operating-kubernetes

Name: operating-kubernetes
Author: ancoleman

45installs59forks

How to install operating-kubernetes?

ancoleman/ai-design-components/operating-kubernetes

$npx -y skills add ancoleman/ai-design-components --skill operating-kubernetes

Installs into the current project.

Summary

Operating production Kubernetes clusters effectively with resource management, advanced scheduling, networking, storage, security hardening, and autoscaling. Use when deploying workloads to Kubernetes, configuring cluster resources, implementing security policies, or troubleshoot

Files · 1

View on GitHub

SKILL.md

1	# Kubernetes Operations
2
3	## Purpose
4
5	Operating Kubernetes clusters in production requires mastery of resource management, scheduling patterns, networking architecture, storage strategies, security hardening, and autoscaling. This skill provides operations-first frameworks for right-sizing workloads, implementing high-availability patterns, securing clusters with RBAC and Pod Security Standards, and systematically troubleshooting common failures.
6
7	Use this skill when deploying applications to Kubernetes, configuring cluster resources, implementing NetworkPolicies for zero-trust security, setting up autoscaling (HPA, VPA, KEDA), managing persistent storage, or diagnosing operational issues like CrashLoopBackOff or resource exhaustion.
8
9	## When to Use This Skill
10
11	Common Triggers:
12	- "Deploy my application to Kubernetes"
13	- "Configure resource requests and limits"
14	- "Set up autoscaling for my pods"
15	- "Implement NetworkPolicies for security"
16	- "My pod is stuck in Pending/CrashLoopBackOff"
17	- "Configure RBAC with least privilege"
18	- "Set up persistent storage for my database"
19	- "Spread pods across availability zones"
20
21	Operations Covered:
22	- Resource management (CPU/memory, QoS classes, quotas)
23	- Advanced scheduling (affinity, taints, topology spread)
24	- Networking (NetworkPolicies, Ingress, Gateway API)
25	- Storage operations (StorageClasses, PVCs, CSI)
26	- Security hardening (RBAC, Pod Security Standards, policies)
27	- Autoscaling (HPA, VPA, KEDA, cluster autoscaler)
28	- Troubleshooting (systematic debugging playbooks)
29
30	## Resource Management
31
32	### Quality of Service (QoS) Classes
33
34	Kubernetes assigns QoS classes based on resource requests and limits:
35
36	Guaranteed (Highest Priority):
37	- Requests equal limits for CPU and memory
38	- Never evicted unless exceeding limits
39	- Use for critical production services
40
41	```yaml
42	resources:
43	requests:
44	memory: "512Mi"
45	cpu: "500m"
46	limits:
47	memory: "512Mi" # Same as request
48	cpu: "500m"
49	```
50
51	Burstable (Medium Priority):
52	- Requests less than limits (or only requests set)
53	- Can burst above requests
54	- Evicted under node pressure
