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Grafana Loki 全面指南：经济高效的日志聚合系统部署与配置

loki by julianobarbosa/claude-code-skills

66 周安装量

44 GitHub Stars

GitHub

安装命令

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

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🇨🇳中文介绍

Grafana Loki 技能

Grafana Loki 的全面指南——这是一款受 Prometheus 启发的、经济高效、可水平扩展的日志聚合系统。

什么是 Loki？

Loki 是一个可水平扩展、高可用、多租户的日志聚合系统，它：

仅索引元数据（标签） - 不像传统系统那样索引完整的日志内容
将压缩后的数据块存储在成本低廉的对象存储中（S3、GCS、Azure Blob）
使用 Prometheus 风格的标签来组织日志流
默认支持多租户，内置租户隔离
经济高效 - 索引大小显著减小，运营成本更低

架构概述

核心组件

组件	用途
Distributor	验证请求，预处理标签，路由到 ingester
Ingester	在内存中缓冲日志，压缩成数据块，写入存储
Querier	从 ingester 和存储中执行 LogQL 查询
Query Frontend	通过拆分、缓存、调度来加速查询
Query Scheduler

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1. 单体模式 (`-target=all`)

所有组件在单个进程中运行
最适合：初步实验、小规模（约 20GB 日志/天）
最简单的方法

2. 简单可扩展部署（SSD）- 推荐默认配置

deploymentMode: SimpleScalable

write:
  replicas: 3   # Distributor + Ingester

read:
  replicas: 2   # Query Frontend + Querier

backend:
  replicas: 2   # Compactor + Index Gateway + Query Scheduler + Ruler

3. 微服务模式（分布式）

deploymentMode: Distributed

ingester:
  replicas: 3
  zoneAwareReplication:
    enabled: true

distributor:
  replicas: 3

querier:
  replicas: 3

queryFrontend:
  replicas: 2

queryScheduler:
  replicas: 2

compactor:
  replicas: 1

indexGateway:
  replicas: 2

推荐：使用 Schema v13 的 TSDB

loki:
  schemaConfig:
    configs:
      - from: "2024-04-01"
        store: tsdb
        object_store: azure  # or s3, gcs
        schema: v13
        index:
          prefix: loki_index_
          period: 24h

Azure Blob 存储（Azure 环境推荐）

loki:
  storage:
    type: azure
    bucketNames:
      chunks: loki-chunks
      ruler: loki-ruler
      admin: loki-admin
    azure:
      accountName: <storage-account-name>
      # 选项 1：用户分配的托管标识（推荐）
      useManagedIdentity: true
      useFederatedToken: false
      userAssignedId: <identity-client-id>
      # 选项 2：账户密钥（仅限开发）
      # accountKey: <account-key>
      requestTimeout: 30s

loki:
  storage:
    type: s3
    bucketNames:
      chunks: my-loki-chunks-2024
      ruler: my-loki-ruler-2024
      admin: my-loki-admin-2024
    s3:
      endpoint: s3.us-east-1.amazonaws.com
      region: us-east-1
      # 使用 IAM 角色或访问密钥
      accessKeyId: <access-key>
      secretAccessKey: <secret-key>
      s3ForcePathStyle: false

loki:
  storage:
    type: gcs
    bucketNames:
      chunks: my-loki-gcs-bucket
    gcs:
      bucketName: my-loki-gcs-bucket
      # 使用 Workload Identity 或服务账户

数据块配置最佳实践

loki:
  ingester:
    chunk_encoding: snappy        # 推荐（快速且高效）
    chunk_target_size: 1572864    # ~1.5MB 压缩后
    max_chunk_age: 2h             # 刷新前的最大时间
    chunk_idle_period: 30m        # 刷新空闲的数据块
    flush_check_period: 30s
    flush_op_timeout: 10m

设置	推荐值	用途
`chunk_encoding`	snappy	速度与压缩比的最佳平衡
`chunk_target_size`	1.5MB	目标压缩数据块大小
`max_chunk_age`	2h	限制内存占用和数据丢失风险
`chunk_idle_period`	30m	刷新非活动流

loki:
  limits_config:
    # 保留策略
    retention_period: 744h              # 31 天

    # 摄取限制
    ingestion_rate_mb: 50
    ingestion_burst_size_mb: 100
    per_stream_rate_limit: 3MB
    per_stream_rate_limit_burst: 15MB

