Monitoring & Observability
Grafana Loki Logging Setup
Grafana Loki is a log aggregation system designed to be cost-effective and operationally simple. Unlike Elasticsearch, Loki only indexes log metadata (labels) — not the full log content — and stores compressed log chunks in object storage. The result is 10x lower storage costs with query performance that's more than sufficient for most teams.
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We implement, you ship. Async, documented, done in days.
What We Deliver
A production-ready Loki deployment with Promtail or Grafana Alloy agents for log collection, Loki configured with object storage backend (S3, GCS, or MinIO), Grafana data source integration, LogQL queries and dashboards, alerting rules via Grafana or Loki Ruler, and retention policies with automated cleanup.
Why Loki Over Elasticsearch
Loki is dramatically cheaper to run. It doesn't require beefy nodes for inverted indexes — log data is compressed and stored in object storage at pennies per GB. Operations are simpler — no shard management, no JVM tuning, no cluster rebalancing. The trade-off is query speed on high-cardinality searches, but for 95% of logging use cases, Loki's performance is excellent. If you're already using Grafana for metrics, Loki is the natural choice for logs.
Deployment Architecture
For small to medium deployments, we use Loki in monolithic or simple scalable mode — a single binary that handles all functions. For high-volume deployments, we use microservice mode with separate read, write, and backend components on Kubernetes. Object storage (S3, GCS) stores log chunks. A small cache (memcached or Redis) accelerates frequent queries.
Log Collection
Promtail or Grafana Alloy agents run on each host or as Kubernetes DaemonSets. They discover log files and containers automatically, attach metadata labels (namespace, pod, container, node), and ship logs to Loki. Pipeline stages parse, filter, and transform logs before ingestion. Multi-line log joining handles stack traces correctly.
LogQL & Dashboards
LogQL — Loki's query language — combines log filtering with metric extraction. We build dashboards that show: log volume by service, error rate derived from log lines, latency extracted from access logs, and custom metrics from structured log fields. Correlating logs with Prometheus metrics in the same Grafana dashboard provides unified troubleshooting.
How It Works
Purchase the engagement, submit your async brief with your log volume and infrastructure details, and receive a production-ready Loki deployment within 5–7 business days. Agent configuration, dashboards, and alerting rules included.
Why Anubiz Engineering
100% async — no calls, no meetings
Delivered in days, not weeks
Full documentation included
Production-grade from day one
Security-first approach
Post-delivery support included
Ready to get started?
Skip the research. Tell us what you need, and we'll scope it, implement it, and hand it back — fully documented and production-ready.