Cloud ERP Uptime and Reliability: What SLAs Actually Mean and What They Don’t Tell You
Every cloud ERP vendor promises uptime. It’s on the website, usually in bold: 99.9% availability. 99.95%. Sometimes 99.99%. The numbers are big, the decimals are precise, and the implication is clear — your system will be there when you need it.
What vendors don’t explain is what those numbers actually mean, what they exclude, what happens when they’re missed, and why the SLA printed on your contract may have very little to do with the reliability you actually experience. Because an SLA isn’t a guarantee of uptime. It’s a legal definition of what counts as downtime, combined with a financial remedy — usually a modest service credit — for when that definition is breached. The gap between what buyers think an SLA promises and what it actually delivers is wide enough to drive an entire day’s worth of missed shipments through.
For distribution companies where every minute of ERP downtime translates directly into orders that don’t ship, customers that don’t get served, and revenue that doesn’t materialize, understanding what SLAs actually mean — and what actually determines reliability — matters more than the number itself.
What the Uptime Number Actually Means
Let’s start with the math, because the math is deceptive.
99.9% uptime sounds nearly perfect. It means the system is available 99.9% of the time, which leaves 0.1% for downtime. Over the course of a year, 0.1% translates to approximately 8.76 hours of allowed downtime. That’s an entire business day — maybe more if the outage lands during peak operations.
99.95% uptime — just five hundredths of a percentage point higher — allows approximately 4.38 hours of annual downtime. 99.99% allows about 52 minutes. The decimals may seem like splitting hairs, but the operational difference between losing nine hours of ERP access per year and losing less than an hour is enormous for a distribution operation.
Now here’s where it gets complicated. That uptime percentage doesn’t necessarily mean what you think it means.
Most SLAs measure availability on a monthly basis, not annually. A vendor might promise 99.9% monthly uptime, which translates to roughly 43 minutes of allowed downtime per month. Miss the target in January but hit it the other eleven months, and the annual availability might be well below 99.9% even though the vendor only breached the SLA once.
More importantly, the SLA only counts downtime that meets the vendor’s definition of an outage. And that definition is where the real story lives.
What Counts as Downtime — and What Doesn’t
Every SLA has an exclusions section, and the exclusions often swallow the promise whole.
Scheduled maintenance windows are almost universally excluded from uptime calculations. If the vendor takes the system offline for four hours on a Saturday night for a platform update, those four hours don’t count against the SLA. Some vendors schedule maintenance weekly. Some do it monthly. Some have “maintenance windows” that are technically scheduled but that occur during hours when your warehouse is still operating. The frequency, duration, and timing of scheduled maintenance can significantly affect your real-world availability without ever triggering an SLA breach.
Degraded performance is usually excluded. If the system is technically accessible but running so slowly that your warehouse associates are standing around waiting for screens to load, most SLAs don’t count that as downtime. The system is “available” — it’s just unusable. For a distribution operation where warehouse productivity depends on sub-second system response times, the distinction between “down” and “so slow it might as well be down” is meaningless. But for SLA purposes, only one of those scenarios counts.
Third-party dependencies are often excluded. If the outage is caused by your internet provider, by a third-party integration, by the cloud infrastructure provider (AWS, Azure, Google Cloud), or by a DNS issue upstream of the vendor’s control, many SLAs exclude it. The system is unavailable to you, but it’s not the vendor’s “fault” as defined by the contract — so no breach, no remedy.
Customer-caused issues are excluded. If someone on your team misconfigures a setting, runs a report that overwhelms system resources, or triggers a problem through their own actions, the resulting downtime doesn’t count against the vendor’s SLA. This is reasonable in principle, but the line between “customer-caused” and “the system should have handled it gracefully” can be blurry, and the interpretation typically favors the vendor.
Force majeure and security events are frequently excluded. A DDoS attack that takes the platform offline? Excluded. A regional cloud infrastructure outage that affects hundreds of services? Excluded. A cyberattack that requires emergency defensive action? Excluded. These are precisely the scenarios most likely to cause extended outages, and they’re precisely the scenarios most SLAs don’t cover.
