Why I introduced This DevOps Definition
“DevOps is the integration of System Engineering and Application Engineering.”
— Sri Srinivas (Srinivasa Raju Tangella)
🎯 The Realization Behind the Definition
After years of hands-on experience in complex DevOps environments — across both Azure and AWS — I came to a critical understanding:
The popular buzzwords around DevOps — “culture,” “collaboration,” “automation,” “tools” — are important, but they are not the full picture.
In practice, I observed a gap:
• Pipelines were running, but applications were failing.
• Teams could use Docker, but couldn’t debug broken Linux permissions.
• A Kubernetes pod failed, but no one could explain the underlying infrastructure issue.
• Windows VMs wouldn't boot, and the root cause was misconfigured system policies, not a bad deployment.
That’s when I realized...
DevOps isn't just about CI/CD pipelines.
It’s about understanding and managing both the infrastructure and the application stack end-to-end.
What This Definition Truly Embraces
✅ System Engineering Includes:
• 🛠️ Cloud Infrastructure: Azure, AWS, GCP
• 💻 OS Administration: Windows Server, Linux (Ubuntu, RHEL, Amazon Linux)
• 🔐 Networking & Security: DNS, Firewalls, NACLs, WAF, IAM
• ♻️ Backup & Disaster Recovery: Snapshots, failovers, cross-region replication
• ⚙️ Automation & Monitoring: PowerShell, Bash, Azure Monitor, CloudWatch, Prometheus
✅ Application Engineering Includes:
• 🧱 App Architecture & Frameworks: .NET, Node.js, Java, Python
• 📦 Build & Packaging Pipelines: Maven, npm, Gradle, MSBuild
• 🔄 Configuration & Dependency Management: Helm, Kustomize, NuGet, Pip
• 🚀 Debugging & Optimization: App Insights, New Relic, logs, crash traces
• ⚡ Containerization & Orchestration: Docker, Kubernetes, ECS, AKS, EKS
• 📈 Performance Engineering: JVM tuning, garbage collection, memory leaks, thread tuning
Without system fluency, deployments break.
Without application fluency, systems are underutilized.
🔮 Why This Definition Matters — Now and In the Future
• 🌐 Reflects real skill demands in hybrid/multi-cloud architectures.
• 🔁 Bridges the gap between DevOps, SRE, Cloud Engineering, and Platform Teams.
• 🧠 Encourages deep expertise, not just tool knowledge.
• 🧱 Supports the “You build it, you run it” model with real accountability.
• 🧭 Prepares engineers for resilience, observability, and optimization — not just deployments.
• 🚀 Powers true DevOps-as-a-Service delivery models with holistic ownership.
DevOps is not just about tools or culture — it is the engineering integration of infrastructure and applications.
So, I introduced a new definition:
“DevOps is the integration of System Engineering and Application Engineering.”
🔧 System Engineering includes:
• Cloud (Azure, AWS, GCP)
• Linux & Windows Administration
• Networking, Firewalls, DNS, IAM
• Monitoring, Backups, PowerShell, Bash
🧱 Application Engineering includes:
• CI/CD pipelines & build frameworks (.NET, Java, Node.js)
• Dependency & config management (Helm, NuGet)
• Debugging, tracing, performance tuning
• Docker, Kubernetes, Helm, cloud-native app design
This definition matters in 2025 and beyond because:
✅ It reflects real-world DevOps skill demands in hybrid environments
✅ It bridges the gap between SRE, Platform Engineering, and DevOps
✅ It encourages engineers to go beyond tools — into true ownership
✅ It aligns with full-stack delivery and DevOps-as-a-Service models
📘 See the official GitHub repo: https://github.com/sresrinivas/etoe
📜 License: CC BY 4.0
✍️ Authored by: Sri Srinivas (Srinivasa Raju Tangella)
📌 The Final Thought
DevOps isn't a title. It's not a tool.
It's a discipline that unites engineering depth in systems and applications —
and this is the definition that will shape the future of DevOps engineering.
Top comments (2)
I’ve enjoyed all the research and hands-on focus you put into this definition, it adds up. Practical stuff like this actually matters to me
Very good Article.