{"id":1010,"date":"2025-09-02T08:40:20","date_gmt":"2025-09-02T08:40:20","guid":{"rendered":"https:\/\/sreschool.com\/blog\/?p=1010"},"modified":"2025-09-02T08:40:21","modified_gmt":"2025-09-02T08:40:21","slug":"what-is-redundancy","status":"publish","type":"post","link":"https:\/\/sreschool.com\/blog\/what-is-redundancy\/","title":{"rendered":"What is Redundancy?"},"content":{"rendered":"\n

<\/h1>\n\n\n\n
\"\"<\/figure>\n\n\n\n

Redundancy<\/strong> is the deliberate duplication of critical components or paths so that a failure doesn\u2019t violate your SLOs<\/strong>. Put simply: remove single points of failure (SPOFs) and make sure something else can take over fast enough that users don\u2019t notice.<\/p>\n\n\n\n

Where you add redundancy (failure domains)<\/h2>\n\n\n\n
    \n
  • Process \/ pod:<\/strong> multiple workers for the same service.<\/li>\n\n\n\n
  • Host \/ node:<\/strong> more than one VM\/node per service tier.<\/li>\n\n\n\n
  • Availability Zone (AZ):<\/strong> replicas spread across \u22652 AZs.<\/li>\n\n\n\n
  • Region:<\/strong> active-active or active-passive between regions.<\/li>\n\n\n\n
  • Vendor:<\/strong> multi-provider or alternate managed service (only when justified).<\/li>\n<\/ul>\n\n\n\n

    Common patterns<\/h2>\n\n\n\n
      \n
    • N+1 \/ N+M:<\/strong> have at least one (or M) spare capacity unit beyond steady-state needs.<\/li>\n\n\n\n
    • 2N (\u201cmirrored\u201d):<\/strong> two full-capacity stacks; either can serve 100%.<\/li>\n\n\n\n
    • Active-active:<\/strong> all sites handle traffic; failover is mostly automatic and fast.<\/li>\n\n\n\n
    • Active-passive:<\/strong> a hot\/warm standby takes over on failure (some failover time).<\/li>\n\n\n\n
    • Quorum-based replication:<\/strong> e.g., 3 or 5 nodes (Raft\/Paxos) so a majority can proceed.<\/li>\n\n\n\n
    • Erasure coding \/ parity:<\/strong> data survives disk\/node loss without full duplication.<\/li>\n<\/ul>\n\n\n\n

      How redundancy improves reliability<\/h2>\n\n\n\n

      If one replica has availability A<\/em>, two independent replicas behind a good load balancer have availability \u2248 1 \u2013 (1\u2013A)\u00b2<\/strong> (and so on), assuming independent<\/strong> failures. Correlation kills this benefit\u2014so separate replicas across failure domains (different AZs\/regions, power, network, versions).<\/p>\n\n\n\n

      Design principles<\/h2>\n\n\n\n
        \n
      1. Eliminate SPOFs:<\/strong> control planes, queues, caches, secrets stores, DNS, load balancers, and CI\/CD paths all need redundancy or fast recovery.<\/li>\n\n\n\n
      2. Isolate failure domains:<\/strong> spread replicas across AZs; don\u2019t co-locate primaries and standbys.<\/li>\n\n\n\n
      3. Diversity beats duplication:<\/strong> different versions, hardware, or providers reduce correlated risk.<\/li>\n\n\n\n
      4. Automate failover:<\/strong> health checks, timeouts, circuit breakers, and quick DNS\/LB re-routing.<\/li>\n\n\n\n
      5. Right-size capacity:<\/strong> spare headroom for failover (e.g., N+1) and pre-scale if needed.<\/li>\n<\/ol>\n\n\n\n

        Trade-offs & pitfalls<\/h2>\n\n\n\n
          \n
        • Cost vs reliability:<\/strong> more replicas, more money. Tie decisions to SLO\/error-budget math.<\/li>\n\n\n\n
        • Complexity:<\/strong> multi-region state is hard (consistency, latency, split-brain).<\/li>\n\n\n\n
        • Hidden coupling:<\/strong> two \u201credundant\u201d services sharing one database = still a SPOF.<\/li>\n\n\n\n
        • False redundancy:<\/strong> two pods on one node or one AZ adds little resilience.<\/li>\n<\/ul>\n\n\n\n

          What to monitor to prove redundancy works<\/h2>\n\n\n\n
            \n
          • Per-AZ\/region health<\/strong> and synthetic checks (not just aggregate).<\/li>\n\n\n\n
          • Failover time<\/strong> (MTTR) and success rate of automated promotions.<\/li>\n\n\n\n
          • Quorum \/ ISR health<\/strong> (for Kafka\/etcd\/Consul), replication lag, and RPO\/RTO.<\/li>\n\n\n\n
          • Capacity headroom<\/strong> after a node\/AZ loss (can you still meet SLO?).<\/li>\n<\/ul>\n\n\n\n

            Test it (don\u2019t just hope)<\/h2>\n\n\n\n
              \n
            • Game days \/ chaos experiments:<\/strong> kill a node, drain an AZ, sever a NAT gateway, block a dependency; verify traffic stays healthy and alerts are actionable.<\/li>\n\n\n\n
            • Runbooks & drills:<\/strong> promote replicas, restore from backups, and rehearse DNS\/LB failover.<\/li>\n<\/ul>\n\n\n\n

              Concrete examples (EKS\/AWS flavored)<\/h2>\n\n\n\n
                \n
              • Stateless services:<\/strong> replicas: 3+<\/code>, PodDisruptionBudget<\/strong>, Pod Topology Spread<\/strong> across 3 AZs, HPA<\/strong> with spare headroom; ALB\/NLB across subnets in all AZs.<\/li>\n\n\n\n
              • Stateful stores:<\/strong>\n
                  \n
                • RDS\/Aurora Multi-AZ<\/strong>, cross-region replica for DR; test failovers.<\/li>\n\n\n\n
                • Kafka<\/strong> (or MSK\/Confluent): replication factor \u22653, min.insync.replicas=2<\/code>, rack-aware across AZs.<\/li>\n\n\n\n
                • Redis\/ElastiCache:<\/strong> cluster mode enabled with multi-AZ, automatic failover.<\/li>\n<\/ul>\n<\/li>\n\n\n\n
                • Storage & DNS:<\/strong> S3 with versioning + (if needed) cross-region replication; Route 53 health-check + failover\/latency records.<\/li>\n\n\n\n
                • Control plane dependencies:<\/strong> multiple NAT gateways (per AZ), duplicate VPC endpoints for critical services, redundant CI runners, dual logging\/metrics paths when feasible.<\/li>\n<\/ul>\n\n\n\n

                  Quick checklist<\/h2>\n\n\n\n
                    \n
                  • Do we meet capacity with one node\/AZ down<\/strong>?<\/li>\n\n\n\n
                  • Are replicas spread across AZs<\/strong> and enforced by policy?<\/li>\n\n\n\n
                  • Is failover automatic<\/strong>, observed<\/strong>, and rehearsed<\/strong>?<\/li>\n\n\n\n
                  • Are dependencies<\/strong> (DB, cache, queue, DNS, secrets) redundant too?<\/li>\n\n\n\n
                  • Do monitors alert on loss of redundancy<\/strong> (e.g., quorum at risk), not just total outage?<\/li>\n<\/ul>\n\n\n\n

                    4 Pillors of High Availability<\/h2>\n\n\n\n
                    \"\"<\/figure>\n","protected":false},"excerpt":{"rendered":"

                    Redundancy is the deliberate duplication of critical components or paths so that a failure doesn\u2019t violate your SLOs. 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