The uptime number on the vendor’s marketing page represents the best case — the availability you’d experience if the only downtime was unexcluded, unscheduled, vendor-caused outages during the SLA measurement period. Real-world availability, which includes scheduled maintenance, performance degradation, and excluded events, is always lower.
What Happens When the SLA Is Breached
Here’s the part that surprises most buyers: the remedy for an SLA breach is almost never a meaningful financial consequence for the vendor.
The standard remedy is a service credit — a percentage of your monthly subscription fee applied to a future invoice. Typical credits range from 5% to 25% of the monthly fee for varying levels of SLA breach. Some vendors cap total credits at one month’s subscription per year regardless of how many breaches occur.
Let’s put concrete numbers on this. A 30-user deployment at $200 per user per month represents $6,000 in monthly subscription revenue. A 10% service credit for an SLA breach is $600. If that breach represented four hours of downtime during your peak shipping window — orders not processed, trucks not loaded, customers not served — the actual business impact could be tens or hundreds of thousands of dollars in missed shipments, expedited freight to catch up, customer penalties, and relationship damage. The $600 credit doesn’t begin to cover the cost. It’s not designed to. It’s designed to give the SLA contractual teeth without creating material financial risk for the vendor.
Some enterprise contracts negotiate more aggressive remedies — early termination rights, performance bonds, or penalty structures that escalate with repeated breaches. These exist in the enterprise world because the customers have negotiating leverage. Mid-market companies typically accept standard SLA terms because the alternative is walking away from a vendor whose product otherwise meets their needs.
The practical implication is clear: don’t rely on the SLA as a safety net. The financial remedy won’t make you whole. What actually protects your business is the platform’s underlying reliability — the architecture, the infrastructure, the operational practices that prevent outages from happening in the first place, not the contract terms that define what happens when they do.
What Actually Determines Reliability
If the SLA is a legal document and not a reliability guarantee, what actually determines whether your cloud ERP will be there when you need it? The answer lives in architecture, infrastructure, and operational practices — none of which appear in the SLA, all of which matter more than the number printed on it.
Infrastructure Redundancy
Cloud ERP platforms running on hyperscale infrastructure providers — AWS, Azure, Google Cloud — benefit from redundancy that’s impossible to replicate in a single-server, single-location deployment. Data replicates across multiple servers. Services distribute across multiple availability zones within a region. In the best architectures, the platform can survive the complete failure of an entire data center without losing availability because the workload is already distributed across independent infrastructure.
The question for buyers is whether the ERP vendor actually leverages this redundancy or whether they’ve deployed on cloud infrastructure in a minimal configuration that doesn’t take advantage of it. Running on AWS doesn’t automatically mean your application has multi-zone redundancy, automated failover, and distributed data replication. It means the capability is available — whether the vendor has implemented it depends on their architecture and their infrastructure investment.
Ask specifically: is the application deployed across multiple availability zones? If one zone goes down, does the system fail over automatically or does it require manual intervention? How is database replication handled — synchronous or asynchronous, single-region or multi-region? The answers distinguish vendors who’ve invested in genuine resilience from those who’ve simply rented space on a cloud provider.
Application Architecture
The application layer’s design determines how gracefully the system handles failures and how quickly it recovers.
Monolithic architectures — common in cloud-migrated legacy systems — run as a single large process. If any component fails, the entire system can go down. Recovery means restarting the entire application, which takes longer and affects every user and every function simultaneously.
Modern cloud-native architectures distribute functionality across multiple services. If one component encounters a problem — say, the reporting engine — other functions continue operating normally. Users can still process orders, run warehouse operations, and manage purchasing while the reporting issue is resolved. The blast radius of any single failure is contained rather than system-wide.
This architectural resilience doesn’t appear in the SLA. A monolithic application and a distributed application might both promise 99.9% uptime. The difference is that when things go wrong — and they will — the distributed architecture degrades gracefully while the monolithic one falls over completely.