    # 查询限制
    max_query_series: 10000
    max_query_lookback: 720h
    max_entries_limit_per_query: 10000

    # OTLP 必需
    allow_structured_metadata: true
    volume_enabled: true

    # 样本拒绝
    reject_old_samples: true
    reject_old_samples_max_age: 168h    # 7 天
    max_label_names_per_series: 25

loki:
  compactor:
    retention_enabled: true
    retention_delete_delay: 2h
    retention_delete_worker_count: 50
    compaction_interval: 10m
    delete_request_store: azure         # 匹配您的存储类型

推荐：独立的 Memcached 实例

# Loki 缓存的 Helm 值
memcached:
  # 结果缓存
  frontend:
    replicas: 3
    memcached:
      maxItemMemory: 1024               # 1GB
      maxItemSize: 5m
      connectionLimit: 1024

  # 数据块缓存
  chunks:
    replicas: 3
    memcached:
      maxItemMemory: 4096               # 4GB
      maxItemSize: 2m
      connectionLimit: 1024

# 在 Loki 配置中启用缓存
loki:
  chunk_store_config:
    chunk_cache_config:
      memcached_client:
        host: loki-memcached-chunks.monitoring.svc
        service: memcached-client

# 流选择器
{job="api-server"}

# 多个标签
{job="api-server", env="prod"}

# 标签匹配器
{namespace=~".*-prod"}           # 正则匹配
{level!="debug"}                  # 不等于

# 过滤表达式
{job="api-server"} |= "error"     # 包含
{job="api-server"} != "debug"     # 不包含
{job="api-server"} |~ "err.*"     # 正则匹配
{job="api-server"} !~ "debug.*"   # 正则不匹配

# JSON 解析
{job="api-server"} | json

# 提取特定字段
{job="api-server"} | json | line_format "{{.message}}"

# 标签提取
{job="api-server"} | logfmt | level="error"

# 模式匹配
{job="api-server"} | pattern "<ip> - - [<_>] \"<method> <path>\"" | method="POST"

# 每分钟日志计数
count_over_time({job="api-server"}[1m])

# 错误率
rate({job="api-server"} |= "error" [5m])

# 字节速率
bytes_rate({job="api-server"}[5m])

# 按标签求和
sum by (namespace) (rate({job="api-server"}[5m]))

# 按流量排名前 10
topk(10, sum by (namespace) (bytes_rate({}[5m])))

OpenTelemetry 集成

原生 OTLP（推荐 - Loki 3.0+）

OpenTelemetry Collector 配置：

exporters:
  otlphttp:
    endpoint: http://loki-gateway:3100/otlp
    headers:
      X-Scope-OrgID: "my-tenant"

service:
  pipelines:
    logs:
      receivers: [otlp]
      exporters: [otlphttp]

loki:
  limits_config:
    allow_structured_metadata: true    # OTLP 必需

日志正文以纯文本形式存储（非 JSON 编码）
17 个默认资源属性自动索引
无需 JSON 解析的简化查询
更好的存储效率

OTLP 属性	Loki 标签
`service.name`	`service_name`
`service.namespace`	`service_namespace`
`k8s.pod.name`	`k8s_pod_name`
`k8s.namespace.name`	`k8s_namespace_name`
`cloud.region`	`cloud_region`

Kubernetes Helm 部署

helm repo add grafana https://grafana.github.io/helm-charts
helm repo update

使用 Values 文件安装

helm install loki grafana/loki \
  --namespace monitoring \
  --values values.yaml

