Evaluating the Impact of Internal Developer Platforms on Developer Productivity and DevOps Delivery
DOI:
https://doi.org/10.63084/cognexus.v2i1.281Keywords:
Internal developer platform, platform engineering, developer productivity, developer experience, DORA metrics, software-delivery performanceAbstract
Cloud-native software development has increased the number of tools, environments, security controls and operational decisions that development teams must manage. Internal Developer Platforms (IDPs) address this complexity by providing self-service infrastructure, standard delivery workflows, approved templates and automated governance. This study evaluates how IDP adoption affects developer productivity and software-delivery performance and identifies the platform capabilities and organisational conditions associated with stronger outcomes. A systematic evidence review was conducted using Google Scholar, IEEE Xplore, ACM Digital Library, ScienceDirect and SpringerLink. The review covered literature published from 2007 to 2025 and retained 35 peer-reviewed studies, scholarly books and authoritative technical reports related to platform engineering, developer experience and DevOps measurement. Evidence was analysed using the SPACE and DevEx productivity perspectives together with DORA throughput and stability measures. The findings indicate that mature, user-centred IDPs can reduce environment-setup effort, shorten feedback cycles, improve access to infrastructure and increase deployment consistency. Self-service provisioning, reusable golden paths, integrated observability and policy automation produced the clearest benefits. However, improvements in perceived productivity did not always correspond to better delivery performance. Early or restrictive platforms were associated with migration costs, reduced developer independence, temporary throughput losses and weaker change stability. Outcomes depended strongly on platform maturity, usability, team context and the availability of alternatives for non-standard work. Organisations should therefore evaluate IDPs through a balanced combination of human, workflow and delivery measures rather than coding-output counts alone.
References
1. Bayer, F. (2024). How metamodeling concepts improve internal developer platforms and cloud platforms to foster business agility. In Metamodeling: Applications and Trajectories to the Future: Essays in Honor of Dimitris Karagiannis (pp. 1-18). Cham: Springer Nature Switzerland. DOI: https://doi.org/10.1007/978-3-031-56862-6_1
2. Cheng, L., Murphy-Hill, E., Canning, M., Jaspan, C., Green, C., Knight, A., ... & Kammer, E. (2022, November). What improves developer productivity at google? code quality. In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (pp. 1302-1313). DOI: https://doi.org/10.1145/3540250.3558940
3. Ciancarini, P., Giancarlo, R., Grimaudo, G., Missiroli, M., & Xia, T. C. (2025). The design and realization of a self-hosted and open-source agile internal development platform. IEEE Access. DOI: https://doi.org/10.1109/ACCESS.2025.3564141
4. Cuadra, J., Hurtado, E., Sarachaga, I., Estévez, E., Casquero, O., & Armentia, A. (2024). Enabling devops for fog applications in the smart manufacturing domain: A model-driven based platform engineering approach. Future Generation Computer Systems, 157, 360-375. DOI: https://doi.org/10.1016/j.future.2024.03.053
5. DeBellis, D., Storer, K., Lewis, A., Good, B., Villalba, D., Maxwell, E., ... & Harvey, N. (2024). DORA Accelerate State of DevOps 2024 Report.
6. Dursun, H. (2023, June). Full spec software via platform engineering: Transition from bolting-on to building-in. In Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering (pp. 172-175). DOI: https://doi.org/10.1145/3593434.3593440
7. Erich, F. M., Amrit, C., & Daneva, M. (2017). A qualitative study of DevOps usage in practice. Journal of software: Evolution and Process, 29(6), e1885. DOI: https://doi.org/10.1002/smr.1885
8. Forsgren, N., Humble, J., & Kim, G. (2018). Accelerate: The science of lean software and devops: Building and scaling high performing technology organizations. IT Revolution.
9. Forsgren, N., Storey, M. A., Maddila, C., Zimmermann, T., Houck, B., & Butler, J. (2021). The SPACE of Developer Productivity: There's more to it than you think. Queue, 19(1), 20-48. DOI: https://doi.org/10.1145/3454122.3454124
10. Forsgren, N., Kalliamvakou, E., Noda, A., Greiler, M., Houck, B., & Storey, M. A. (2024). Devex in action. Communications of the ACM, 67(6), 42-51. DOI: https://doi.org/10.1145/3643140
11. Garousi, V., Felderer, M., & Mäntylä, M. V. (2019). Guidelines for including grey literature and conducting multivocal literature reviews in software engineering. Information and software technology, 106, 101-121. DOI: https://doi.org/10.1016/j.infsof.2018.09.006
12. Greiler, M., Storey, M. A., & Noda, A. (2022). An actionable framework for understanding and improving developer experience. IEEE Transactions on Software Engineering, 49(4), 1411-1425. DOI: https://doi.org/10.1109/TSE.2022.3175660
13. Hicks, C. M., Lee, C. S., & Ramsey, M. (2024). Developer Thriving: four sociocognitive factors that create resilient productivity on software teams. IEEE Software, 41(4), 68-77. DOI: https://doi.org/10.1109/MS.2024.3382957
14. Jabbari, R., Bin Ali, N., Petersen, K., & Tanveer, B. (2016, May). What is DevOps? A systematic mapping study on definitions and practices. In Proceedings of the scientific workshop proceedings of XP2016 (pp. 1-11). DOI: https://doi.org/10.1145/2962695.2962707
15. Jaspan, C., & Green, C. (2022). A human-centered approach to developer productivity. IEEE Software, 40(1), 23-28. DOI: https://doi.org/10.1109/MS.2022.3212165
16. Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering.
