Optimizely
January 16, 2026
Trenton Baker
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One of the most frequently asked questions for Solr deployments is if they need disaster recovery.
Short answer: yes. If Apache Solr search supports a production workload, disaster recovery should be mandatory, not optional.
Solr search is treated as a backend service, but in production it powers customer experiences, revenue flows and business-critical workflows. When Solr goes down, the impact is rarely isolated to search alone. Recovery time, data loss and downstream effects become business issues immediately.
Most teams don’t skip disaster recovery intentionally. They assume backups, replicas or “we’ll fix it fast” will be enough. That assumption usually holds until the first real incident. When that happens, recovery timelines and data loss turn from theoretical threats to real gaps that teams never planned for.
This post explains why disaster recovery is required for production Solr, why backups alone fall short and why recovery costs are consistently underestimated. It also clarifies how Managed Search reduces operational burden, but does not remove the need for a defined, tested disaster recovery plan.
Isn’t Solr Resilient by Design?
Yes, Solr is designed to be resilient. Replication, shard placement and failover help keep clusters available during routine failures.
But resilience and disaster recovery solve different problems.
Resilience helps systems stay online during expected faults. Disaster recovery defines what happens when something larger breaks. That includes hyperscaler regional outages, widespread cloud failures, data corruption, ransomware or human error.
When one of these mitigating events occurs, availability mechanisms alone don’t answer the most important questions. A recovery strategy and tested plan does.
Does Search Resilience Equal Disaster Recovery?
Short answer: no. Resilience focuses on keeping systems running during expected failures. Disaster recovery focuses on restoring service after something larger breaks. The difference matters because continuity and restoration protect the business in different ways.
A decade ago, 99% uptime was considered robust for production systems. Today, even 99.9% uptime is unacceptable and slow recovery turns minutes of downtime into real business damage.
Resilience reduces the likelihood of disruption. Disaster recovery limits the impact of disruption and exists to answer questions resilience does not:
- How much data loss is acceptable? This defines how far the business can roll back without breaking trust, reporting or compliance obligations.
- How long can search be unavailable? This determines whether downtime is a minor inconvenience or a revenue-impacting event.
- How quickly can traffic be restored elsewhere? This affects customer experience, support load and the ability to keep operations moving during an incident.
- What does recovery look like under pressure? This tests whether recovery plans work when teams are short on time, information and margin for error.
If these answers are not defined ahead of time, you’ll certainly discover them during your first incident. That discovery process is slow, stressful and expensive. More importantly, it pushes recovery decisions into the middle of an outage, when business risk is already at its highest.
Resilience helps teams avoid problems. Disaster recovery helps the business thrive despite them.
Aren’t Backups Enough for Production Solr?
Backups are necessary but not sufficient. A backup answers one narrow question: “Can we restore data?” Disaster recovery answers broader questions when systems fail: “How fast?” “How much?” “With what impact?”
For large Solr indexes, restores can take hours or longer. Re-indexing may not be feasible at all. During that window, search is unavailable, partially available or inconsistent.
Backups without tested recovery paths create a false sense of safety. They protect data, not business continuity.
What Breaks When Production Solr Goes Down?
The first thing that breaks is the assumption that recovery will be simple. Reality sets in quickly. Once an outage hits, teams face:
- Downtime that exceeds expectations. Recovery takes longer than planned because failover paths, restore times or traffic routing were never tested under real conditions.
- Data loss larger than assumed. Backups are older than expected, restore points are incomplete or recent changes cannot be recovered.
- Manual recovery steps under time pressure. Engineers are forced to make high-risk decisions without automation or clear runbooks.
- Escalation from engineering to leadership. Recovery timelines become executive concerns as customer impact and revenue exposure grow.
- Customer and SLA impact that compounds quickly. Support load increases, contractual obligations come into play and trust erodes with every hour of disruption.
The most costly outages are not caused by atypical failures. They come from common scenarios that were never planned for.
SearchStax delivered a Solr disaster recovery architecture for LME that was a key element to drive the search implementation on our the website.
Why Are Recovery Costs Higher Than Expected?
Because most planning focuses on uptime, not on restoring them after something breaks. Uptime planning assumes failures are short, localized and easy to recover from. Recovery planning deals with the opposite. Systems are unavailable, data may be inconsistent and teams must rebuild functionality and trust under pressure. That gap is where costs appear.
When recovery is not planned ahead of time, teams absorb costs in places they rarely model:
- Engineering time burns quickly. Senior engineers abandon planned work to troubleshoot unfamiliar failures and stitch recovery together by hand. Unplanned downtime can exceed $300,000 per hour according to the ITIC Downtime Survey and without a defined recovery path, that cost escalates even faster.