生产环境 Values 示例

deploymentMode: Distributed

loki:
  auth_enabled: true

  schemaConfig:
    configs:
      - from: "2024-04-01"
        store: tsdb
        object_store: azure
        schema: v13
        index:
          prefix: loki_index_
          period: 24h

  storage:
    type: azure
    azure:
      accountName: mystorageaccount
      useManagedIdentity: true
      userAssignedId: <client-id>
    bucketNames:
      chunks: loki-chunks
      ruler: loki-ruler
      admin: loki-admin

  limits_config:
    retention_period: 2160h             # 90 天
    allow_structured_metadata: true

ingester:
  replicas: 3
  zoneAwareReplication:
    enabled: true
  resources:
    requests:
      cpu: 2
      memory: 8Gi
    limits:
      cpu: 4
      memory: 16Gi

querier:
  replicas: 3
  maxUnavailable: 2

queryFrontend:
  replicas: 2

distributor:
  replicas: 3

compactor:
  replicas: 1

indexGateway:
  replicas: 2
  maxUnavailable: 1

# 用于外部访问的网关
gateway:
  service:
    type: LoadBalancer

# 监控
monitoring:
  serviceMonitor:
    enabled: true

用户分配的托管标识（推荐）

1. 创建标识：

az identity create \
  --name loki-identity \
  --resource-group <rg>

IDENTITY_CLIENT_ID=$(az identity show --name loki-identity --resource-group <rg> --query clientId -o tsv)
IDENTITY_PRINCIPAL_ID=$(az identity show --name loki-identity --resource-group <rg> --query principalId -o tsv)

2. 分配给节点池：

az vmss identity assign \
  --resource-group <aks-node-rg> \
  --name <vmss-name> \
  --identities /subscriptions/<sub>/resourceGroups/<rg>/providers/Microsoft.ManagedIdentity/userAssignedIdentities/loki-identity

3. 授予存储权限：

az role assignment create \
  --role "Storage Blob Data Contributor" \
  --assignee-object-id $IDENTITY_PRINCIPAL_ID \
  --scope /subscriptions/<sub>/resourceGroups/<rg>/providers/Microsoft.Storage/storageAccounts/<storage>

4. 配置 Loki：

loki:
  storage:
    azure:
      useManagedIdentity: true
      userAssignedId: <IDENTITY_CLIENT_ID>

loki:
  auth_enabled: true

# 使用租户头信息查询
curl -H "X-Scope-OrgID: tenant-a" \
  "http://loki:3100/loki/api/v1/query?query={job=\"app\"}"

# 多租户查询（如果启用）
# X-Scope-OrgID: tenant-a|tenant-b

1. 容器未找到（Azure）

# 创建所需的容器
az storage container create --name loki-chunks --account-name <storage>
az storage container create --name loki-ruler --account-name <storage>
az storage container create --name loki-admin --account-name <storage>

2. 授权失败（Azure）

# 验证 RBAC 分配
az role assignment list --scope /subscriptions/<sub>/resourceGroups/<rg>/providers/Microsoft.Storage/storageAccounts/<storage>

# 如果缺失则分配
az role assignment create \
  --role "Storage Blob Data Contributor" \
  --assignee-object-id <principal-id> \
  --scope <storage-scope>

# 重启 pod 以刷新令牌
kubectl delete pod -n monitoring <ingester-pod>

# 增加内存限制
ingester:
  resources:
    limits:
      memory: 16Gi

loki:
  querier:
    query_timeout: 5m
    max_concurrent: 8
  query_scheduler:
    max_outstanding_requests_per_tenant: 2048

