate the load on internal servers and identify characteristic values ​​ranging from lowest to highest. This principle means that HQDA Army G-4 representatives can test processes within their IT system and map specific procedures with and without DevOps. This practice can help provide objective evidence of the impacts of DevOps on specific operations, including the strength and speed of influence.

DevOps for HQDA Army G-4: Ways to Succeed

For DevOps to succeed and prove its relevance to HQDA Army G-4, specific implementation conditions are to be met. Firstly, as Jones et al. (2019) state, the corresponding digital system development principle has to be promoted to introduce such a flexible software supervision strategy. All the necessary safety elements need to be integrated to prevent the failure of individual components and the suspension of process control. Secondly, all costs should be calculated to assess the feasibility of utilizing additional control algorithms. According to the researchers, “70% of a system’s total lifecycle cost is in the sustainment phase,” which explains the need to determine whether the military complex is able to financially support specialized software (Jones et al., 2019, p. 6). In case the aforementioned conditions are met, successful DevOps support in Army G-4 will be established, and the department will be able to create a stable service system for this framework without compromising its budget.

Conclusion

The (DoD) HQDA Army G-4, as the coordinator of logistics processes and policies of the national military sector, needs a sustainable system to optimize its digital base, and the effective scaling of DevOps, as a practice designed to perform these tasks, is an essential condition for achieving productivity and minimizing costs. Establishing a sustainable organizational learning program can help improve the skills of Army G-4 personnel, and system load testing may contribute to determining appropriate boundaries for low and high performance. The success of DevOps in Army G-4 depends on the resilience of the entire software and the cost-effectiveness of its maintenance.

References

Davis, J., & Daniels, R. (2016). Effective DevOps: Building a culture of collaboration, affinity, and tooling at scale. O’Reilly.

Jones, C., Doswell, J., Clark, B., Charette, R., Judy, J., & Janusz, P. (2019). New army software sustainment cost estimating results. ICEAA Annual Workshop, 1-45.

Kenner, B. T. (2019). Too agile? – DevOps software development challenges in a military environment [Unpublished master’s thesis]. University of South Carolina.

Mathieson, J. T., Mazzuchi, T., & Sarkani, S. (2020). . IEEE Systems Journal, 1-12.

Wilde, N., Eddy, B., Patel, K., Cooper, N., Gamboa, V., Mishra, B., & Shah, K. (2016). . International Journal of Software Engineering & Applications, 7(6), 01-16.

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