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DevOps vs. Platform engineering

Sooraj Shah
Sooraj Shah

April 14, 2025

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DevOps vs. Platform engineering

DevOps vs. platform engineering: Conceptual differences

DevOps emerged in the late 2000s as an approach to software development that broke down silos and improved collaboration between software developers and IT operations. This approach required a cultural shift in favor of process-driven change within engineering organizations. 

Previously, developers and engineers evaluated their own work without proper knowledge of their deployment environments and the operational considerations their IT teams required. Before DevOps, releases were timed in months, if not years. This was deeply inefficient: if a developer passed over a task to the ops team, weeks or months could pass before the code was evaluated, let alone deployed to fix the problem. If developers needed to review or make changes a second time, they most likely had already moved on to other tasks and forgotten details of the project.

Implementing DevOps practices improved transparency between teams and encouraged a culture of collaboration. By sharing responsibility and embracing continuous improvement, engineering teams were able to work together to build better software, improve processes, and  meet business goals quickly.

DevOps engineers help continue this transformation of software development best practices in their organizations today. Their work promotes developer agility by building the infrastructure, processes, and culture needed for faster deployments and improving site reliability. 

‍Platform engineering, on the other hand, centers on improving the experience of everyone involved in software engineering, from developers to CTOs. They build and maintain the platforms and portals that provide self-service workflows to reduce developer friction, eliminate repetitive tasks, and improve scalability. Ultimately, platform engineers are the maintainers of the infrastructure DevOps builds, allowing developers to focus on building and shipping software faster. 

‍Platform engineering as a concept emerged in the last few years as a response to the growing complexity of software development. According to Gartner, this is compounded by the “agile empowerment of teams” — as developers were more empowered by DevOps practices to move fast and make their own decisions about code and tools, standards began to slip. With the introduction of microservices, Kubernetes, cloud resources, and more, things only got messier. 

The platform team builds an internal developer portal to support the organization’s software platform, and uses a product management approach to improve, scale, and maintain it, often referred to as “platform as a product.” In other words, platform engineers treat their users — including developers, DevOps, SREs, and engineering leaders — as customers of the platform, who will be best served by an experience that  provides a consistent, reusable set of services and workflows for everyone on demand. 

Platform engineering is about abstracting away the complexity of software development and ensuring users can follow golden paths to build and ship software efficiently. According to Gartner, by 2026, 80% of large software engineering organizations will have a dedicated platform engineering team — up from 45% in 2022.

| Aspect | DevOps | Platform Engineering | |---|---|---| | Core philosophy | A collaborative approach to integrating development and operations teams, with a focus on automating and improving the software delivery lifecycle. | A specialized engineering team focused on building a platform for other engineering teams to use. | | Primary goal | To shorten and automate the software development lifecycle to accelerate the delivery of high-quality software. | To improve the experience of software engineers by providing everything within a self-service platform so they don't have to work directly with infrastructure. | | Scope of work | Focus on the entire SDLC, including planning, coding, building, testing, deploying, and monitoring. Involves performing tasks that traditionally span the walls between development and operations. Automation is a key aspect of DevOps engineering. | Focus on building and maintaining a self-service platform that helps developers move faster. Involves designing and building the underlying infrastructure with a focus on automation, self-service, and providing clear documentation details. | | Role responsibilities | * Implement the tools that facilitate collaboration between development and operations teams. (e.g., Jenkins, Ansible, GitLab CI)
* Automate the provisioning, deployment, and infrastructure management
* Implement monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack)
* Foster collaboration and communication between teams
* Continuously improve and automate release processes. | * Build and maintain the self-service platform
* Improve developer experience
* Implement disaster recovery, security, and compliance measures
* Define and implement workflows (CI/CD, etc.)
* Standardize platform tools and processes (e.g., GitOps)
* Monitor systems and application performance
* Provide training, tools, and standardized processes for development teams
* Maintain security/compliance of platform
* Ensure knowledge sharing and platform documentation. | | Technical skills required | * Proficient in CI/CD pipelines and tools
* Strong scripting skills
* Deep knowledge of infrastructure as code (IaC)
* Skilled in system administration
* Familiar with Bash, Python, or Go
* Understanding of observability tools
* Knowledge of containerization
* Understanding of networking concepts
* Basic networking and security knowledge. | * Strong working knowledge of infrastructure as code (IaC) and automation
* Skilled in building and maintaining self-service platforms
* Good understanding of cloud platforms
* Familiar with tools like Terraform, Kubernetes, etc.
* Strong communication and collaboration skills. | | Approach to tooling | Works with the various tools used throughout the SDLC by developers, operations, QA, security. | Flows a list of approved tools to developers, and abstracts away the complexity. Increases developer needs, and optimizes the use of tools (provides one set of tools). | | Communication style | Constant interaction between development and operations teams, with shared responsibility and planning done in unison. | Reduces the need for direct communication. Provides documentation for information about a specific tool or process. (Allows for standardized approval or approval). Platform Engineering is more technical. | | Biggest benefit | Automated software delivery and faster release cycles. | Smooth and consistent developer experience. | | Before and after scenario | Before DevOps: A developer pushes their code, but it still has to wait days or weeks for operations to deploy it, leading to delays and frustration.
After DevOps: With automation and collaboration, the developer pushes the code, and it's deployed within minutes, allowing for faster feedback and more frequent releases. | Before platform engineering: A developer submits a ticket to request infrastructure, configuration, or access, waits for approval, and then another team handles it.
After platform engineering: The developer uses the self-service tools, and gets the infrastructure, configuration, or access they need immediately. | | Performance metrics (how they're measured on success) | Deployment frequency, system uptime, and change failure rate. | Time to value. After platform adoption rate, developer satisfaction, and infrastructure utilization/productivity. | | Common challenges | * Resistance to DevOps culture and mindset.
* Lack of communication across teams.
* Tool sprawl, increased complexity, and lack of standardization.
* Insufficient documentation gaps.
* Security concerns.
* Ensuring stability and reliability in a dynamic environment. | * Lack of platform adoption.
* Unpredictability and compatibility between different tools.
* Difficulty with integration with legacy systems.
* Cultural silos between teams.
* Balancing innovation and proving value to the business.
* Integrating external tools and internal tools. |

