MongoDB vs DynamoDB

Audits WiredTiger dirty cache byte percentages, checks eviction server activity, and calculates secondary member replication lag.

// 1. Audit WiredTiger cache dirty and mapped memory pressure
db.serverStatus().wiredTiger.cache;
const cache = db.serverStatus().wiredTiger.cache;
print("Dirty cache bytes: " + cache["tracked dirty bytes in the cache"]);
print("Max cache bytes:   " + cache["maximum bytes configured"]);
print("Dirty cache %:     " + ((cache["tracked dirty bytes in the cache"] / cache["maximum bytes configured"]) * 100).toFixed(2) + "%");

// 2. Measure replica set replication lag across secondaries
const status = rs.status();
const primaryOptime = status.members.find(m => m.stateStr === "PRIMARY").optimeDate;
status.members.forEach(m => {
  if (m.stateStr === "SECONDARY") {
    const lagSeconds = (primaryOptime - m.optimeDate) / 1000;
    print(m.name + " (" + m.stateStr + ") lag: " + lagSeconds + "s");
  }
});

Inspects consumed capacity metrics, identifies throttle spikes, and verifies table-level partition limits.

# 1. Inspect consumed read/write capacity vs throttled request spikes
aws cloudwatch get-metric-data \
  --metric-data-queries '[
    {
      "Id": "consumed_reads",
      "MetricStat": {
        "Metric": {"Namespace": "AWS/DynamoDB", "MetricName": "ConsumedReadCapacityUnits", "Dimensions": [{"Name": "TableName", "Value": "prod_users"}]},
        "Period": 300,
        "Stat": "Sum"
      }
    },
    {
      "Id": "throttled_events",
      "MetricStat": {
        "Metric": {"Namespace": "AWS/DynamoDB", "MetricName": "ThrottledRequests", "Dimensions": [{"Name": "TableName", "Value": "prod_users"}]},
        "Period": 300,
        "Stat": "Sum"
      }
    }
  ]' \
  --start-time "$(date -u -v-2H +%Y-%m-%dT%H:%M:%SZ)" \
  --end-time "$(date -u +%Y-%m-%dT%H:%M:%SZ)"