# 检查 pod 状态
kubectl get pods -n monitoring -l app.kubernetes.io/name=loki

# 检查 ingester 日志
kubectl logs -n monitoring -l app.kubernetes.io/component=ingester --tail=100

# 检查 compactor 日志
kubectl logs -n monitoring -l app.kubernetes.io/component=compactor --tail=100

# 验证就绪状态
kubectl exec -it <loki-pod> -n monitoring -- wget -qO- http://localhost:3100/ready

# 检查配置
kubectl exec -it <loki-pod> -n monitoring -- cat /etc/loki/config/config.yaml

# 推送日志
POST /loki/api/v1/push

# OTLP 日志
POST /otlp/v1/logs

# 即时查询
GET /loki/api/v1/query?query={job="app"}&time=<timestamp>

# 范围查询
GET /loki/api/v1/query_range?query={job="app"}&start=<start>&end=<end>

# 标签
GET /loki/api/v1/labels
GET /loki/api/v1/label/<name>/values

# 序列
GET /loki/api/v1/series

# 尾部（WebSocket）
GET /loki/api/v1/tail?query={job="app"}

GET /ready
GET /metrics

按主题的详细配置：

存储配置：对象存储、保留策略、WAL
LogQL 参考：查询语法和示例
OpenTelemetry 集成：OTLP 配置

2026 年 1 月 24 日

🇺🇸English

Grafana Loki Skill

Comprehensive guide for Grafana Loki - the cost-effective, horizontally-scalable log aggregation system inspired by Prometheus.

What is Loki?

Loki is a horizontally-scalable, highly-available, multi-tenant log aggregation system that:

Indexes only metadata (labels) - Not full log content like traditional systems
Stores compressed chunks in affordable object storage (S3, GCS, Azure Blob)
Uses Prometheus-style labels for organizing log streams
Multi-tenant by default with built-in tenant isolation
Cost-efficient - Dramatically smaller index and lower operational costs

Architecture Overview

Core Components

Component	Purpose
Distributor	Validates requests, preprocesses labels, routes to ingesters
Ingester	Buffers logs in memory, compresses into chunks, writes to storage
Querier	Executes LogQL queries from ingesters and storage
Query Frontend	Accelerates queries via splitting, caching, scheduling
Query Scheduler	Manages per-tenant query queues for fairness
Index Gateway	Serves index queries for TSDB stores
Compactor	Merges index files, manages retention, handles deletion
Ruler	Evaluates alerting and recording rules

Data Flow

Write Path:

Log Source → Distributor → Ingester → Object Storage
                                    ↓
                              Chunks + Indexes

Read Path:

Query → Query Frontend → Query Scheduler → Querier
                                             ↓
                                    Ingesters + Storage

Deployment Modes

1. Monolithic Mode (`-target=all`)

All components in single process
Best for: Initial experimentation, small-scale (~20GB logs/day)
Simplest approach

2. Simple Scalable Deployment (SSD) - Recommended Default

deploymentMode: SimpleScalable

write:
  replicas: 3   # Distributor + Ingester

read:
  replicas: 2   # Query Frontend + Querier

backend:
  replicas: 2   # Compactor + Index Gateway + Query Scheduler + Ruler

3. Microservices Mode (Distributed)

deploymentMode: Distributed

ingester:
  replicas: 3
  zoneAwareReplication:
    enabled: true

distributor:
  replicas: 3

querier:
  replicas: 3

queryFrontend:
  replicas: 2

queryScheduler:
  replicas: 2

compactor:
  replicas: 1

indexGateway:
  replicas: 2

Schema Configuration

Recommended: TSDB with Schema v13

loki:
  schemaConfig:
    configs:
      - from: "2024-04-01"
        store: tsdb
        object_store: azure  # or s3, gcs
        schema: v13
        index:
          prefix: loki_index_
          period: 24h

Storage Configuration

Azure Blob Storage (Recommended for Azure)

loki:
  storage:
    type: azure
    bucketNames:
      chunks: loki-chunks
      ruler: loki-ruler
      admin: loki-admin
    azure:
      accountName: <storage-account-name>
      # Option 1: User-Assigned Managed Identity (Recommended)
      useManagedIdentity: true
      useFederatedToken: false
      userAssignedId: <identity-client-id>
      # Option 2: Account Key (Dev only)
      # accountKey: <account-key>
      requestTimeout: 30s

AWS S3

loki:
  storage:
    type: s3
    bucketNames:
      chunks: my-loki-chunks-2024
      ruler: my-loki-ruler-2024
      admin: my-loki-admin-2024
    s3:
      endpoint: s3.us-east-1.amazonaws.com
      region: us-east-1
      # Use IAM roles or access keys
      accessKeyId: <access-key>
      secretAccessKey: <secret-key>
      s3ForcePathStyle: false

