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What a redundancy plan is—and what it is not
A redundancy plan keeps a service available when infrastructure, software, connectivity, or an entire operating location fails. It combines duplicated components or environments with replication, traffic routing, monitoring, failover procedures, and tested recovery. The plan is successful only when it meets explicit business objectives; having two servers does not, by itself, create high availability.
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- Recovery time objective (RTO): the maximum acceptable time between an outage and restored service.
- Recovery point objective (RPO): the maximum acceptable amount of data loss, expressed as the time between the latest recoverable state and the failure.
- Service-level objective (SLO): the availability or performance target the service is expected to achieve over a defined period.
Google Cloud describes RTO and RPO as measurable objectives. Smaller values generally require more infrastructure, automation, operational work, and testing. AWS presents redundancy as a trade-off between downtime and data loss on one side and cost and complexity on the other. Treat those objectives as constraints to satisfy, not as marketing percentages to copy from another workload.
Start with business impact, not infrastructure
Classify what an outage would damage
List each workload and describe the consequences of an interruption or incorrect data. Consider lost transactions or advertising, safety implications, contractual or regulatory obligations, customer trust, and the time of day or season when demand peaks. A public game-service status page, for example, may be less critical than the account or payment service behind it; a leaderboard can often tolerate delayed updates while authentication cannot. Keep these decisions at the workload level instead of assigning one availability target to an entire company.
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Translate consequences into RTO and RPO
Ask the owner two questions: “How long can users be unable to use this function?” and “How much successfully committed work can we recreate manually or from another source?” Record answers in minutes or hours for RTO and in time intervals for RPO. An RPO of zero implies that every accepted write must survive the failure; an RPO measured in minutes permits a corresponding amount of replay or re-entry. Do not promise a target that has not been demonstrated by a recovery exercise.
Set the SLO and its measurement window
Define what counts as available: successful login, a completed match-making request, an API response within a latency limit, or another user-visible test. Specify the observation window and the exclusions allowed by your service agreement. An SLO should be measurable by the same monitoring used during failover, otherwise an apparently successful recovery can hide a degraded service.
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AWS Well-Architected names three broad strategies: backup and restore, standby (active/passive), and active/active. The table shows the practical differences; the achievable values depend on your implementation and test results.
| Pattern | How production is served | RTO and RPO characteristics | Failure scope | Capacity and operations | Main trade-off |
|---|---|---|---|---|---|
| Backup and restore | One environment serves traffic. Recovery starts by restoring data and rebuilding or starting services. | Slowest recovery of the three. RPO is determined by backup frequency, durability, and the last successful restore. | Can recover from component, zone, or regional loss if backups and a restore location are available. | Lowest steady-state infrastructure and staffing burden, but restore automation and runbooks are essential. | Lower cost and simpler normal operation in exchange for longer interruption and potentially more data loss. |
| Active-passive standby | A primary serves users while a standby receives replication or is partially provisioned. | RTO is governed by detection, promotion, traffic switching, and standby startup or scale-up. RPO depends on replication lag or the latest durable backup. | Handles failures covered by the standby’s location and replication design, including a zone or region when provisioned there. | Costs less than running two fully active deployments, but the standby must be maintained, patched, monitored, and sized for recovery demand. | A compromise between cost and interruption; a cold or undersized standby cannot meet a fast RTO. |
| Active-active | Multiple complete deployments serve production simultaneously, with traffic distributed across them. | Can provide very low interruption and low RPO when writes and routing are designed for it, but failover is not automatic merely because two sites are live. | Can continue through a component, zone, or regional failure if traffic and data remain available elsewhere. | Requires duplicate production capacity, sophisticated routing and observability, disciplined releases, and procedures for data consistency and write conflicts. | Best fit for mission-critical workloads, with the highest infrastructure cost and operational complexity. |
Choose the pattern from your targets
Use backup and restore when recovery can be deliberate
Select this pattern when the business can tolerate a longer outage and the accepted data-loss window matches your backup schedule. Design for a complete rebuild: application artifacts, configuration, secrets, identity dependencies, network rules, and data must all be recoverable. A backup that exists but has never been restored is an assumption, not a recovery capability.