Database Reliability
The database is the most critical component in any ERP system. If the database goes down, everything goes down. How the vendor protects the database determines the system’s floor-level reliability.
The essentials include automated backup at frequent intervals — continuous or near-continuous, not nightly. Point-in-time recovery capability that can restore the database to any moment, not just the last backup. Read replicas that distribute database load and provide failover targets if the primary database fails. And replication across multiple infrastructure zones so that a single hardware failure can’t make the database unavailable.
Ask the vendor: what’s the recovery point objective — how much data could be lost in a worst-case database failure? What’s the recovery time objective — how long would it take to restore service? Has the vendor actually tested their disaster recovery process, and when? The difference between a vendor who has tested their DR plan in the last quarter and one who has a plan document they’ve never executed is the difference between confidence and hope.
Deployment Practices
How the vendor deploys updates to the platform directly affects reliability. Updates are one of the most common causes of unplanned downtime in cloud applications — a code change that introduces a bug, a configuration update that has an unexpected interaction, a database migration that takes longer than expected.
Mature deployment practices mitigate this risk. Blue-green deployments maintain two identical production environments, routing traffic to the new version only after it’s been validated and providing instant rollback to the previous version if problems emerge. Canary deployments route a small percentage of traffic to the new version first, monitoring for errors before expanding to full deployment. Automated testing suites catch regressions before they reach production. And deployment monitoring with automatic rollback triggers provides a safety net that catches problems human observation might miss.
These practices are invisible to customers. You’ll never see a deployment happen on a well-run platform. But the difference between a vendor that deploys with rigorous safety practices and one that pushes changes directly to production and hopes for the best shows up in the frequency of incidents and the speed of recovery when they occur.
Monitoring and Incident Response
Even the best architecture and the most careful deployment practices can’t prevent every incident. What determines the customer impact is how quickly the vendor detects, responds to, and resolves problems.
Comprehensive monitoring means the vendor’s operations team knows about a problem before you do. Automated alerting detects anomalies in performance metrics, error rates, and system behavior. On-call engineering teams respond to alerts within minutes, not hours. Incident response playbooks define clear escalation paths and resolution procedures for common failure modes.
Status pages — transparent, real-time reporting of system health — demonstrate a vendor’s commitment to reliability transparency. A vendor that publishes a status page with historical uptime data, incident reports, and resolution timelines is one that takes reliability seriously and is accountable for their track record. A vendor without a public status page is asking you to take their uptime claims on faith.
Multi-Tenant Reliability: Why It’s Usually Better
Multi-tenant architecture affects reliability in ways that favor the customer, though the intuition often suggests otherwise.
The common concern is that sharing a platform with other customers introduces risk — a noisy neighbor whose workload degrades your performance, or a cascading failure that affects every customer simultaneously. These concerns were valid in the early days of multi-tenant computing. Modern platforms address them comprehensively through resource isolation that prevents individual customer workloads from affecting others, load balancing that distributes traffic intelligently, and capacity management that maintains headroom for traffic spikes.
The reliability advantages of multi-tenancy are less obvious but more significant. The vendor maintains one platform, which means their entire operations team is focused on one environment. Monitoring is comprehensive because there’s only one thing to monitor. Incident response is rapid because the team knows the environment intimately. And the business incentive to maintain reliability is intense — a platform-wide outage affects every customer simultaneously, which means the vendor’s entire revenue base is at risk during any incident. That concentration of risk drives investment in reliability that single-tenant vendors can’t economically justify for individual customer instances.
Single-tenant deployments spread the vendor’s operations attention across hundreds or thousands of individual instances. Monitoring each one with the same depth, responding to incidents on each one with the same urgency, and maintaining each one with the same rigor is operationally more difficult and more expensive. The per-customer investment in reliability is almost always lower in a single-tenant model, even though the customer’s perception of a “dedicated” environment suggests the opposite.
What Distribution Companies Should Actually Evaluate
Forget the SLA number for a moment. Here’s what actually determines whether your cloud ERP will be reliable enough for a distribution operation where downtime means missed shipments and damaged customer relationships.