Google Cloud Storage

loki:
  storage:
    type: gcs
    bucketNames:
      chunks: my-loki-gcs-bucket
    gcs:
      bucketName: my-loki-gcs-bucket
      # Uses Workload Identity or service account

Chunk Configuration Best Practices

loki:
  ingester:
    chunk_encoding: snappy        # Recommended (fast + efficient)
    chunk_target_size: 1572864    # ~1.5MB compressed
    max_chunk_age: 2h             # Max time before flush
    chunk_idle_period: 30m        # Flush idle chunks
    flush_check_period: 30s
    flush_op_timeout: 10m

Setting	Recommended	Purpose
`chunk_encoding`	snappy	Best speed-to-compression balance
`chunk_target_size`	1.5MB	Target compressed chunk size
`max_chunk_age`	2h	Limits memory and data loss exposure
`chunk_idle_period`	30m	Flushes inactive streams

Limits Configuration

loki:
  limits_config:
    # Retention
    retention_period: 744h              # 31 days

    # Ingestion limits
    ingestion_rate_mb: 50
    ingestion_burst_size_mb: 100
    per_stream_rate_limit: 3MB
    per_stream_rate_limit_burst: 15MB

    # Query limits
    max_query_series: 10000
    max_query_lookback: 720h
    max_entries_limit_per_query: 10000

    # Required for OTLP
    allow_structured_metadata: true
    volume_enabled: true

    # Sample rejection
    reject_old_samples: true
    reject_old_samples_max_age: 168h    # 7 days
    max_label_names_per_series: 25

Compactor Configuration

loki:
  compactor:
    retention_enabled: true
    retention_delete_delay: 2h
    retention_delete_worker_count: 50
    compaction_interval: 10m
    delete_request_store: azure         # Match your storage type

Caching Configuration

Recommended: Separate Memcached instances

# Helm values for Loki caching
memcached:
  # Results cache
  frontend:
    replicas: 3
    memcached:
      maxItemMemory: 1024               # 1GB
      maxItemSize: 5m
      connectionLimit: 1024

  # Chunks cache
  chunks:
    replicas: 3
    memcached:
      maxItemMemory: 4096               # 4GB
      maxItemSize: 2m
      connectionLimit: 1024

# Enable caching in Loki config
loki:
  chunk_store_config:
    chunk_cache_config:
      memcached_client:
        host: loki-memcached-chunks.monitoring.svc
        service: memcached-client

LogQL Query Language

Basic Queries

# Stream selector
{job="api-server"}

# Multiple labels
{job="api-server", env="prod"}

# Label matchers
{namespace=~".*-prod"}           # Regex match
{level!="debug"}                  # Not equal

# Filter expressions
{job="api-server"} |= "error"     # Contains
{job="api-server"} != "debug"     # Not contains
{job="api-server"} |~ "err.*"     # Regex match
{job="api-server"} !~ "debug.*"   # Regex not match

Pipeline Stages

# JSON parsing
{job="api-server"} | json

# Extract specific fields
{job="api-server"} | json | line_format "{{.message}}"

# Label extraction
{job="api-server"} | logfmt | level="error"

# Pattern matching
{job="api-server"} | pattern "<ip> - - [<_>] \"<method> <path>\"" | method="POST"

Metric Queries

# Count logs per minute
count_over_time({job="api-server"}[1m])

# Rate of errors
rate({job="api-server"} |= "error" [5m])

# Bytes rate
bytes_rate({job="api-server"}[5m])

# Sum by label
sum by (namespace) (rate({job="api-server"}[5m]))

# Top 10 by volume
topk(10, sum by (namespace) (bytes_rate({}[5m])))

OpenTelemetry Integration

Native OTLP (Recommended - Loki 3.0+)

OpenTelemetry Collector Config:

exporters:
  otlphttp:
    endpoint: http://loki-gateway:3100/otlp
    headers:
      X-Scope-OrgID: "my-tenant"

service:
  pipelines:
    logs:
      receivers: [otlp]
      exporters: [otlphttp]

Loki Config:

loki:
  limits_config:
    allow_structured_metadata: true    # Required for OTLP

Key Benefits:

Log body stored as plain text (not JSON encoded)
17 default resource attributes auto-indexed
Simpler queries without JSON parsing
Better storage efficiency

Resource Attribute Mapping

OTLP Attribute	Loki Label
`service.name`	`service_name`
`service.namespace`	`service_namespace`
`k8s.pod.name`	`k8s_pod_name`
`k8s.namespace.name`	`k8s_namespace_name`

Kubernetes Helm Deployment

Add Repository

helm repo add grafana https://grafana.github.io/helm-charts
helm repo update

Install with Values

helm install loki grafana/loki \
  --namespace monitoring \
  --values values.yaml

Production Values Example

deploymentMode: Distributed

loki:
  auth_enabled: true

  schemaConfig:
    configs:
      - from: "2024-04-01"
        store: tsdb
        object_store: azure
        schema: v13
        index:
          prefix: loki_index_
          period: 24h

  storage:
    type: azure
    azure:
      accountName: mystorageaccount
      useManagedIdentity: true
      userAssignedId: <client-id>
    bucketNames:
      chunks: loki-chunks
      ruler: loki-ruler
      admin: loki-admin

  limits_config:
    retention_period: 2160h             # 90 days
    allow_structured_metadata: true

ingester:
  replicas: 3
  zoneAwareReplication:
    enabled: true
  resources:
    requests:
      cpu: 2
      memory: 8Gi
    limits:
      cpu: 4
      memory: 16Gi

querier:
  replicas: 3
  maxUnavailable: 2

queryFrontend:
  replicas: 2

distributor:
  replicas: 3

compactor:
  replicas: 1

indexGateway:
  replicas: 2
  maxUnavailable: 1

# Gateway for external access
gateway:
  service:
    type: LoadBalancer

# Monitoring
monitoring:
  serviceMonitor:
    enabled: true

Azure Identity Configuration

User-Assigned Managed Identity (Recommended)

1. Create Identity:

az identity create \
  --name loki-identity \
  --resource-group <rg>

IDENTITY_CLIENT_ID=$(az identity show --name loki-identity --resource-group <rg> --query clientId -o tsv)
IDENTITY_PRINCIPAL_ID=$(az identity show --name loki-identity --resource-group <rg> --query principalId -o tsv)

2. Assign to Node Pool:

az vmss identity assign \
  --resource-group <aks-node-rg> \
  --name <vmss-name> \
  --identities /subscriptions/<sub>/resourceGroups/<rg>/providers/Microsoft.ManagedIdentity/userAssignedIdentities/loki-identity

3. Grant Storage Permission:

az role assignment create \
  --role "Storage Blob Data Contributor" \
  --assignee-object-id $IDENTITY_PRINCIPAL_ID \
  --scope /subscriptions/<sub>/resourceGroups/<rg>/providers/Microsoft.Storage/storageAccounts/<storage>

4. Configure Loki:

loki:
  storage:
    azure:
      useManagedIdentity: true
      userAssignedId: <IDENTITY_CLIENT_ID>

Multi-Tenancy

loki:
  auth_enabled: true

# Query with tenant header
curl -H "X-Scope-OrgID: tenant-a" \
  "http://loki:3100/loki/api/v1/query?query={job=\"app\"}"

# Multi-tenant queries (if enabled)
# X-Scope-OrgID: tenant-a|tenant-b

Troubleshooting

Common Issues

1. Container Not Found (Azure)

# Create required containers
az storage container create --name loki-chunks --account-name <storage>
az storage container create --name loki-ruler --account-name <storage>
az storage container create --name loki-admin --account-name <storage>

2. Authorization Failure (Azure)

# Verify RBAC assignment
az role assignment list --scope /subscriptions/<sub>/resourceGroups/<rg>/providers/Microsoft.Storage/storageAccounts/<storage>

# Assign if missing
az role assignment create \
  --role "Storage Blob Data Contributor" \
  --assignee-object-id <principal-id> \
  --scope <storage-scope>