- Delayed releases and blocked teams. Search often sits upstream of other systems. When Solr is unavailable, dependent teams stall, releases slip and backlogs grow even after service returns.
- Customer support escalations. As outages persist, support volume rises. Tickets escalate quickly and recovery timelines become leadership issues.
- Contractual or compliance exposure. Missed SLAs, reporting gaps or unavailable data can trigger penalties or audits that extend beyond the incident itself.
- Long-term trust erosion after visible incidents. Customers may tolerate downtime. They remember poor recovery. Confidence drops when communication is uncertain or timelines change.
These costs multiply when recovery is improvised. Decisions are slower, riskier and harder to reverse once made under pressure.
Defining RPO (Recovery Point Objective) and RTO (Recovery Time Objective) ahead of time forces teams to quantify recovery expectations before an incident turns those expectations into liabilities.
How Does Ransomware Affect Disaster Recovery Plans?
In cloud environments, ransomware turns disaster recovery into a requirement, not a precaution.
Modern attacks encrypt, delete, or corrupt data, which makes redundancy alone insufficient. Clean recovery points and tested restore paths matter more than availability.
A disaster recovery plan defines how systems are restored without guessing, negotiating or rebuilding from scratch. It applies to search infrastructure the same way it applies to databases and core applications. Disaster recovery is not a ransomware solution by itself, but without it, every other security control has a hard stop.
Managed Search reduces operational exposure by handling Solr infrastructure, upgrades and day-to-day management. Enabling disaster recovery adds a defined way to restore search after an incident. It does not prevent attacks; it determines whether recovery is possible under pressure.
That distinction matters. Ransomware resilience depends on how quickly systems can be restored to a known good state when prevention fails.
Does Managed Search Remove the Need for Disaster Recovery?
No, Managed Search improves operational agility. It does not define recovery behavior.
Managed Search removes much of the administration burden of running Solr in production. Provisioning, scaling, upgrades, monitoring and infrastructure reliability are handled for you. That lowers day-to-day risk and reduces the chance of routine failures.
Disaster recovery solves a different problem.
Managed Search makes disaster recovery easier to adopt and operate, but teams still need to make deliberate decisions about recovery, including:
- Whether disaster recovery is required for the workload. This depends on how critical search is to customers, revenue or internal operations. If search supports production workflows, recovery expectations already exist, even if they are not documented.
- What recovery objectives are acceptable. RPO and RTO define how much data loss and downtime the business can tolerate. These are business decisions, not infrastructure defaults.
- How recovery should be tested. A recovery plan that has never been exercised is unproven. Testing is what turns recovery from an assumption into a capability.
Managed Search reduces operational effort. Disaster recovery defines what happens when that effort is not enough.
What Does Solr Disaster Recovery Require?
Good disaster recovery is defined before it is needed and proven before it is trusted.
In practice, that means setting recovery expectations ahead of time and knowing they can be met when Solr is unavailable, data is inconsistent or traffic must shift elsewhere. Recovery is not about adding configuration, it’s about predictable outcomes under pressure.
At a minimum, Solr disaster recovery requires:
- Clear recovery objectives. Define acceptable data loss and downtime in advance. RPO and RTO reflect business tolerance, not guesses made during an outage.
- Recovery paths that match real workloads. Recovery behavior aligns with how search is actually used in production.
- Regular testing. Plans are exercised so teams know what works, what breaks and how long recovery really takes.
- Durable documentation. Recovery does not depend on tribal knowledge or specific individuals being available.
- Shared expectations. Engineering actions and leadership expectations are aligned before an incident occurs.
Good disaster recovery does not require re-architecting applications or building custom tooling. It requires clarity, ownership and validation.
What Does Solr Disaster Recovery Require?
Start with assessment, not assumptions. The simplest path to disaster recovery is understanding current exposure, defining acceptable recovery outcomes and matching recovery options to real production workloads. Most teams already have pieces in place. What’s missing is a defined, tested recovery plan that turns those pieces into a predictable outcome.
If your Solr supports a production workload, disaster recovery should not be a future project.
We’re hosting a 30-minute session that shows:
- Why disaster recovery should be mandatory for production Solr
- How RPO and RTO translate into real business impact
- What actually breaks during real incidents
- How to enable disaster recovery without re-architecting
Primary next step: Register for the webinar
Secondary option: Request a free DR assessment
Running production Solr without disaster recovery isn’t a shortcut.
— It’s deferred risk.