Use active-passive when you need a ready escape route
Active-passive is appropriate when downtime must be shortened but duplicate live capacity is not justified. Decide whether the standby is hot, warm, or cold in practical terms: how much software is running, how current the data is, and how quickly it can accept peak traffic. Microsoft notes that active-passive RTO is measured by failover time. Include health detection, promotion, connection handling, cache or queue treatment, and a documented return to the original primary.
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Use active-active for interruption-intolerant services
Active-active is suitable when a failure must have little or no visible interruption and the organization can operate multiple production environments. Every live site needs current software, capacity headroom, security controls, telemetry, and a release process that does not create incompatible versions. The design must also define where a write is accepted, how concurrent writes are ordered, and what happens when sites disagree. Microsoft describes active-active as ideal for mission-critical workloads while warning of its higher cost and complexity.
Match redundancy to the fault domain
Availability zones or equivalent local domains
Separate replicas across zones or comparable fault domains to handle a localized power, cooling, network, or hardware failure. A second instance in the same domain does not protect against that domain’s outage. Zone-level redundancy is often the first expansion beyond a single site because it improves resilience without requiring cross-region data movement.
Multiple regions
Add regions only when the threat model includes a regional outage, regulatory isolation requirement, or a geographic failure that zones cannot contain. AWS distinguishes multi-zone mitigation from multi-Region protection; Microsoft similarly ties region and zone choices to workload criticality and SLOs. Cross-region designs introduce replication lag, data-residency and transfer constraints, independent networking and identity dependencies, and a need to plan failback. A regional pair is not complete until you can route users to the surviving region and later return them without overwriting newer data.
Make the scope explicit
For each workload, document the failure it is meant to survive: process, host, component, zone, region, or operator error. Do not claim regional availability from a zone-only design, and do not count a backup in the same account or location as protection from a destructive event that could reach both copies.
Replication and backup solve different problems
Replication copies current state to another environment so traffic can continue quickly. Microsoft describes it as support for day-to-day resiliency and a common part of a high-availability strategy. Replication can deliver low RTO and RPO, but it also copies corruption, accidental deletion, ransomware-encrypted data, and bad application writes.
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Backups provide a separate, recoverable history from which you can restore a known-good point. Keep them independent of the production failure path, protect their access controls, and retain enough versions to cover delayed discovery of corruption. Test restoring the application and its data together; a database dump without the matching schema, keys, configuration, or application version may be unusable.
Account for capacity, consistency, and automation
Size for recovery demand, not average demand
A standby that can handle only normal traffic may fail when users retry after an outage. Size the promoted environment for the expected recovery peak, or document a controlled degradation such as disabled nonessential features. In active-active, determine how much traffic each surviving site must absorb after one site is removed. Include queues, caches, databases, authentication, observability, and network egress in the capacity calculation.
Define the data model before choosing topology
Single-writer replication can simplify ordering, while multi-writer active-active requires conflict detection and resolution. Identify authoritative records, idempotent operations, duplicate-request handling, clock or ordering assumptions, and the user-visible result of a conflict. If a service cannot safely merge concurrent writes, route writes to one authority and use the redundant site for reads or as a promoted successor.
Automate the repeatable path and gate the dangerous path
Automate health checks, traffic withdrawal, promotion, configuration changes, and notifications where mistakes are predictable. Require an explicit approval or safety gate before irreversible actions such as promoting a stale copy or deleting the former primary. Every automated action needs logs, alerts, an owner, and a rollback or failback procedure.
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- Inventory workloads and dependencies. Record owners, data stores, external services, identity systems, queues, certificates, and network paths. A service is only as available as its least-redundant critical dependency.
- Write the business consequence. State what revenue, safety, compliance obligation, or customer experience is affected at each outage duration and data-loss interval.
- Set RTO, RPO, and SLO targets. Use measurable user-visible conditions and include the observation window and recovery boundary.