How DevOps and platform engineering work together

DevOps and platform engineering are not competitors, they are complementary movements. Platform engineering focuses on cultural transformation, incorporating new working agreements, engineering values, and best practices, while DevOps ensures that the tools to support that culture are available and optimized. DevOps provides the method to develop and deliver software, whereas platform engineering is about building the platforms to facilitate efficient development. DevOps solves immediate operational bottlenecks, whereas platform engineering takes a proactive approach by building reusable solutions to prevent future bottlenecks. 

While many organizations may believe they ought to “shift” from DevOps to platform engineering to solve the challenges they’re facing, this does not mean they should move away from DevOps practices or a DevOps team. In fact, as platform engineering also provides infrastructure to support DevOps workflows, combining their powers is the best way to get the most out of a DevOps team, delivering improved reliability, efficiency, and speed. 

But just as when DevOps first emerged, many DevOps engineers are now calling themselves platform engineers, and DevOps teams are being renamed “platform engineering” teams. Organizations need to be wary that the roles and aims of each type of team are different. If an engineering team is big enough to incorporate both DevOps and platform engineering teams, then this will likely yield the best outcomes.

However, like many shifts in technology, sometimes teams need a new direction, and platform engineering can help them to focus on this new direction.

Examples of DevOps and platform engineering in practice

Example 1: Transitioning from DevOps to platform engineering at AMCS Group

AMCS Group initially built a global DevOps team to support its growing business, adopting tools and methods like Git, CI/CD, and Azure. However, as the company scaled from 200 to 1,000 employees, the DevOps team became overwhelmed with repetitive requests, such as cloud deployment and infrastructure change requests. This left little room for their DevOps team to innovate and make process improvements.

To address this, AMCS transitioned to a platform engineering approach, focusing on self-service capabilities for developers while maintaining best practices and security standards. The company established a dedicated platform engineering team, who provided developers with the tools and automation needed to build, test, and deploy applications independently.

A key initiative was the development of an internal developer portal, which introduced self-service actions to eliminate repetitive DevOps tickets and centralized service visibility through a software catalog, which helped to reduce requests for information. 

Read the full case study here.

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Example 2: Using platform engineering to aid DevOps at Cybersixgill

Cybersixgill turned to platform engineering to alleviate DevOps bottlenecks caused by frequent developer requests for tasks such as scaffolding services and provisioning environments. The company introduced an internal developer portal to provide structured self-service actions, allowing developers to create new CD applications and update production environments without direct DevOps intervention.

To further streamline operations, Cybersixgill implemented an automated microservice scaffolding process, reducing service setup time from days to minutes. The platform also improved resource management, cutting down CI/CD cycle times from 30 minutes to 30 seconds — allowing developers to deploy changes faster while reducing DevOps dependencies. 

Read the full case study here.

