loki

Deploy Grafana Loki with Helm and configure LogQL queries.

7|1|Updated Jul 12, 2026

Search Tags:#kubernetes #log aggregation #helm #retention #logql #loki #storage-backends

Ready to run

npx skills add https://github.com/julianobarbosa/claude-code-skills --skill loki

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: loki
Source: https://github.com/julianobarbosa/claude-code-skills/tree/main/skills/loki
Command: npx skills add https://github.com/julianobarbosa/claude-code-skills --skill loki

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill guides you through deploying and operating Grafana Loki, simplifying horizontally scalable log aggregation, storage backends (S3, GCS, Azure Blob), and LogQL-powered queries in Kubernetes environments.

Core Features & Use Cases

Unified log ingestion and querying: Configure Loki components (Distributor, Ingesters, Querier) to collect and query logs efficiently.
Storage backends & retention: Set up object storage backends, retention, and compaction strategies.
Deployment guidance: Helm-based deployments and multi-mode strategies for scalable log infrastructure.

Quick Start

Example: Deploy Loki with a TSDB-backed storage and write basic LogQL queries to locate errors in your cluster logs.

Frequently Asked Questions about loki

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I deploy Loki for log aggregation in Kubernetes?▼

Deploy Loki in Kubernetes using Helm charts configured with a storage backend (S3, GCS, or Azure Blob), Distributor, Ingester, and Querier components. Helm streamlines multi-mode scaling and object storage setup for horizontally scalable log collection and indexing.

What storage backends does Loki support for log retention?▼

Loki supports S3, GCS, and Azure Blob as object storage backends. Configure retention policies and compaction strategies within your chosen backend to manage log lifecycle and reduce storage costs at scale.

How do I query logs with LogQL in Loki?▼

LogQL is Loki's query language for filtering and aggregating logs by labels and metadata. Write queries to locate errors, trace requests across cluster logs, and extract metrics from structured log streams ingested by Loki.

Can I use Loki for multi-tenant log isolation?▼

Yes, Loki supports multi-tenant isolation through metadata-based label indexing and TSDB schema configurations. This enables secure log separation and independent retention policies across multiple tenants in a single deployment.

Does Loki integrate with OpenTelemetry collectors?▼

Loki integrates with OTLP collectors to ingest logs alongside traces and metrics. This unified observability pipeline simplifies log collection from distributed systems and enables correlation with telemetry data.

What are the retention and compaction options in Loki?▼

Loki offers configurable retention policies and compaction strategies to manage log chunk lifecycle in object storage. These settings control how long logs remain queryable and optimize storage efficiency for large-scale deployments.