Public cloud platforms offer speed, scale, and convenience, especially for AI workloads requiring large compute resources. But there’s a catch: visibility and control degrade quickly. Just like a massive house party — it’s brilliant fun, but you still have no idea who’s in the kitchen. Maybe it’s those new neighbours again, and they’ve eaten all the lemon drizzle cake you made for the school fair.
When you fully depend on managed services or proprietary infrastructure, it becomes difficult to:
- Monitor exactly how and where data is processed
- Define consistent access policies across services
- Detect misconfigurations or silent failures
This is especially problematic for regulated sectors (finance, healthcare, public services) or where data sovereignty matters.
A platform engineering approach, underpinned by an Internal Developer Platform (IDP), restores control and visibility by creating a standardised, governed layer on top of public cloud services. This ensures that while developers can leverage the cloud’s power, they do so within safe, pre-defined guardrails.
Embrace Hybrid- or Multi-Cloud Strategies:
- A platform team can provide a unified experience for developers regardless of the underlying cloud provider. This allows the business to place workloads where it makes the most sense.
- The IDP provides a single self-service interface for developers to deploy their AI workloads, abstracting away the specifics of AWS, Google, Azure, or an on-premises data centre.
- The Cloud/SRE teams can use Kubernetes operator CRDs, Terraform or Pulumi templates to define the infrastructure for each environment. The IDP then allows developers to choose where to deploy, while the platform ensures that the underlying infrastructure is configured correctly and securely, whether it’s in the public cloud or on private hardware.
- For sensitive data, the IDP can enforce policies that automatically route workloads to a private cloud or on-premises infrastructure, ensuring full control over identity, encryption, and data access.
Enforce Full-Stack Observability:
- An IDP centralises monitoring and logging, giving platform teams and developers a complete, end-to-end view of their AI pipelines.
- The IDP automates the deployment of observability agents (Prometheus, Grafana, or Zabbix) across all environments, regardless of the cloud vendor. This standardises how metrics, logs, and traces are collected.
- The platform provides a single dashboard within the IDP, allowing developers to see the health and performance of their AI models from data ingestion all the way through to model inference. This helps to detect anomalies, security threats, or silent failures quickly, rather than having to piece together information from multiple, disparate provider consoles.
Set Your Own Cloud Governance Standards:
- Instead of relying on a cloud provider’s default settings, the platform team uses an IDP to enforce a consistent set of security and governance rules across all environments.
- The security team defines security baselines and policy-as-code using tools like Open Policy Agent (OPA) or HashiCorp Sentinel. These policies are built directly into the IDP’s deployment pipelines.
The IDP acts as the single point of control, ensuring that every piece of infrastructure or application deployed adheres to the organisation’s specific governance rules. For instance, a policy might prevent the deployment of a public-facing database or enforce specific encryption standards for all storage buckets. This prevents human error and ensures that the company’s controls are always upheld, regardless of the cloud provider’s defaults.
Security and governance are not the enemy of innovation — they’re what make safe, scalable innovation possible. Platform engineering sits at the intersection of infrastructure, compliance, and delivery — giving your teams the tools to control risk without slowing down development. It’s the sensible adult in the room, making sure everyone has fun without setting the house on fire.
Source Credit: https://medium.com/google-cloud/3-big-ai-risks-and-how-platform-engineering-can-help-2b7b77456eb5?source=rss—-e52cf94d98af—4
