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# Retooling and refactoring - an investment in people.

Cloud migrations frequently stall because complex abstractions paralyze developers. Fix this by treating foundational platform refactoring as a direct, hands-on investment in your engineering team's continuous education.

- **Speakers:** Andrew Holway
- **Event:** WeAreDevelopers LIVE
- **Published:** April 6, 2022
- **Duration:** 50:23
- **URL:** https://www.wearedevelopers.com/videos/371-retooling-and-refactoring-an-investment-in-people

## Summary

Adopting new technologies—such as migrating from legacy Python architectures to high-performance Golang or orchestrating microservices—frequently stalls out because traditional agile methodologies are ill-equipped for foundational technology transitions. Relying on isolated research spikes puts enormous pressure on individual developers, while abstract corporate training quickly fades due to the exponential forgetting curve. Because software engineering relies heavily on tacit, tool-using knowledge, technical mastery must be cultivated continuously and directly on the job rather than in detached, out-of-context classroom environments.

To properly execute infrastructure modernization, organizations should treat retooling as an instructional design challenge that prioritizes the collaborative educational outcomes of their engineering teams. Uncovering the "happy path" for complex ecosystems like Kubernetes, Docker, or Elasticsearch allows product teams to bypass the noise of fragmented open-source documentation. Overcomplicating early cloud migrations with dense infrastructure-as-code abstractions like Terraform or Helm can actually paralyze teams; in many cases, stripping deployments back to fundamental AWS CLI or direct `kubectl` commands restores momentum and accelerates learning.

True technological capability must be retained internally, avoiding the trap of traditional outsourcing that intrinsically strips architectural ownership away from core staff. By delivering targeted skill sprints that leave internal teams with working CI/CD pipelines and independent branch deployments, organizations build sustainable autonomy. Ultimately, eliminating siloed infrastructure roles in favor of a "if you build it, you run it" culture empowers developers, dramatically lowers staff churn, and ensures that platform refactoring fundamentally serves as a long-term investment in people.

**Keywords:** instructional design for engineering, software developer tacit knowledge, combatting the forgetting curve, technology adoption happy path, developer-driven devops ownership, kubernetes orchestration patterns, golang concurrency migration, legacy codebase microservice refactoring, ci/cd pipeline autonomy, aws cli deployment simplicity, internal capability cultivation, engineering team skill sprints, cloud infrastructure simplifications, continuous professional development, on-the-job technical upskilling

## Chapters

1. **Applying instructional design to technical knowledge acquisition** (00:00) — Using structured instructional design transforms the acquisition of difficult technical paradigms into deliberate, trackable learning outcomes.
1. **Why agile frameworks fail at new technology adoption** (01:51) — Relying on short research spikes places undue pressure on solo engineers and fails to surface optimal architectural patterns.
1. **Limitations of traditional training and external technical consultants** (05:54) — Traditional abstract IT training ignores the forgetting curve, while outsourcing externalizes tacit tool-using knowledge.
1. **Case study on adopting Kubernetes and Golang effectively** (08:58) — Providing a clear, simple deployment pattern cleanly unblocks legacy migration efforts into modern Kubernetes clusters.
1. **Automating infrastructure to eliminate traditional DevOps roles** (10:31) — Leveraging Kubernetes effectively allows developers to own their deployment lifecycles without handing off work to dedicated DevOps engineers.
1. **Simplifying cloud infrastructure by avoiding complex configuration tools** (12:07) — Dropping heavy orchestration tools like Terraform or Helm for native CLIs directly reduces unneeded declarative abstraction layers.
1. **Separating platform provisioning from application development concerns** (14:08) — Isolating deployment complexity strictly inside Kubernetes allows application developers to independently own schemas and CI/CD pipelines.
1. **Comparing cloud providers and their learning curves** (16:14) — Why simpler default setups in Google Cloud Platform reduce corporate dependencies on specialized platform engineers compared to AWS.
1. **Building internal capabilities through structured organizational skill sprints** (18:42) — Delivering on-the-job educational outcomes ensures teams deeply assimilate new architectural patterns without building permanent vendor dependence.
1. **Insights on transitioning from supercomputing to technical education** (24:01) — How an early career building high-performance computing systems organically shaped a shift towards structured software engineering education.
1. **Refactoring a complex legacy monolith into microservices** (26:06) — How sequentially adopting Kubernetes, modernizing Elasticsearch, and transitioning to Golang solved deep architectural debt for a legacy application.
1. **Convincing organizations to actively invest in engineering skills** (29:06) — Aligning technical learning paths directly with business goals secures corporate funding and structured time for holistic developer growth.
1. **Accelerating productivity and technology adoption in new teams** (35:38) — Pre-defining broad architectural compliance guidelines reduces initial team storming and heavily accelerates project time-to-first-value.
1. **Identifying and advocating for new technical skill requirements** (39:06) — Drafting clear educational roadmaps enables individual developers to effectively pitch large-scale stack migrations directly to executive leadership.
1. **Critical infrastructure and performance skills for modern developers** (41:54) — Mastering CI/CD, database indexing, and SQL query optimization ensures software engineers can efficiently architect and deploy robust codebases.
1. **Evaluating the future of container orchestration and virtualization** (45:31) — A fundamental shift in containerization technology is strictly required before any meaningful new alternative to Kubernetes can emerge.
1. **Leveraging instructional design to improve technical knowledge transfer** (48:25) — Applying formal instructional design principles is ultimately essential for cultivating diverse engineering teams and rapidly onboarding junior developers.

## Related Moments

- [Rethinking corporate training platforms for technical teams](https://www.wearedevelopers.com/videos/373-seriously-gaming-your-cloud-expertise-from-cloud-tourist-to-cloud-native) (from "Seriously gaming your cloud expertise: from cloud tourist to cloud native")
- [Using failed adoption to drive necessary architectural improvements](https://www.wearedevelopers.com/videos/100233-when-human-meets-canary) (from "When human meets canary")
- [Transitioning from software engineering into a DevOps trajectory](https://www.wearedevelopers.com/videos/547-how-to-gitops-your-cluster-with-flux) (from "How to GitOps your cluster with Flux")
- [Fostering team collaboration through common infrastructure abstractions](https://www.wearedevelopers.com/videos/182-gitops-keeps-focus-on-apps-not-on-infrastructure) (from "GitOps keeps focus on apps, not on infrastructure")
- [Introduction to cloud native infrastructure and platform engineering](https://www.wearedevelopers.com/videos/885-platform-engineering-vs-devops-why-not-both) (from "Platform Engineering vs. DevOps Why not both?")
- [Summarizing the organizational benefits of platform engineering](https://www.wearedevelopers.com/videos/885-platform-engineering-vs-devops-why-not-both) (from "Platform Engineering vs. DevOps Why not both?")

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