# Restart pod to refresh token
kubectl delete pod -n monitoring <ingester-pod>

3. Ingester OOM

# Increase memory limits
ingester:
  resources:
    limits:
      memory: 16Gi

4. Query Timeout

loki:
  querier:
    query_timeout: 5m
    max_concurrent: 8
  query_scheduler:
    max_outstanding_requests_per_tenant: 2048

Diagnostic Commands

# Check pod status
kubectl get pods -n monitoring -l app.kubernetes.io/name=loki

# Check ingester logs
kubectl logs -n monitoring -l app.kubernetes.io/component=ingester --tail=100

# Check compactor logs
kubectl logs -n monitoring -l app.kubernetes.io/component=compactor --tail=100

# Verify readiness
kubectl exec -it <loki-pod> -n monitoring -- wget -qO- http://localhost:3100/ready

# Check configuration
kubectl exec -it <loki-pod> -n monitoring -- cat /etc/loki/config/config.yaml

API Reference

Ingestion

# Push logs
POST /loki/api/v1/push

# OTLP logs
POST /otlp/v1/logs

Query

# Instant query
GET /loki/api/v1/query?query={job="app"}&time=<timestamp>

# Range query
GET /loki/api/v1/query_range?query={job="app"}&start=<start>&end=<end>

# Labels
GET /loki/api/v1/labels
GET /loki/api/v1/label/<name>/values

# Series
GET /loki/api/v1/series

# Tail (WebSocket)
GET /loki/api/v1/tail?query={job="app"}

Health

GET /ready
GET /metrics

Reference Documentation

For detailed configuration by topic:

Storage Configuration : Object stores, retention, WAL
LogQL Reference : Query syntax and examples
OpenTelemetry Integration : OTLP configuration

External Resources

Weekly Installs

Repository

julianobarbosa/…e-skills

GitHub Stars

First Seen

Jan 24, 2026

Security Audits

Gen Agent Trust HubPass SocketPass SnykPass

Installed on

codex56

opencode56

cursor55

gemini-cli55

github-copilot53

claude-code49

Azure 升级评估与自动化工具 - 轻松迁移 Functions 计划、托管层级和 SKU

111,700 周安装

Grafana Loki 全面指南：经济高效的日志聚合系统部署与配置

🇨🇳中文介绍

Grafana Loki 技能

什么是 Loki？

架构概述

核心组件

相关 Skills

数据流

部署模式

1. 单体模式 (-target=all)

2. 简单可扩展部署（SSD）- 推荐默认配置

3. 微服务模式（分布式）

模式配置

存储配置

Azure Blob 存储（Azure 环境推荐）

AWS S3

Google Cloud 存储

数据块配置最佳实践

限制配置

Compactor 配置

缓存配置

LogQL 查询语言

基础查询

流水线阶段

指标查询

OpenTelemetry 集成

原生 OTLP（推荐 - Loki 3.0+）

资源属性映射

Kubernetes Helm 部署

添加仓库

使用 Values 文件安装

生产环境 Values 示例

Azure 身份配置

用户分配的托管标识（推荐）

多租户

故障排除

常见问题

诊断命令

API 参考

摄取

查询

健康检查

参考文档

外部资源

🇺🇸English

Grafana Loki Skill

What is Loki?

Architecture Overview

Core Components

Data Flow

Deployment Modes

1. Monolithic Mode (-target=all)

2. Simple Scalable Deployment (SSD) - Recommended Default

3. Microservices Mode (Distributed)

Schema Configuration

Storage Configuration

Azure Blob Storage (Recommended for Azure)

AWS S3

Google Cloud Storage

Chunk Configuration Best Practices

Limits Configuration

Compactor Configuration

Caching Configuration

LogQL Query Language

Basic Queries

Pipeline Stages

Metric Queries

OpenTelemetry Integration

Native OTLP (Recommended - Loki 3.0+)

Resource Attribute Mapping

Kubernetes Helm Deployment

Add Repository

Install with Values

Production Values Example

Azure Identity Configuration

User-Assigned Managed Identity (Recommended)

Multi-Tenancy

Troubleshooting

Common Issues

Diagnostic Commands

1. 单体模式 (`-target=all`)

1. Monolithic Mode (`-target=all`)