Because most tools abstract the system
Tools like:
Kubernetes
Docker
Terraform
Cloud providers
CI/CD tools
…hide the underlying CPU, RAM, storage, network details.
So engineers assume:
“The platform will manage it; I don’t need to know systems-level details.”
That’s WRONG.
2️⃣ Because modern DevOps training is shortcut-based
Bootcamps and online courses teach:
Docker commands
Jenkins pipelines
Kubernetes YAML
GitHub Actions
…but don’t teach:
How CPU scheduling works
How memory paging or swapping impacts containers
How Linux kernel handles disk I/O
How networks, subnets, routes, MTU work
How disk throughput affects pods
So DevOps engineers come out tool operators, not system engineers.
3️⃣ Because many DevOps engineers never operated bare-metal
Old-school sysadmins worked with:
Physical servers
Memory leaks
Disk corruptions
Slow NIC cards
RAID failures
Network packet loss
Modern DevOps only sees:
EC2 instance
Pod
Node
Volume
Load balancer
They never learn the internals.
4️⃣ Because Kubernetes hides problems — and L2/L3 engineers handle SRE work
In many companies:
L1 DevOps → Runs pipelines, deployments
L2 DevOps/SRE → Handles resource, scaling, infra issues
Platform Engineering → Solves deep kernel/resource problems
So junior DevOps rarely touch real resource issues.
5️⃣ Because people think DevOps = Deployment + CI/CD
But actually DevOps = complete lifecycle, including:
Performance engineering
Capacity planning
Resource optimization
Bottleneck diagnosis
But most engineers stop at CI/CD level only.
❌ But Ignoring CPU, Memory, Disk, IO, Networking Makes You a Weak DevOps Engineer
Here’s why:
🔸 Docker → uses cgroups, namespaces, page cache, overlayfs
If you don’t know:
CPU throttling
Memory OOM Killer
Page cache behavior
Copy-on-write performance
You cannot troubleshoot container problems.
🔸 Kubernetes → CPU Requests/Limits depend on node hardware
If you don’t know:
CPU shares
Core allocation
NUMA
Memory paging
Container escape issues
You cannot fix pod crashes.
🔸 CI/CD running on agents need resource tuning
Slow builds often caused by:
I/O saturation
High CPU load
Low memory
Network packet loss
Not tool issues.
🔸 Cloud bill optimization requires resource mastery
If you don't understand CPU/memory/disk sizing, you will overspend lakhs of rupees per month.
🔥 Real Industry Example
A Kubernetes pod running Java crashed every 10 minutes.
DevOps blamed:
Docker
Spring Boot
JVM version
Real cause:
Node had low memory
Kernel started swapping
JVM slowed
Pod failed health checks
Restart loop started
Only an engineer who understands memory, swap, paging can fix this.
⭐ What a Strong DevOps Engineer Must Know
To become a 10x DevOps engineer, you must understand:
CPU
Cores vs threads
CPU throttling
Load average
cgroups CPU shares
Memory
Paging
Swap
OOM killer
Page cache
Memory leaks
Disk
IOPS
Throughput
Latency
Filesystem limits
OverlayFS performance
Network
Subnets
MTU
Packet flow
TCP handshake
DNS resolution
Firewall impact
💡 Final Answer (Simple Words)
DevOps engineers ignore CPU, memory, disk, I/O, networking because tools hide everything, training is shortcut-based, jobs split responsibilities, and engineers focus only on CI/CD and YAML — not real engineering.
But mastering these fundamentals is what makes you:
A real DevOps Expert
Not just a tool operator
And ready for L2, L3, SRE, Platform Engineering roles
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