Example 3: Rabobank used platform engineering to maintain innovation velocity

Rabobank, a global financial services leader, faced a common enterprise challenge: a growing demand for digital products but a shortage of skilled engineers. While the obvious answer was to hire more engineers, any new hires still needed to be onboarded before they could deliver software, which increased their lead time for improvements. This wouldn’t be sustainable in the long term.

The company turned to platform engineering, ensuring teams could onboard and deliver value more efficiently. 

Rabobank focused on documenting standards, golden paths, reusable infrastructure components, and automated onboarding and deployment. These measures streamlined workflows, empowered teams with self-service capabilities, and significantly reduced onboarding time. As a result, new teams could become productive within weeks rather than months.

The impact was clear: developer productivity accelerated, engineers experienced greater job satisfaction, and innovation velocity remained high despite talent shortages. By investing in platform engineering, Rabobank successfully reduced time-to-productivity for new teams, maximizing efficiency and maintaining a competitive edge.

Read more about it here.

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Common misconceptions and FAQs

  • Is platform engineering replacing DevOps?
    • No, platform engineering enables organizations to achieve their DevOps goals by iterating on developer experience and automating infrastructure to drive efficiency and autonomy.

  • Do you need DevOps if you have platform engineering?
    • Yes, DevOps still ensures smooth collaboration and automation, while platform engineering streamlines infrastructure.

  • What is the biggest difference between DevOps and platform engineering?
    • DevOps focuses on cultural transformation and collaboration, while platform engineering builds internal platforms to improve developer experience.

  • How does Site Reliability Engineering (SRE) fit in?
    • SREs aim to ensure reliability and scalability of infrastructure
    • They work with DevOps engineers to ensure automation and CI/CD pipelines are optimized. 
    • They decide on monitoring and alerting tools required for incident management.
    • While DevOps and platform engineers assist SREs in incident response, it is SRE’s responsibility to lead incident response, and speed up future responses. DevOps and platform engineering principles can help SREs to meet their targets.

  • What are the common pitfalls of platform engineering?
    • Over-engineering the platform, creating unnecessary complexity.
    • Lack of developer engagement, leading to low adoption.
    • Not defining a clear product roadmap for the platform.

  • How long do developers wait for DevOps or SRE assistance?

The future of DevOps and platform engineering 

  • Is DevOps dead?  
    • No, but it will evolve to integrate more platform engineering elements.

  • Will platform engineering become mandatory?  
    • Yes. It is likely that large-scale organizations especially may opt to have an engineering team that incorporates developers, DevOps and platform engineers.  Smaller organizations may decide to transition their existing DevOps team to become more aligned with platform engineering.

  • DevOps and platform engineering predictions for 2025 and beyond:
    • AI-driven automation will reduce the need for manual interventions.
    • Internal developer portals will become more prominent, helping to bring together SREs, DevOps engineers and platform engineers, along with developers into one workspace.

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Example JSON block

{
  "foo": "bar"
}

Order Domain

{
  "properties": {},
  "relations": {},
  "title": "Orders",
  "identifier": "Orders"
}

Cart System

{
  "properties": {},
  "relations": {
    "domain": "Orders"
  },
  "identifier": "Cart",
  "title": "Cart"
}

Products System

{
  "properties": {},
  "relations": {
    "domain": "Orders"
  },
  "identifier": "Products",
  "title": "Products"
}

Cart Resource

{
  "properties": {
    "type": "postgress"
  },
  "relations": {},
  "icon": "GPU",
  "title": "Cart SQL database",
  "identifier": "cart-sql-sb"
}

Cart API

{
 "identifier": "CartAPI",
 "title": "Cart API",
 "blueprint": "API",
 "properties": {
   "type": "Open API"
 },
 "relations": {
   "provider": "CartService"
 },
 "icon": "Link"
}

Core Kafka Library

{
  "properties": {
    "type": "library"
  },
  "relations": {
    "system": "Cart"
  },
  "title": "Core Kafka Library",
  "identifier": "CoreKafkaLibrary"
}

Core Payment Library

{
  "properties": {
    "type": "library"
  },
  "relations": {
    "system": "Cart"
  },
  "title": "Core Payment Library",
  "identifier": "CorePaymentLibrary"
}

Cart Service JSON

{
 "identifier": "CartService",
 "title": "Cart Service",
 "blueprint": "Component",
 "properties": {
   "type": "service"
 },
 "relations": {
   "system": "Cart",
   "resources": [
     "cart-sql-sb"
   ],
   "consumesApi": [],
   "components": [
     "CorePaymentLibrary",
     "CoreKafkaLibrary"
   ]
 },
 "icon": "Cloud"
}

