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Redis Caching & Messaging (Pub/Sub, Streams) · 강의

리더 선출 패턴

고가용성을 위해 분산 서비스에서 Redis를 리더 선출에 활용하는 방법을 살펴봅니다.

리더 선출 패턴은(는) CoddyKit의 무료 Redis Caching & Messaging (Pub/Sub, Streams) 강의입니다. 이것은 4개 중 2번째 강의입니다. 아래에서 전체 강의를 무료로 읽을 수 있으며, 내장 코드 에디터와 24/7 AI 튜터와 함께 브라우저에서 직접 실습할 수 있습니다. 이 강의는 Redis Caching & Messaging (Pub/Sub, Streams) 학습 경로의 일부이며, 진행 상황이 웹과 CoddyKit 앱에 동기화됩니다. Redis Caching & Messaging (Pub/Sub, Streams) 강의에는 총 4개의 강의가 포함되어 있습니다.

이 강의의 일부는 아직 번역되지 않았으며 영어로 표시됩니다.

Why Leader Election?

In a distributed system, multiple instances of your application run simultaneously. Sometimes, you need one instance to perform a specific task, like processing a queue or coordinating updates, to avoid conflicts or duplicate work.

This is where leader election comes in. It's a process where distributed nodes agree on a single node to be the "leader" at any given time.

Redis for Election Coordination

Redis is an excellent choice for implementing leader election due to its speed, atomic operations, and strong consistency guarantees for single-key operations.

  • Atomic Operations: Commands like SETNX or SET ... NX EX execute entirely or not at all, preventing race conditions.
  • Persistence: If configured, Redis can persist data, making leader election state more durable.
  • Centralized State: Provides a single, agreed-upon source of truth for who the current leader is.

Basic Election: SETNX

The simplest way to attempt leader election with Redis is using the SETNX command. SETNX key value ("Set if Not eXists") sets a key only if it doesn't already exist. If the key is set, it returns 1; otherwise, 0.

The first process to successfully set the leader key becomes the leader.

import redis
import time

# Connect to Redis
r = redis.Redis(decode_responses=True)

LEADER_KEY = "my_app:leader_v1"
MY_ID = "process_A" # Unique ID for this process

print(f"Process {MY_ID} attempting to become leader...")

# Try to acquire leadership
if r.setnx(LEADER_KEY, MY_ID):
    print(f"Process {MY_ID} is now the leader!")
    # Simulate leader work
    time.sleep(3) # Work for 3 seconds
    # In a real scenario, the leader would perform tasks
    # and eventually release leadership or renew its lease.
    r.delete(LEADER_KEY) # Release leadership
    print(f"Process {MY_ID} released leadership.")
el:
    current_leader = r.get(LEADER_KEY)
    print(f"Process {MY_ID}: Another process ({current_leader}) is already the leader.")

The Problem: Leader Failure

Consider the basic SETNX approach. What if the elected leader (process_A from the last example) crashes immediately after setting the LEADER_KEY, but before it has a chance to delete it?

The LEADER_KEY would remain in Redis indefinitely, preventing any other process from becoming leader. This creates a permanent deadlock, breaking your distributed system's high availability.

TTL for Fault Tolerance

To prevent deadlocks, we must add an expiration time (Time-To-Live, or TTL) to the leader key. This ensures that even if a leader crashes, its leadership key will eventually expire, allowing a new election.

We can use the EXPIRE key seconds command right after SETNX to set a TTL.

import redis
import time

r = redis.Redis(decode_responses=True)

LEADER_KEY = "my_app:leader_v2"
MY_ID = "process_B"
LOCK_TTL = 10 # seconds

print(f"Process {MY_ID} attempting to become leader...")

if r.setnx(LEADER_KEY, MY_ID):
    r.expire(LEADER_KEY, LOCK_TTL) # Set expiration
    print(f"Process {MY_ID} is now the leader with TTL {LOCK_TTL}s!")
    # Simulate leader work for a short period
    time.sleep(LOCK_TTL // 2)
    print(f"Process {MY_ID} completed its short task.")
    if r.get(LEADER_KEY) == MY_ID: # Check if still leader before deleting
        r.delete(LEADER_KEY)
        print(f"Process {MY_ID} released leadership.")
    else:
        print(f"Process {MY_ID}: Leadership lost or expired already.")
el:
    current_leader = r.get(LEADER_KEY)
    print(f"Process {MY_ID}: Another process ({current_leader}) is already the leader.")

The SETNX + EXPIRE Race

While adding EXPIRE is better, a critical race condition still exists! Imagine this sequence:

  1. Process A calls SETNX LEADER_KEY process_A. It succeeds (returns 1).
  2. Process A then crashes before it can call EXPIRE LEADER_KEY 10.

The LEADER_KEY is set, but without a TTL, leading to the same deadlock situation as before. We need an atomic way to set the key and its expiration.

