How to fix Memory resource exceeded in Kubernetes

# View memory limit and usage:
kubectl describe pod <pod-name> -n <namespace> | grep -E "Limits|Requests" -A 3

# More detailed:
kubectl get pod <pod-name> -n <namespace> -o jsonpath='{.spec.containers[*].resources.limits.memory}'

# Current usage:
kubectl top pods <pod-name> -n <namespace>

# Watch memory growth:
kubectl top pods <pod-name> -n <namespace> -w

# For Java applications, capture heap dump:
kubectl exec -it <pod-name> -n <namespace> -- jmap -dump:live,format=b,file=/tmp/heap.bin <pid>
kubectl cp <pod-name>:/tmp/heap.bin /tmp/heap.bin -n <namespace>

# Analyze with JProfiler or similar tool

# For Node.js, capture heap snapshot:
kubectl exec <pod-name> -n <namespace> -- node --inspect &
# Then use Chrome DevTools

# For Python:
kubectl exec <pod-name> -n <namespace> -- pip install memory-profiler
kubectl exec <pod-name> -n <namespace> -- python -m memory_profiler myapp.py

# Generic approach - check memory over time:
watch 'kubectl top pod <pod-name> -n <namespace>'

# View git history for recent changes:
git log --oneline -n 20
git diff HEAD~5..HEAD  # Changes in last 5 commits

# Look for:
# - New caching without eviction policies
# - Loading entire files/datasets into memory
# - Accumulating collections (lists, maps) in global scope
# - Missing close/cleanup of resources

git revert <commit-hash>

# For a deployment:
kubectl set resources deployment <name> -n <namespace> --limits=memory=2Gi

# Or patch:
kubectl patch deployment <name> -n <namespace> -p '{"spec":{"template":{"spec":{"containers":[{"name":"<container>","resources":{"limits":{"memory":"2Gi"}}}]}}}}'

# Or edit YAML:
kubectl edit deployment <name> -n <namespace>
# Change: limits.memory from 512Mi to 2Gi
kubectl apply -f deployment.yaml

MemoryMXBean memBean = ManagementFactory.getMemoryMXBean();
MemoryUsage heapUsage = memBean.getHeapMemoryUsage();
long maxMemory = heapUsage.getMax() / (1024 * 1024);  // MB
long usedMemory = heapUsage.getUsed() / (1024 * 1024);
System.out.println("Heap: " + usedMemory + "/" + maxMemory);

const used = process.memoryUsage();
console.log(`Memory: ${Math.round(used.heapUsed / 1024 / 1024)} MB`);

import psutil
process = psutil.Process(os.getpid())
mem = process.memory_info().rss / 1024 / 1024  # MB
print(f"Memory: {mem} MB")

# Bad: loads entire file into memory
data = open('large_file.csv').read()

# Good: read line by line
with open('large_file.csv') as f:
    for line in f:
        process(line)

# Bad: SELECT * FROM users
users = db.query(User).all()  # Million users in memory!

# Good: paginate
page = db.query(User).offset(0).limit(100).all()

from functools import lru_cache

@lru_cache(maxsize=100)  # Limit cache size
def expensive_operation(x):
    return compute(x)

kubectl set resources deployment <name> -n <namespace> --requests=memory=512Mi

# Or edit:
kubectl edit deployment <name> -n <namespace>

resources:
  requests:
    memory: 512Mi    # Scheduler reserves this
  limits:
    memory: 1Gi      # Cannot exceed this

# Enable metrics in Prometheus:
kubectl apply -f https://github.com/prometheus/prometheus/raw/main/documentation/examples/prometheus.yml

# Query memory usage:
# PromQL: container_memory_usage_bytes{pod="<pod>"}

# Or use kubectl:
kubectl top pods -n <namespace> --sort-by=memory -w

# Create alerts for memory threshold:
# Alert when pod uses > 80% of limit
alert = "container_memory_usage_bytes / (10^6) > limit * 0.8"