55	- Use for web servers, most applications
56
57	```yaml
58	resources:
59	requests:
60	memory: "256Mi"
61	cpu: "250m"
62	limits:
63	memory: "512Mi" # 2x request
64	cpu: "500m"
65	```
66
67	BestEffort (Lowest Priority):
68	- No requests or limits set
69	- First to be evicted under pressure
70	- Use only for development/testing
71
72	### Decision Framework: Which QoS Class?
73
74	\| Workload Type \| QoS Class \| Configuration \|
75	\|---------------\|-----------\|---------------\|
76	\| Critical API/Database \| Guaranteed \| requests == limits \|
77	\| Web servers, services \| Burstable \| limits 1.5-2x requests \|
78	\| Batch jobs \| Burstable \| Low requests, high limits \|
79	\| Dev/test environments \| BestEffort \| No limits \|
80
81	### Resource Quotas and LimitRanges
82
83	Enforce multi-tenancy with ResourceQuotas (namespace limits) and LimitRanges (per-container defaults):
84
85	```yaml
86	# ResourceQuota: Namespace-level limits
87	apiVersion: v1
88	kind: ResourceQuota
89	metadata:
90	name: team-quota
91	namespace: team-alpha
92	spec:
93	hard:
94	requests.cpu: "10"
95	requests.memory: "20Gi"
96	limits.cpu: "20"
97	limits.memory: "40Gi"
98	pods: "50"
99	```
100
101	For detailed resource management patterns including Vertical Pod Autoscaler (VPA), see `references/resource-management.md`.
102
103	## Advanced Scheduling
104
105	### Node Affinity
106
107	Control which nodes pods schedule on with required (hard) or preferred (soft) constraints:
108
109	```yaml
110	affinity:
111	nodeAffinity:
112	requiredDuringSchedulingIgnoredDuringExecution:
113	nodeSelectorTerms:
114	- matchExpressions:
115	- key: node.kubernetes.io/instance-type
116	operator: In
117	values:
118	- g4dn.xlarge # GPU instance
119	```
120
121	### Taints and Tolerations
122
123	Reserve nodes for specific workloads (inverse of affinity):
124
125	```bash
126	# Taint GPU nodes to prevent non-GPU workloads
127	kubectl taint nodes gpu-node-1 workload=gpu:NoSchedule
128	```
129
130	```yaml
131	# Pod tolerates GPU taint
132	tolerations:
133	- key: "workload"
134	operator: "Equal"
135	value: "gpu"
136	effect: "NoSchedule"
137	```
138
139	### Topology Spread Constraints
140
141	Distribute pods evenly across failure domains (zones, nodes):
142
143	```yaml
144	topologySpreadConstraints:
145	- maxSkew: 1 # Max difference in pod count
146	topologyKey: topology.kubernetes.io/zone
147	whenUnsatisfiable: DoNotSchedule
148	labelSelector:
149	matchLabels:
150	app: critical-app
151	```
152
153	For advanced scheduling patterns including pod priority and preemption, see `references/scheduling-patterns.md`.
154
155	## Networking
156
157	### NetworkPolicies (Zero-Trust Security)
158
159	Implement default-deny security with NetworkPolicies:
160
161	```yaml
162	# Default deny all traffic
163	apiVersion: networki

