By Arjun Mehta
As your engineering organization grows, you face a problem: onboarding is taking longer, developers are spending time on infrastructure instead of features, and every team is solving the same problems independently.
One team builds a deployment pipeline. Another builds monitoring. A third builds secrets management. Each creates their own solution, and none of them work together well.
That's when platform engineering starts to make sense. Platform engineering is the practice of building internal developer platforms (IDPs)—tools and infrastructure that make your developers faster and happier.
A good internal developer platform lets a developer with no ops experience:
- Deploy a service to production in one command
- Get immediate feedback about performance and errors
- Add monitoring and alerting without thinking about it
- Scale horizontally when needed
- Know exactly what's running and who has access
Without a platform, each team invents these things. With a platform, they come for free.
What Is Platform Engineering?
Platform engineering is creating a "paved road" for developers. Instead of saying "build whatever you want with whatever tools you want," you say "here's the standard way we build and deploy services. It handles the common cases. If you need something different, talk to us first."
This creates:
Consistency: Services use the same standards, making it easier for engineers to move between teams.
Speed: Developers don't reinvent deployment, monitoring, and scaling. The platform handles it.
Safety: The platform enforces best practices (security, logging, error handling). It's hard to do things wrong.
Visibility: Ops teams know what's running where and why.
Platform engineering doesn't mean everyone uses the same programming language or tech stack (though there are benefits to some consistency). It means everyone uses the same deployment pipeline, monitoring, and operational practices.
When to Build an Internal Developer Platform
Building a platform takes effort. You need people dedicated to it. You need buy-in from engineering teams. You need to maintain it as your infrastructure changes.
Don't build a platform if:
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You have fewer than 20-30 engineers. The overhead of maintaining a platform outweighs the benefits. Each team managing their own infrastructure is fine.
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Your infrastructure is simple and stable. If you can deploy with a shell script and nothing breaks, you don't need a platform yet.
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You're changing infrastructure frequently. Wait until you're settled on how you want to deploy, scale, and monitor.
Build a platform if:
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Onboarding is slow. New engineers take weeks to understand how to deploy their code.
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Infrastructure work is stealing time from features. Engineers are spending 20%+ of time on ops instead of product.
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Teams are creating conflicting solutions. Team A uses Kubernetes, Team B uses Lambdas, Team C runs VMs. The conflicts cost engineering time.
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Operations is overwhelmed. Your ops team can't support 50+ engineers making ad-hoc infrastructure requests.
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You're losing engineers to frustration. Engineers are leaving because infrastructure work is painful.
The Core Components of an IDP
1. Deployment Pipeline
A developer should be able to deploy with one command. The platform should:
- Build their code
- Run tests
- Push to a registry
- Deploy to production (or staging first)
- Monitor the deployment for issues
Developers shouldn't need to know about Docker, Kubernetes, or CI/CD. They commit code, and the platform handles the rest.
2. Observability
Every service should automatically get:
- Basic monitoring (CPU, memory, request count)
- Logging (structured logs collected automatically)
- Tracing (requests traced through the system)
- Alerting (notify on-call when something breaks)
Developers shouldn't have to instrument their code to get basic observability.
3. Configuration and Secrets Management
Developers need to manage configuration (database connection strings, API keys, feature flags). The platform should provide:
- A safe place to store secrets (encrypted)
- A way to inject them at runtime
- Environment-specific configuration
- Auditing of who accessed what
4. Infrastructure Abstractions
Instead of asking developers to provision servers, the platform provides abstractions:
- "I want a web service that scales based on load"
- "I want a background job queue"
- "I want a database"
The platform handles the details of how that's implemented.
5. Networking and Security
The platform handles:
- How services communicate with each other
- How external traffic gets routed
- TLS/encryption in transit
- Access control (who can call what)
- Network security boundaries
6. Development Environment
The platform gives developers:
- A local environment that mimics production
- Easy access to databases and dependencies
- A way to test integrations before deploying
- Documentation on how to build and run locally
Building Your First IDP
Don't try to build everything at once. Start with what's causing the most pain.
Phase 1: Deployment Pipeline
Your first priority is making deployment fast and reliable. Build CI/CD that lets developers deploy with a command. This alone will massively improve productivity.
