How do you scale Prometheus for a large environment?

Prometheus is a single-node system, so for large environments:

• Use multiple Prometheus instances scraping different targets.
• Federation: Create a parent Prometheus that scrapes aggregated metrics from child Prometheus instances.
• Remote storage: Use Thanos, Cortex, or Mimir to store metrics in scalable object storage (S3, GCS).
• Sharding: Distribute scraping targets across Prometheus instances using load balancing tools like Kube StatefulSets.

How does Prometheus handle stale or missing metrics?

• Stale markers: Prometheus marks time-series data as stale if a target stops reporting metrics.
• Absent function (absent()): Used in PromQL to detect missing metrics.
• Dead Man's Switch: A constant alert (e.g., ALWAYS_ON) ensures the alerting system is functional.

Example:

absent(up{job="my_service"})

Triggers an alert if up{job="my_service"} is missing.

What is Prometheus WAL (Write-Ahead Log) and its purpose?

The Write-Ahead Log (WAL) in Prometheus:

• Stores data on disk before committing it to TSDB (Time-Series Database).
• Reduces data loss during crashes.
• WAL files are stored in /data/wal/ and help recover metrics quickly after a restart.

What are Histogram and Summary metrics in Prometheus?

Both are used for measuring latency and response time:

• Histogram: Buckets data into predefined ranges, allowing percentiles to be calculated later.
• Summary: Precomputes percentiles but cannot be aggregated across instances.

Example (Histogram metric):

histogram_quantile(0.95, rate(http_request_duration_seconds_bucket[5m]))

This calculates the 95th percentile response time.

How do you secure Prometheus endpoints?

• Enable authentication & TLS via a reverse proxy (Nginx, Traefik).
• Use RBAC (Role-Based Access Control) in Kubernetes for limiting access.
• Set up network policies to restrict Prometheus access.

Example: Using basic auth with Nginx:

server {
  listen 9090;
  location / {
    auth_basic "Restricted";
    auth_basic_user_file /etc/nginx/.htpasswd;
  }
}

How do you monitor Prometheus itself using Grafana?

• Enable the built-in Prometheus self-metrics endpoint (/metrics).
• Use dashboards to monitor scrape latency, TSDB memory usage, query duration.
• Use the Prometheus Federation API to get meta-metrics.

What are Grafana Annotations and how are they useful?

Annotations mark events (deployments, incidents, downtimes) on Grafana graphs for better visualization.
Example: Mark a Kubernetes deployment event in Grafana.

How do you configure Grafana for multi-tenancy?

• Organizations: Create multiple teams with separate dashboards.
• Data source permissions: Restrict access at the data-source level.
• Multi-instance deployment: Run separate Grafana instances for different teams.

What is Alerting in Grafana and how does it work?

• Grafana alerts monitor query conditions.
• Alert states: OK, Pending, Alerting, No Data.
• Notification channels: Slack, PagerDuty, Email, Webhooks.

Example Grafana alert condition:

• avg(http_requests_total) > 1000 → Sends an alert if requests exceed 1000.

How does Loki compare with Elasticsearch for logging?

Loki is recommended for lightweight, Kubernetes-native logging, while Elasticsearch is better for complex log analysis.

What is the Hot-Warm-Cold architecture in Elasticsearch?

This strategy optimizes storage cost:

• Hot Nodes → Store recent, frequently queried data.
• Warm Nodes → Store older logs with infrequent access.
• Cold Nodes → Store archived logs for long-term retention.

How do you reduce indexing pressure in Elasticsearch?

• Use ILM (Index Lifecycle Management).
• Optimize shard count (Avoid too many small shards).
• Increase refresh intervals (index.refresh_interval: 30s).

How does Logstash manage backpressure?

• Persistent Queues → Buffer data before sending to Elasticsearch.
• Dead Letter Queue (DLQ) → Stores failed events for reprocessing.

Example:

queue.type: persisted
queue.max_bytes: 1gb

What are Query Caching strategies in Elasticsearch?

• Request cache: Stores query results.
• Shard request cache: Caches aggregations and filters.
• Doc value cache: Optimizes sorting and aggregations.

How do you use Kibana for anomaly detection?

• Machine Learning Jobs → Identify unusual trends in logs.
• SIEM (Security Information and Event Management) → Detect security threats.

Example anomaly detection job:

{
  "analysis_config": {
    "bucket_span": "15m",
    "detectors": [{ "function": "mean", "field_name": "cpu_usage" }]
  }
}

How do you secure Elasticsearch clusters?

• Enable TLS (xpack.security.enabled: true).
• Use API Key authentication.
• Implement firewall rules to restrict access.

How do you integrate Prometheus with Elasticsearch?

Use Metricbeat with the Prometheus module to collect metrics and store them in Elasticsearch. This allows you to:

• Visualize Prometheus metrics in Kibana
• Combine metrics with logs for better correlation
• Use Elasticsearch's powerful search capabilities on metric data