- Map targets to a pattern. Start with backup and restore. Move to active-passive when its tested failover time is required. Choose active-active only when the interruption target and workload criticality justify its extra capacity and consistency work.
- Choose the fault-domain scope. Select zones for localized failures and regions for regional threats. Verify data-residency, latency, and transfer constraints before committing.
- Design replication and backups together. Set replication behavior and lag alarms, define backup frequency and retention, isolate backup access, and document a clean restore point.
- Size and instrument recovery capacity. Test peak-load behavior after losing one domain. Monitor replication lag, backup success, restore duration, health-check accuracy, routing convergence, and error rates.
- Document ownership and execute exercises. Publish contact roles, decision authority, commands or UI paths, communication templates, failover, failback, and restore steps. Run controlled exercises, record measured RTO and RPO, and revise the objectives or architecture when results miss the target.
What the runbook must contain
- Detection: the signals that distinguish a real failure from a bad deployment or monitoring outage.
- Traffic control: health-check behavior, routing changes, connection draining, DNS or load-balancer actions, and expected propagation time.
- Data decisions: which replica is authoritative, how to handle in-flight writes, and when to stop replication to prevent corruption from spreading.
- Promotion: the exact sequence for starting services, applying configuration, validating dependencies, and opening traffic gradually.
- Communication: incident roles, escalation thresholds, customer messaging, and a record of decisions.
- Failback: how to resynchronize the former primary, validate it, shift traffic back safely, and preserve writes created during the outage.
- Security and compliance: equivalent access controls, encryption, secrets, audit logs, and regional handling in every standby or active site.
Test the claims before relying on them
Perform two separate exercises. A failover exercise measures whether the service can continue in the selected surviving domain. A restore exercise measures whether independent backups can rebuild a usable service after corruption or destructive loss. Record elapsed time, data recovered, manual actions, failed assumptions, and user-visible errors.
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Test partial failures as well as total loss: a slow database, broken health check, expired certificate, partitioned network, stale replica, and failed deployment can trigger unsafe automation without taking down an entire region. Re-run after architecture, schema, routing, identity, or release-process changes. Treat the observed RTO and RPO as the current capability; update the target or invest in the design when the exercise misses it.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Common selection mistakes
Choosing active-active because it sounds safest
Two live sites do not remove the need for conflict handling, capacity planning, independent dependencies, or tested routing. If the workload has no credible multi-writer design or the team cannot operate both sites, active-passive with a well-tested promotion path may be safer.
Calling replication a backup
A replica can faithfully preserve a mistake. Keep independent backups and prove that a historical restore works.
Ignoring failback
Failover is only half the incident. Without a resynchronization and traffic-return plan, the temporary site can become a fragile permanent primary or cause data loss during the switch back.
Under-sizing the standby
Recovery traffic often includes retries and delayed demand. Validate peak behavior after removing one site, not only idle readiness.
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Using a generic uptime target
Provider examples and industry percentages are not universal recommendations. Set an SLO from the workload’s consequences and measure it with your own user-visible checks.
Worked decision examples
Noncritical content or analytics
If a delay of hours is acceptable and historical data can be reconstructed, backup and restore may meet the business need. Spend effort on reliable backups, a documented rebuild, and a restore exercise rather than duplicating the entire service.
Account or transaction service
If users must regain access quickly and losing only a small interval of writes is acceptable, active-passive with current replication and a tested promotion sequence can be appropriate. Keep independent backups for corruption and deletion.
Real-time multiplayer coordination
If a regional outage would immediately disrupt active sessions and customer trust, consider active-active across regions. First solve authoritative state, conflict behavior, session routing, and surviving-region capacity; otherwise the duplicate deployment may increase failure modes instead of reducing them.
Bottom line
Choose redundancy by working backward from business impact: define RTO, RPO, and SLO; identify the failure domain you must survive; and select backup/restore, active-passive, or active-active only after its tested behavior meets those objectives. Use replication for continuity, independent backups for corruption and catastrophic loss, and controlled failover and restore exercises to replace assumptions with measured capability.
Quick Recap
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