17. Kumar, A., Nadeem, M., & Shameem, M. (2025). A Systematic Literature Review for Investigating DevOps Metrics to Implement in Software Development Organizations. Journal of Software: Evolution and Process, 37(1), e2733. DOI: https://doi.org/10.1002/smr.2733
18. Leite, L., Rocha, C., Kon, F., Milojicic, D., & Meirelles, P. (2019). A survey of DevOps concepts and challenges. ACM computing surveys (CSUR), 52(6), 1-35. DOI: https://doi.org/10.1145/3359981
19. Lwakatare, L. E., Kilamo, T., Karvonen, T., Sauvola, T., Heikkilä, V., Itkonen, J., ... & Lassenius, C. (2019). DevOps in practice: A multiple case study of five companies. Information and software technology, 114, 217-230. DOI: https://doi.org/10.1016/j.infsof.2019.06.010
20. Meyer, A. N., Barton, L. E., Murphy, G. C., Zimmermann, T., & Fritz, T. (2017). The work life of developers: Activities, switches and perceived productivity. IEEE Transactions on Software Engineering, 43(12), 1178-1193. DOI: https://doi.org/10.1109/TSE.2017.2656886
21. Mishra, A., & Otaiwi, Z. (2020). DevOps and software quality: A systematic mapping. Computer Science Review, 38, 100308. DOI: https://doi.org/10.1016/j.cosrev.2020.100308
22. Mori, V. S., & Kittlaus, H. B. (2024, June). A Framework for Managing Platforms as Products in IT Organizations. In International Conference on Digital Product Management (pp. 59-74). Cham: Springer Nature Switzerland. DOI: https://doi.org/10.1007/978-3-031-71515-0_5
23. Noda, A., Storey, M. A., Forsgren, N., & Greiler, M. (2023). DevEx: What Actually Drives Productivity: The developer-centric approach to measuring and improving productivity. Queue, 21(2), 35-53. DOI: https://doi.org/10.1145/3595878
24. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. bmj, 372. DOI: https://doi.org/10.31222/osf.io/v7gm2
25. Razzaq, A., Buckley, J., Lai, Q., Yu, T., & Botterweck, G. (2024). A systematic literature review on the influence of enhanced developer experience on developers' productivity: Factors, practices, and recommendations. ACM Computing Surveys, 57(1), 1-46. DOI: https://doi.org/10.1145/3687299
26. Rüegger, J., Kropp, M., Graf, S., & Anslow, C. (2024, September). Fully automated DORA metrics measurement for continuous improvement. In Proceedings of the 2024 International Conference on Software and Systems Processes (pp. 36-45). DOI: https://doi.org/10.1145/3666015.3666020
27. Sallin, M., Kropp, M., Anslow, C., Quilty, J. W., & Meier, A. (2021, June). Measuring software delivery performance using the four key metrics of devops. In International Conference on Agile Software Development (pp. 103-119). Cham: Springer International Publishing. DOI: https://doi.org/10.1007/978-3-030-78098-2_7
28. Shahin, M., Babar, M. A., & Zhu, L. (2017). Continuous integration, delivery and deployment: a systematic review on approaches, tools, challenges and practices. IEEE access, 5, 3909-3943. DOI: https://doi.org/10.1109/ACCESS.2017.2685629
29. Skelton, M., & Pais, M. (2025). Team Topologies: Organizing Business and Technology for Fast Flow of Value. Simon and Schuster.
30. Srinivasan, V., Rajkumar, M., Santhanam, S., & Garg, A. (2025). PlatFab: A Platform Engineering Approach to Improve Developer Productivity. Journal of Information Systems Engineering & Business Intelligence, 11(1). DOI: https://doi.org/10.20473/jisebi.11.1.79-90
31. Storey, M. A., Zimmermann, T., Bird, C., Czerwonka, J., Murphy, B., & Kalliamvakou, E. (2019). Towards a theory of software developer job satisfaction and perceived productivity. IEEE Transactions on Software Engineering, 47(10), 2125-2142. DOI: https://doi.org/10.1109/TSE.2019.2944354
32. Tilak, P. Y., Yadav, V., Dharmendra, S. D., & Bolloju, N. (2020, September). A platform for enhancing application developer productivity using microservices and micro-frontends. In 2020 IEEE-HYDCON (pp. 1-4). IEEE. DOI: https://doi.org/10.1109/HYDCON48903.2020.9242913
33. van de Kamp, R., Bakker, K., & Zhao, Z. (2023, October). Paving the path towards platform engineering using a comprehensive reference model. In International Conference on Enterprise Design, Operations, and Computing (pp. 177-193). Cham: Springer Nature Switzerland. DOI: https://doi.org/10.1007/978-3-031-54712-6_11
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