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Asim Aslam 4311b73361 Enhance ADK vs Go Micro comparison and apply lint fixes (#2994)
* docs: compare Go Micro with Google ADK in the comparison guide

Adds a 'vs Agent Frameworks (Google ADK)' section: ADK builds an agent,
Go Micro builds the distributed system the agent lives in (agents are
services in the mesh). Covers the category difference, a feature table,
when to choose each, and MCP/A2A interoperability.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL

* docs: replace ADK comparison slogan with concrete explanation

State plainly what each tool provides (ADK builds an agent process; Go Micro
builds the surrounding service mesh) instead of marketing phrasing.

* lint: apply golangci-lint autofixes; exclude ST1003 and demo errcheck

Mechanical, behaviour-preserving fixes applied by 'golangci-lint run --fix':
gofmt, misspell (US spelling), usestdlibvars (http.Method*/Status*), unconvert,
and the auto-fixable staticcheck simplifications (QF*, S1017/S1019/S1023/S1039).

Config: exclude ST1003 (remaining offenders are exported API renames, e.g.
web.Id, which would break compatibility) and skip errcheck for examples/ and
internal/harness/ (demo code where fire-and-forget is intentional).

Build and test compilation verified.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL

* lint: WIP cleanup checkpoint (errcheck config + partial fixes)

Checkpoint of an in-progress golangci-lint cleanup (background pass). Builds
cleanly; lint is not yet zero. Follow-up commit will complete the cleanup and
switch CI to a blocking full-tree lint.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-06-22 17:21:47 +01:00
..

Registry Cache

Cache is a library that provides a caching layer for the go-micro registry.

If you're looking for caching in your microservices use the selector.

Features

  • Caching: Caches registry lookups with configurable TTL
  • Stale Cache Fallback: Returns stale cached data when registry is unavailable
  • Singleflight Protection: Deduplicates concurrent requests for the same service
  • Adaptive Throttling: Rate limits failed lookups to prevent cache penetration (new in v5)

Interface

// Cache is the registry cache interface
type Cache interface {
	// embed the registry interface
	registry.Registry
	// stop the cache watcher
	Stop()
}

Usage

Basic Usage

import (
	"github.com/micro/go-micro/registry"
	"github.com/micro/go-micro/registry/cache"
)

r := registry.NewRegistry()
cache := cache.New(r)

services, _ := cache.GetService("my.service")

Advanced Configuration

import (
	"time"
	"github.com/micro/go-micro/registry"
	"github.com/micro/go-micro/registry/cache"
)

r := registry.NewRegistry()

// Configure cache with custom options
cache := cache.New(r,
	cache.WithTTL(2*time.Minute),                    // Cache TTL
	cache.WithMinimumRetryInterval(10*time.Second),  // Throttle failed lookups
)

services, _ := cache.GetService("my.service")

Adaptive Throttling

The cache implements rate limiting on ALL cache refresh attempts (not just errors) to prevent overwhelming the registry. This protects against multiple scenarios:

  1. Registry failures: When etcd is down/overloaded
  2. Rolling deployments: When all caches expire simultaneously under high QPS
  3. Cache expiration storms: When many services expire at once

How It Works

  • Rate limiting: Refresh attempts are throttled per-service using MinimumRetryInterval (default 5s)
  • Stale cache preference: If stale cache exists (even if expired), return it instead of calling registry
  • No cache fallback: If no cache exists, return ErrNotFound and rely on gRPC retry
  • Singleflight deduplication: Concurrent requests are still deduplicated
  • Recovery: Throttling is reset on successful registry lookup

Example Scenarios

Scenario 1: Registry Failure with Stale Cache

cache := cache.New(etcdRegistry, cache.WithMinimumRetryInterval(10*time.Second))

// Initial lookup populates cache
services, _ := cache.GetService("api")  // → Calls etcd, caches result

// Cache expires after TTL
time.Sleep(2 * time.Minute)

// Etcd fails, but we have stale cache
services, err := cache.GetService("api")  // → Returns stale cache WITHOUT calling etcd
// err == nil, services contains stale data

Scenario 2: Rolling Deployment Cache Storm

// Scenario: All 1000 upstream pods watch downstream service
// Downstream does rolling deployment - last pod updated
// All 1000 upstream caches expire simultaneously
// High QPS hits the system at this moment

// First request after cache expiration
services, _ := cache.GetService("downstream")  // → Calls etcd, updates lastRefreshAttempt

// Next 999 requests arrive within MinimumRetryInterval
services, _ := cache.GetService("downstream")  // → Returns stale cache, NO etcd call
// Rate limiting prevents 999 stampede requests to etcd

Scenario 3: No Cache Available

// First lookup when etcd is down (no cache exists yet)
_, err := cache.GetService("new-service")  // → Calls etcd, fails, records attempt time
// err != nil

// Immediate retry (< 10s later, still no cache)
_, err = cache.GetService("new-service")  // → Throttled, returns ErrNotFound immediately
// err == ErrNotFound

// After MinimumRetryInterval
time.Sleep(10 * time.Second)
_, err = cache.GetService("new-service")  // → Allowed to retry, calls etcd again

This prevents cache penetration scenarios where thousands of concurrent requests hammer a failing or overloaded registry.