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6 picks

Type

operating-kubernetes

45installs59forks

View on GitHub

How to install operating-kubernetes?

ancoleman/ai-design-components/operating-kubernetes

$npx -y skills add ancoleman/ai-design-components --skill operating-kubernetes

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Kubernetes Operations
2
3	## Purpose
4
5	Operating Kubernetes clusters in production requires mastery of resource management, scheduling patterns, networking architecture, storage strategies, security hardening, and autoscaling. This skill provides operations-first frameworks for right-sizing workloads, implementing high-availability patterns, securing clusters with RBAC and Pod Security Standards, and systematically troubleshooting common failures.
6
7	Use this skill when deploying applications to Kubernetes, configuring cluster resources, implementing NetworkPolicies for zero-trust security, setting up autoscaling (HPA, VPA, KEDA), managing persistent storage, or diagnosing operational issues like CrashLoopBackOff or resource exhaustion.
8
9	## When to Use This Skill
10
11	Common Triggers:
12	- "Deploy my application to Kubernetes"
13	- "Configure resource requests and limits"
14	- "Set up autoscaling for my pods"
15	- "Implement NetworkPolicies for security"
16	- "My pod is stuck in Pending/CrashLoopBackOff"
17	- "Configure RBAC with least privilege"
18	- "Set up persistent storage for my database"
19	- "Spread pods across availability zones"
20
21	Operations Covered:
22	- Resource management (CPU/memory, QoS classes, quotas)
23	- Advanced scheduling (affinity, taints, topology spread)
24	- Networking (NetworkPolicies, Ingress, Gateway API)
25	- Storage operations (StorageClasses, PVCs, CSI)
26	- Security hardening (RBAC, Pod Security Standards, policies)
27	- Autoscaling (HPA, VPA, KEDA, cluster autoscaler)
28	- Troubleshooting (systematic debugging playbooks)
29
30	## Resource Management
31
32	### Quality of Service (QoS) Classes
33
34	Kubernetes assigns QoS classes based on resource requests and limits:
35
36	Guaranteed (Highest Priority):
37	- Requests equal limits for CPU and memory
38	- Never evicted unless exceeding limits
39	- Use for critical production services
40
41	```yaml
42	resources:
43	requests:
44	memory: "512Mi"
45	cpu: "500m"
46	limits:
47	memory: "512Mi" # Same as request
48	cpu: "500m"
49	```
50
51	Burstable (Medium Priority):
52	- Requests less than limits (or only requests set)
53	- Can burst above requests
54	- Evicted under node pressure
55	- Use for web servers, most applications
56
57	```yaml
58	resources:
59	requests:
60	memory: "256Mi"
61	cpu: "250m"
62	limits:
63	memory: "512Mi" # 2x request
64	cpu: "500m"
65	```
66
67	BestEffort (Lowest Priority):
68	- No requests or limits set
69	- First to be evicted under pressure
70	- Use only for development/testing
71
72	### Decision Framework: Which QoS Class?
73
74	\| Workload Type \| QoS Class \| Configuration \|
75	\|---------------\|-----------\|---------------\|
76	\| Critical API/Database \| Guaranteed \| requests == limits \|
77	\| Web servers, services \| Burstable \| limits 1.5-2x requests \|
78	\| Batch jobs \| Burstable \| Low requests, high limits \|
79	\| Dev/test environments \| BestEffort \| No limits \|
80
81	### Resource Quotas and LimitRanges
82
83	Enforce multi-tenancy with ResourceQuotas (namespace limits) and LimitRanges (per-container defaults):
84
85	```yaml
86	# ResourceQuota: Namespace-level limits
87	apiVersion: v1
88	kind: ResourceQuota
89	metadata:
90	name: team-quota
91	namespace: team-alpha
92	spec:
93	hard:
94	requests.cpu: "10"
95	requests.memory: "20Gi"
96	limits.cpu: "20"
97	limits.memory: "40Gi"
98	pods: "50"
99	```
100
101	For detailed resource management patterns including Vertical Pod Autoscaler (VPA), see `references/resource-management.md`.
102
103	## Advanced Scheduling
104
105	### Node Affinity
106
107	Control which nodes pods schedule on with required (hard) or preferred (soft) constraints:
108
109	```yaml
110	affinity:
111	nodeAffinity:
112	requiredDuringSchedulingIgnoredDuringExecution:
113	nodeSelectorTerms:
114	- matchExpressions:
115	- key: node.kubernetes.io/instance-type
116	operator: In
117	values:
118	- g4dn.xlarge # GPU instance
119	```
120
121	### Taints and Tolerations
122
123	Reserve nodes for specific workloads (inverse of affinity):
124
125	```bash
126	# Taint GPU nodes to prevent non-GPU workloads
127	kubectl taint nodes gpu-node-1 workload=gpu:NoSchedule
128	```
129
130	```yaml
131	# Pod tolerates GPU taint
132	tolerations:
133	- key: "workload"
134	operator: "Equal"
135	value: "gpu"
136	effect: "NoSchedule"
137	```
138
139	### Topology Spread Constraints
140
141	Distribute pods evenly across failure domains (zones, nodes):
142
143	```yaml
144	topologySpreadConstraints:
145	- maxSkew: 1 # Max difference in pod count
146	topologyKey: topology.kubernetes.io/zone
147	whenUnsatisfiable: DoNotSchedule
148	labelSelector:
149	matchLabels:
150	app: critical-app
151	```
152
153	For advanced scheduling patterns including pod priority and preemption, see `references/scheduling-patterns.md`.
154
155	## Networking
156
157	### NetworkPolicies (Zero-Trust Security)
158
159	Implement default-deny security with NetworkPolicies:
160
161	```yaml
162	# Default deny all traffic
163	apiVersion: networki

People who liked this also viewed

6 picks

Type