Why are platform engineering best practices important?
Platform engineering best practices involve building and operating an internal developer platform to simplify software development. Key principles include prioritizing developer experience, automating tasks, and fostering a culture of continuous improvement. These practices aim to empower developers, increase productivity, and ensure consistent, reliable, and secure application delivery.
In this article, we’ll cover the following best practices:
- Prioritize developer experience: Make platforms intuitive, consistent, and easy to use so developers can focus on shipping features instead of managing complexity.
- Embed security and compliance by default: Enforce secure defaults and automated compliance checks so teams don’t need to retrofit controls later.
- Build for scalability and reliability: Design with patterns that handle growth, load, and failures without disrupting developer workflows.
- Do everything to reduce overhead: Eliminate repetitive manual work through templates, automation, and abstractions that hide unnecessary infrastructure details.
- Use self-service and automation: Provide safe, role-based self-service capabilities backed by automated workflows to increase delivery speed and consistency.
- Don’t build it all yourself: Reuse proven open-source and commercial tools where possible, and reserve custom development for areas with unique business value.
- Measure outcomes with metrics and feedback loops: Track usage, performance, and developer satisfaction to identify gaps and guide improvements.
- Ensure observability and plan for Continuous Delivery: Standardize pipelines and provide unified monitoring so teams can release confidently and troubleshoot quickly.
- Design for resilience with chaos engineering: Validate recovery strategies through controlled fault injection and build resilience patterns into platform templates.
- Continuously improve and evolve: Treat the platform as a product, adapting to new needs, reducing technical debt, and refining workflows over time.
1. Prioritize developer experience
Developer experience (DX) is central to successful platform adoption. A platform that’s hard to use, poorly documented, or inconsistent will be avoided or misused, regardless of how technically powerful it is. Platform teams must design with empathy, minimizing the time and effort developers spend on non-core tasks like setting up pipelines, configuring environments, or debugging deployment issues.
Well-structured interfaces—such as clean APIs, intuitive dashboards, and developer-friendly CLIs—improve usability. Providing SDKs and client libraries in multiple languages further lowers the barrier to entry. Teams should conduct regular developer interviews, surveys, and shadowing sessions to identify pain points and usability issues.
Examples of good DX include providing default templates for common service types, automated onboarding scripts, sandbox environments for experimentation, and instant feedback mechanisms in CI/CD pipelines.
2. Embed security and compliance by default
Security should not be bolted on—it must be embedded into the platform’s architecture from the start. This means enforcing secure defaults, such as using TLS for all communications, applying least-privilege principles for IAM roles, and ensuring that secrets are never stored in source code.
Compliance requirements like SOC 2, ISO 27001, or HIPAA should be addressed through automation. For example, use policy-as-code tools (e.g., Open Policy Agent) to enforce tagging, encryption, or access controls. CI/CD pipelines should include automated security scans (e.g., SAST, DAST, dependency scanning) and infrastructure compliance checks.
Auditability is key. Every platform action—such as provisioning resources or deploying services—should be logged and traceable. Centralized logging, audit trails, and immutable artifact storage help satisfy compliance and investigation requirements.
By baking in security and compliance, platform teams reduce risk and avoid reactive, last-minute fixes during audits or incidents.
3. Build for scalability and reliability
As organizations grow, platforms must support increasing workloads, more teams, and more complex systems. Scalability is not just about horizontal growth but also about maintaining consistent performance and stability under load. Platforms should be designed using scalable patterns like stateless services, asynchronous processing, and distributed systems principles.
Reliability is equally critical. Platforms should follow principles like graceful degradation (where services remain partially functional during failures), redundancy across zones or regions, and proactive health checks. Use of Kubernetes with autoscaling, service meshes like Istio for traffic management, and cloud-native infrastructure (like managed databases or queues) helps achieve these goals.
Monitoring saturation metrics (CPU, memory, queue depth) and setting SLOs and SLIs allows teams to anticipate issues before they impact users. A reliable, scalable platform enables teams to deploy at high velocity without sacrificing performance.
4. Do everything to reduce overhead
Every manual step in a developer’s workflow adds cognitive load and slows down delivery. Platform engineering should aim to eliminate this friction by providing reusable components and automated workflows that cover the full software lifecycle—from project creation to deployment and monitoring.
Reusable service templates (e.g., Node.js microservice, Python API, frontend React app) pre-configure best practices like logging, tracing, health checks, and CI/CD setup. Secrets management should be handled through integrations with vault systems, and service configuration should be declarative and version-controlled.