Products Service JSON

{
  "identifier": "ProductsService",
  "title": "Products Service",
  "blueprint": "Component",
  "properties": {
    "type": "service"
  },
  "relations": {
    "system": "Products",
    "consumesApi": [
      "CartAPI"
    ],
    "components": []
  }
}

Component Blueprint

{
 "identifier": "Component",
 "title": "Component",
 "icon": "Cloud",
 "schema": {
   "properties": {
     "type": {
       "enum": [
         "service",
         "library"
       ],
       "icon": "Docs",
       "type": "string",
       "enumColors": {
         "service": "blue",
         "library": "green"
       }
     }
   },
   "required": []
 },
 "mirrorProperties": {},
 "formulaProperties": {},
 "calculationProperties": {},
 "relations": {
   "system": {
     "target": "System",
     "required": false,
     "many": false
   },
   "resources": {
     "target": "Resource",
     "required": false,
     "many": true
   },
   "consumesApi": {
     "target": "API",
     "required": false,
     "many": true
   },
   "components": {
     "target": "Component",
     "required": false,
     "many": true
   },
   "providesApi": {
     "target": "API",
     "required": false,
     "many": false
   }
 }
}

Resource Blueprint

{
 “identifier”: “Resource”,
 “title”: “Resource”,
 “icon”: “DevopsTool”,
 “schema”: {
   “properties”: {
     “type”: {
       “enum”: [
         “postgress”,
         “kafka-topic”,
         “rabbit-queue”,
         “s3-bucket”
       ],
       “icon”: “Docs”,
       “type”: “string”
     }
   },
   “required”: []
 },
 “mirrorProperties”: {},
 “formulaProperties”: {},
 “calculationProperties”: {},
 “relations”: {}
}

API Blueprint

{
 "identifier": "API",
 "title": "API",
 "icon": "Link",
 "schema": {
   "properties": {
     "type": {
       "type": "string",
       "enum": [
         "Open API",
         "grpc"
       ]
     }
   },
   "required": []
 },
 "mirrorProperties": {},
 "formulaProperties": {},
 "calculationProperties": {},
 "relations": {
   "provider": {
     "target": "Component",
     "required": true,
     "many": false
   }
 }
}

Domain Blueprint

{
 "identifier": "Domain",
 "title": "Domain",
 "icon": "Server",
 "schema": {
   "properties": {},
   "required": []
 },
 "mirrorProperties": {},
 "formulaProperties": {},
 "calculationProperties": {},
 "relations": {}
}

System Blueprint

{
 "identifier": "System",
 "title": "System",
 "icon": "DevopsTool",
 "schema": {
   "properties": {},
   "required": []
 },
 "mirrorProperties": {},
 "formulaProperties": {},
 "calculationProperties": {},
 "relations": {
   "domain": {
     "target": "Domain",
     "required": true,
     "many": false
   }
 }
}
{{tabel-1}}

Microservices SDLC

  • Scaffold a new microservice

  • Deploy (canary or blue-green)

  • Feature flagging

  • Revert

  • Lock deployments

  • Add Secret

  • Force merge pull request (skip tests on crises)

  • Add environment variable to service

  • Add IaC to the service

  • Upgrade package version

Development environments

  • Spin up a developer environment for 5 days

  • ETL mock data to environment

  • Invite developer to the environment

  • Extend TTL by 3 days

Cloud resources

  • Provision a cloud resource

  • Modify a cloud resource

  • Get permissions to access cloud resource

SRE actions

  • Update pod count

  • Update auto-scaling group

  • Execute incident response runbook automation

Data Engineering

  • Add / Remove / Update Column to table

  • Run Airflow DAG

  • Duplicate table

Backoffice

  • Change customer configuration

  • Update customer software version

  • Upgrade - Downgrade plan tier

  • Create - Delete customer

Machine learning actions

  • Train model

  • Pre-process dataset

  • Deploy

  • A/B testing traffic route

  • Revert

  • Spin up remote Jupyter notebook

{{tabel-2}}

Engineering tools

  • Observability

  • Tasks management

  • CI/CD

  • On-Call management

  • Troubleshooting tools

  • DevSecOps

  • Runbooks

Infrastructure

  • Cloud Resources

  • K8S

  • Containers & Serverless

  • IaC

  • Databases

  • Environments

  • Regions

Software and more

  • Microservices

  • Docker Images

  • Docs

  • APIs

  • 3rd parties

  • Runbooks

  • Cron jobs

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