Streamlining Your Platform Team’s Workloads
As organizations scale their cloud infrastructure and applications, platform teams are increasingly feeling the strain. A platform team (or infrastructure/DevOps team) is tasked with providing a reliable foundation, including CI/CD pipelines, cloud environments, tooling and compliance guardrails.
The issue is that as the number of developers and services grows, platform engineers can become overloaded with support requests and operational tasks.
One of the most effective ways to reduce the direct workload on platform teams is to implement self-service infrastructure for developers. However, self-service in this space is often misunderstood; it doesn’t mean developers are writing infrastructure code themselves.
Instead, it allows them to request and manage resources within the guardrails set by the platform team, ensuring consistency, security and compliance while reducing bottlenecks.
Growing Burdens on Platform Teams
In a modern tech organization, platform teams wear many hats. They might be responsible for infrastructure provisioning (creating AWS/GCP resources for teams), maintaining CI/CD pipelines, managing shared services like databases and monitoring, enforcing security policies and generally acting as a center of cloud expertise. These responsibilities tend to grow out of control faster than the team can scale to handle them.
Several issues increase the burden on infrastructure teams:
- Cloud complexity: Each new project adds more services, requiring platform teams to manage provisioning and templates at scale.
- Ticket Ops: Developers rely on platform teams for every infrastructure request, creating bottlenecks as ticket queues grow.
- Operational toil: Repetitive tasks like patching, troubleshooting and scaling keep teams reactive instead of automating.
- Context switching: Supporting multiple teams forces engineers to jump between tasks, reducing efficiency and increasing cognitive load.
If platform teams struggle to keep up, developers experience delays, infrastructure becomes harder to manage and the entire organization slows down. In many organizations, the burden is so great that our platform teams do not have the bandwidth to investigate streamlining options.
The Case for Self-Service Infrastructure
One approach to reduce the burden on infrastructure engineers is to enable self-service. This allows developers to request and consume infrastructure resources such as databases, queues and APIs on demand, without needing to open tickets or wait for manual provisioning.
By enabling self-service infrastructure, platform teams scale their contributions from project-specific implementations, to building reusable automation, guardrails, policies and infrastructure for many teams. Instead of manually provisioning every resource, they create policies and tooling that allow teams to move faster without bypassing security and compliance requirements.
Enabling Self-Service Without Loss of Control
Platform teams can introduce self-service infrastructure while ensuring security, compliance and governance by implementing key strategies like:
- Reusable templates and catalogs: Standardized infrastructure patterns, such as pre-configured CI/CD pipelines and service stacks, allow developers to spin up resources without manual intervention.
- Infrastructure as Code with guardrails: Developers define what they need using tools like Terraform or Pulumi, but platform teams enforce compliance by providing approved modules and policies.
- Role-based access and policy enforcement: Self-service does not mean unlimited access. Platform teams set permissions, budget constraints and Policy as Code rules (such as Open Policy Agent) to ensure safe, controlled resource provisioning.
- Internal developer platforms (IDPs): Unified UIs, command line interface (CLI) and other tooling that abstracts infrastructure complexity, integrating repo creation, CI/CD setup and monitoring into a developer-friendly workflow.
The challenge is ensuring that self-service doesn’t lead to configuration drift, security gaps or inconsistent infrastructure deployments. Nitric helps solve this by acting as an interface between development teams and infrastructure, allowing developers to declare what they need while ensuring platform teams retain control over how resources are provisioned and governed.
Example: Provisioning Secure and Consistent Infrastructure
Here is a possible scenario, where an application team or developer has requested cloud storage use in their application. Traditionally, when a team needs a new storage bucket, the process might look something like this:
- The developer submits a ticket requesting an S3 or Google Cloud Storage (GCS) bucket.
- A DevOps engineer manually provisions the bucket or writes Terraform to automatically provision it, including required configuration and permissions.
- The engineer hands over the bucket or it is made available via CI/CD, allowing the development team to start using it.
- This process, due its reactive (request/prioritize/response) nature, typically takes hours or days, often blocking the development team in the meantime.
With self-service infrastructure, this workflow changes. Developers request what they need in code or via a platform, and the automation handles provisioning according to pre-approved policies.
Using a tool like Nitric, developers can define infrastructure requirements without writing low-level Terraform or dealing with cloud provider APIs.
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import { bucket } from '@nitric/sdk'; // Developer declares a new bucket for storing user uploads const userFiles = bucket('user-uploads').allow('read', 'write', 'delete'); // Later in their application code: async function saveUserFile(fileName: string, data: Buffer) { await userFiles.file(fileName).write(data); console.log(`Saved file ${fileName} to user-uploads bucket.`); } |
When this code runs, Nitric automatically provisions the required storage bucket in AWS or GCP within the constraints defined by platform engineers.
Keeping Guardrails in Place
While developers can request resources, platform teams ensure compliance by enforcing policies at the infrastructure level. For example, all S3 buckets can be automatically encrypted with a platform-wide Terraform policy:
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resource "aws_s3_bucket_server_side_encryption_configuration" "bucket_encryption" { bucket = aws_s3_bucket.bucket.id rule { apply_server_side_encryption_by_default { sse_algorithm = "AES256" } } } |
This approach ensures:
- Developers get what they need without waiting.
- Platform teams maintain full control over security and compliance.
- Fix once, roll out fixes to all projects
- No one has to manually create resources or review tickets.
- Infrastructure is consistently deployed across projects
- Each project is always in sync with its required infrastructure
Conclusion
Platform teams are the backbone of any technology organization, but reactive processes don’t scale, particularly when manual work is involved. As teams grow, the demand for infrastructure resources increases, and platform engineers can’t afford to spend all their time handling requests, troubleshooting deployment issues, and managing tickets.
“Developer self-service can sound like a dream: A platform that developers can use to freely develop — unburdened by sprawling IT, tools they shouldn’t need to know how to use, and tickets that take forever to complete.”
— Puppet
Self-service infrastructure reduces friction, improves security and ensures platform teams stay in control. By shifting from manual provisioning to automation, policy enforcement and developer-friendly self-service tools, platform teams:
- Eliminate bottlenecks without compromising security.
- Reduce ticket queues and operational toil.
- Free up time to focus on automation and platform improvements.
Instead of being gatekeepers, platform teams become enablers, helping teams move faster while ensuring infrastructure remains secure and scalable. This is how organizations scale without burning out their platform teams.