Atomic SET for Robustness

Redis provides a powerful, atomic SET command that combines setting a key's value and its expiration. The format is SET key value [EX seconds | PX milliseconds] [NX | XX].

  • NX: Only set the key if it does not already exist (like SETNX).
  • EX seconds: Set an expiration time in seconds.
  • PX milliseconds: Set an expiration time in milliseconds.

Using SET LEADER_KEY MY_ID NX EX 10 ensures that both conditions (key not existing AND expiration) are applied atomically.

import redis
import time

r = redis.Redis(decode_responses=True)

LEADER_KEY = "my_app:leader_v3"
MY_ID = "process_C"
LOCK_TTL = 10 # seconds

print(f"Process {MY_ID} attempting to become leader atomically...")

# Try to acquire leadership using atomic SET with NX and EX
# This command returns True if the key was set, False otherwise.
if r.set(LEADER_KEY, MY_ID, nx=True, ex=LOCK_TTL):
    print(f"Process {MY_ID} is now the leader with atomic TTL {LOCK_TTL}s!")
    # Simulate leader work
    time.sleep(LOCK_TTL // 2)
    print(f"Process {MY_ID} still working as leader.")
    if r.get(LEADER_KEY) == MY_ID: # Important: check value before deleting!
        r.delete(LEADER_KEY)
        print(f"Process {MY_ID} gracefully released leadership.")
    else:
        print(f"Process {MY_ID}: Leadership lost or expired already.")
el:
    current_leader = r.get(LEADER_KEY)
    print(f"Process {MY_ID}: Another process ({current_leader}) is already the leader.")

Maintaining Leadership: Heartbeats

Once a leader is elected using the atomic SET command, it needs to periodically signal that it's still alive and capable of leading. This is done through "heartbeats."

A heartbeat involves the leader refreshing the expiration time of its leadership key before it expires (e.g., using EXPIRE LEADER_KEY NEW_TTL or PEXPIRE). If the leader fails to send heartbeats, its key will expire, triggering a new election among the remaining processes.

Check Your Understanding

Which of the following are benefits of using the atomic SET key value NX EX seconds command for leader election compared to separate SETNX and EXPIRE commands?

Recap: Leader Election

We've explored how Redis can facilitate leader election in distributed systems. We started with basic SETNX, identified its pitfalls, and learned to improve it with EXPIRE.

Crucially, we discovered the robust and atomic SET key value NX EX seconds command to prevent race conditions and ensure keys always have an expiration. Finally, we touched upon the importance of leader heartbeats to maintain active leadership.

자주 묻는 질문

“리더 선출 패턴” 강의는 무료인가요?

네 — “리더 선출 패턴” 전체 내용을 이 웹사이트에서 무료로 읽을 수 있습니다. 인터랙티브하게 실습하려면(내장 코드 에디터와 24/7 AI 튜터), CoddyKit PRO로 업그레이드하면 Redis Caching & Messaging (Pub/Sub, Streams) 강의 전체를 잠금 해제할 수 있습니다. Redis Caching & Messaging (Pub/Sub, Streams) 강의에는 총 4개의 강의가 포함되어 있습니다.

“리더 선출 패턴”에서 뭘 배우나요?

고가용성을 위해 분산 서비스에서 Redis를 리더 선출에 활용하는 방법을 살펴봅니다. 브라우저에서 직접 실행하는 실습 코드로 Redis Caching & Messaging (Pub/Sub, Streams)을(를) 배우며, 24/7 AI 튜터가 강의를 진행하면서 질문에 답변해줍니다.

Redis Caching & Messaging (Pub/Sub, Streams)을(를) 시작하는 데 경험이 필요한가요?

사전 경험은 필요하지 않습니다. CoddyKit의 Redis Caching & Messaging (Pub/Sub, Streams)은(는) 초급자부터 고급 학습자까지를 위해 구성되어 있으므로, 여기서 시작하거나 처음부터 시작할 수 있으며 자신의 속도대로 진행할 수 있습니다. 이것은 4개 중 2번째 강의입니다.

“리더 선출 패턴” 강의는 얼마나 걸리나요?

대부분의 CoddyKit 강의는 약 5~10분이 소요됩니다. 각 강의는 간결하고 인터랙티브하여 꾸준한 진행이 가능하며, 웹과 앱에서 중단한 부분부터 바로 시작할 수 있습니다.

이 Redis Caching & Messaging (Pub/Sub, Streams) 강의에서 코드를 작성하고 실행할 수 있나요?

네. 모든 Redis Caching & Messaging (Pub/Sub, Streams) 강의에는 내장 코드 에디터가 포함되어 있으므로, 브라우저에서 바로 실제 코드를 작성하고 실행한 후 즉시 AI 피드백을 받을 수 있습니다 — 로컬 설정이 필요 없습니다.

이 강의의 모든 강의

  1. Redis를 사용한 분산 잠금
  2. 리더 선출 패턴
  3. 조정 서비스로서의 Redis
  4. 분산 속도 제한
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