Productivity also improves when developers are not burdened with infrastructure concerns. By abstracting infrastructure layers behind APIs or CLI commands, developers can deploy services without needing to know about VPCs, subnets, or ingress rules.
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5. Use self-service and automation
Self-service is a cornerstone of effective platforms. When developers can provision infrastructure, create services, and push code independently, overall delivery velocity increases and bottlenecks are reduced. Platform teams should expose capabilities through self-service portals or API gateways with secure role-based access.
Automation ensures repeatability and minimizes human error. Infrastructure-as-code (e.g., using Terraform or Pulumi), CI/CD pipelines (e.g., GitHub Actions, Argo CD), and automated secrets rotation are essential. Approval processes and policy enforcement can also be automated using tools like OPA/Gatekeeper.
Crucially, self-service should be safe. Platform teams must provide clear guardrails, including quotas, audit logging, and validation rules, so developers can move quickly without compromising security or reliability.
6. Don’t build it all yourself
Platform teams often face pressure to build custom tooling, but this can quickly lead to high maintenance costs and slow delivery. Before developing anything in-house, assess whether existing open-source tools or commercial platforms meet your needs. Reusing battle-tested solutions reduces the risk of bugs, improves reliability, and speeds up implementation.
Invest time in integration, not reinvention. Instead of building your own CI/CD tool, customize a system like Argo CD or Octopus Deploy to fit your workflows. Use tools like Backstage for developer portals or Crossplane for infrastructure composition, rather than building equivalents from scratch.
When custom development is necessary, scope it narrowly and ensure it aligns with team priorities and user needs. Focus internal development efforts on areas where differentiation matters and where no off-the-shelf solutions exist.
7. Measure outcomes with metrics and feedback loops
Without measurement, it’s impossible to improve. Platform teams should track both system-level metrics (e.g., uptime, latency, error rates) and user-centric metrics (e.g., deployment frequency, time to onboard, feature lead time). These KPIs help evaluate platform health and ROI.
User feedback is equally important. Regular interviews, surveys, Net Promoter Score (NPS), and even in-platform feedback widgets can provide insight into how well the platform meets developer needs.
Instrumentation should be built into every service and pipeline the platform provides. Tools like Prometheus, Grafana, and Honeycomb can surface patterns and trends. Feedback loops should be short, ensuring insights are translated into improvements quickly.
8. Ensure observability and plan for Continuous Delivery
Observability enables developers and operators to understand what’s happening in a system. A good platform should provide consistent logging (structured logs), metrics (latency, throughput, error rates), and traces (distributed tracing) out of the box. Logs should be centralized, searchable, and accessible in real time.
Continuous Delivery pipelines should be standardized, templated, and secure. This includes automating environment creation, running test suites, security checks, and deploying artifacts to staging and production. GitOps-based workflows with tools like Flux or Argo CD help maintain consistency and traceability.
Integrated observability and CI/CD allows teams to release confidently and react quickly to issues, reducing mean time to resolution (MTTR).
9. Design for resilience with chaos engineering
No system is perfect, and failures are inevitable. Resilience means the platform can handle failures gracefully and recover quickly. Chaos engineering validates this by intentionally introducing faults and measuring system response.
Experiments can include shutting down services, introducing latency, or simulating network partitions. Platforms like Gremlin or Chaos Mesh support this kind of testing. These experiments should be automated and safe, ideally running in non-production or isolated environments.
Building resilience also includes strategies like circuit breakers, retries with backoff, idempotent operations, and bulkheads. These patterns should be included in platform templates so that all services benefit from them without additional engineering effort.
10. Continuously improve and evolve
The platform should be treated as a product, with a roadmap, backlog, and user research process. Just as product teams iterate based on usage data and feedback, platform teams must continuously refine and expand capabilities in response to changing needs.
Technical debt should be tracked and managed systematically. Regular evaluations of tools, architecture decisions, and workflows help ensure the platform doesn’t become outdated or brittle. This might involve migrating to new orchestration platforms, adopting new observability tools, or evolving governance policies.
Strong platform teams foster a culture of experimentation, learning from failures, and sharing knowledge across teams. Documentation, internal demos, and platform office hours all support this ongoing evolution.
Solving the Custom Platform Engineering Crisis with Octopus Platform Hub
Platform Hub in Octopus provides the foundation your team needs to deliver a world-class developer experience without years of engineering overhead. Instead of cobbling together disparate tools and maintaining fragile custom integrations, Platform Hub offers a unified interface where developers can self-service deployments, provision infrastructure, and manage releases across any cloud or on-premises environment. Your platform engineering team can focus on strategic initiatives rather than firefighting toolchain issues, while developers gain the autonomy they need to ship faster.
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