Phase 2: Observability
Once deployment is fast, add automatic observability. Services should automatically emit metrics, logs, and traces. Developers shouldn't have to think about it.
Phase 3: Configuration and Secrets
Add a system for managing configuration and secrets. This is critical for security.
Phase 4: Infrastructure Abstractions
Abstract infrastructure. Instead of "provision a Kubernetes cluster," offer "create a web service." Hide the complexity.
Phase 5: Development Environment
Build tools that let developers develop and test locally in an environment that closely matches production.
Each phase takes weeks or months depending on your scale. Don't rush. Build what solves the most pain first.
Tools and Platforms
You don't need to build everything from scratch. Many platforms exist:
Heroku-style platforms:
- Vercel (frontend)
- Netlify (frontend)
- Render (full-stack)
These abstract away infrastructure entirely. Good if your needs fit their model.
Kubernetes-based:
- Helm (packages and configuration)
- Pulumi (infrastructure as code)
- ArgoCD (deployment automation)
These give you control with less manual work.
Open source platforms:
- Backstage (developer portal, standardized templates)
- Terraform (infrastructure as code)
- Dagger (CI/CD)
You can assemble these into a platform for your organization.
Managed services:
- AWS, GCP, Azure provide managed services (RDS for databases, Lambda for serverless, etc.)
You build a platform using these services.
Most organizations use a mix: managed services for the hard stuff (databases, message queues) plus custom tooling for how they do deployments and operations.
The Platform Team
Building a platform requires dedicated people. You need:
Platform engineers: People who understand infrastructure, understand what developers need, and can build tooling.
Product mindset: Treat the platform like a product. Your customers are engineers. Listen to what makes them faster or slower.
Documentation and education: A platform only works if developers understand how to use it. Invest in docs and onboarding.
Continuous improvement: Your platform will never be complete. Prioritize improvements based on what slows engineers down.
A platform team of 2-3 people can support 30-50 engineers. Beyond that, you might need more.
Challenges with Platform Engineering
Over-engineering: Building a platform that handles 99% of cases you'll never encounter. Start simple. Add complexity when you hit real problems.
Platform adoption: If developers don't trust the platform or find it limiting, they'll work around it. Make the "paved road" so good that developers choose it.
Lock-in: A platform that's too rigid locks you in. Leave escape hatches for teams with unusual needs.
Maintenance burden: A platform creates a dependency. If it breaks, everyone is blocked. Make sure platform reliability is a priority.
Keeping it current: As your infrastructure evolves (new Kubernetes versions, new services, etc.), the platform needs to evolve too.
Measuring Platform Success
How do you know if your platform is working?
Deployment frequency: Can developers ship faster?
Mean time to recovery: When something breaks, can you fix it faster?
Developer productivity: Are engineers spending more time on features and less time on infrastructure?
Engineer satisfaction: Are developers happy with the platform? Would they recommend it to other teams?
Onboarding time: How long does it take a new engineer to ship their first feature?
Track these metrics. If they're not improving after 6 months, the platform isn't working.
Platform Engineering and Codebase Intelligence
Tools like Glue help platform engineers understand their infrastructure. By analyzing your codebase, you can see how services are coupled, what teams own what, and where architectural issues exist. This informs platform decisions: what abstractions to provide, where to add safety guards, what to monitor.
Frequently Asked Questions
Q: Isn't a platform just more bureaucracy?
A: Bad platforms are. Good platforms remove friction. If your platform slows developers down, it's not working. The goal is to make the common case effortless.
Q: Do developers lose autonomy with a platform?
A: Good platforms provide freedom within guardrails. They handle the boring stuff (deployment, monitoring, security) automatically so developers can focus on product. Developers unhappy with the platform should be listened to. Maybe you need to add an escape hatch.
Q: What if we outgrow our platform?
A: Platforms evolve. Version them. Let different teams use different versions if needed. When your infrastructure changes, migrate gradually.
Q: Can we build a platform if we use multiple cloud providers?
A: It's harder, but possible. Tools like Pulumi abstract across clouds. You might need to handle some multi-cloud complexity, but a good platform can still simplify things for developers.