Ask for historical uptime data — not the SLA promise, but the actual track record. A vendor confident in their reliability will share historical availability metrics. Compare the actual uptime against the SLA target. If they consistently exceed the SLA by a wide margin, the platform is genuinely reliable. If they hover near the SLA threshold, the promise is aspirational rather than conservative.
Ask about the last major incident. When was it? How long did it last? How many customers were affected? What caused it? What did the vendor change to prevent recurrence? A vendor that can discuss incidents openly and describe the improvements they made is one that treats reliability as an engineering discipline rather than a marketing claim. A vendor that claims they’ve never had a significant incident is either very new, very lucky, or very dishonest.
Ask about scheduled maintenance frequency and timing. How often does the vendor take the system offline for maintenance? How long do maintenance windows last? What time zone are they scheduled in — and does that overlap with your operating hours? A vendor that performs maintenance weekly during hours that conflict with your warehouse operations is delivering materially less availability than one that deploys updates with zero-downtime practices.
Ask about performance SLAs, not just availability SLAs. The system being “available” matters less than the system being responsive. Does the SLA include any performance commitments — maximum page load times, transaction processing speeds, or API response times? If not, the vendor has no contractual obligation to deliver a usable experience, only a technically accessible one.
Ask what happens during infrastructure provider outages. When AWS or Azure has a regional incident — which happens several times per year — what happens to the ERP platform? Does it fail over to another region automatically? Does it go down until the infrastructure provider recovers? The answer reveals whether the vendor has invested in multi-region resilience or whether they’re dependent on a single provider region that represents a single point of failure.
Ask about the vendor’s status page and incident communication. How will you learn about outages — proactively from the vendor, or reactively when your team can’t log in? Does the vendor publish a real-time status page? Do they send notifications when incidents are detected, when they’re being worked, and when they’re resolved? Transparency in incident communication is a strong signal of operational maturity.
Planning for Downtime Even When You Don’t Expect It
No platform — cloud, on-premise, or otherwise — delivers 100% uptime. The question isn’t whether you’ll experience downtime. It’s whether you’ve planned for it.
For distribution operations, downtime planning means identifying the critical processes that can’t tolerate any interruption and the processes that can work around a brief outage. Order entry may be able to pause for 30 minutes. Warehouse picking that’s already been directed can continue with paper-based fallback procedures. Shipping can batch-process labels once the system is restored. Customer service needs a way to access recent order status even if the full system is unavailable.
The most resilient distribution operations have lightweight continuity plans that don’t depend on the ERP being available for every function at every moment. These plans aren’t elaborate disaster recovery exercises — they’re simple, practical procedures that keep the most critical operations moving during brief system interruptions.
Your vendor should be a partner in developing these plans, because they understand the platform’s failure modes and recovery characteristics better than anyone. A vendor that helps you plan for the downtime they’re trying to prevent is one that takes your operational continuity seriously.
How Bizowie Approaches Uptime and Reliability
Bizowie treats reliability as an engineering priority, not a marketing number. Our platform runs on redundant cloud infrastructure with automated failover, continuous data replication, and deployment practices designed to deliver updates without downtime or disruption.
As a multi-tenant platform, our entire operations investment is concentrated on one environment — the platform every customer runs on. Monitoring is comprehensive. Incident response is immediate. And the business incentive is aligned: every customer’s experience depends on the same platform, which means reliability isn’t a nice-to-have — it’s existential for our business.
We deploy updates continuously using practices that eliminate the scheduled maintenance windows that other platforms require. Our goal is that you never notice a deployment happening — the platform simply improves in the background while your operation runs uninterrupted.
And we’re transparent about our track record. We don’t hide behind an SLA number and hope you never need to invoke it. We invest in the architecture, the infrastructure, and the operational practices that make the SLA a formality rather than a safety net — because for distribution businesses, uptime isn’t an IT metric. It’s an operational requirement that directly affects your customers, your revenue, and your reputation.
See a platform built for reliability, not just marketed for it. Schedule a demo with Bizowie and ask us the hard questions — about our architecture, our incident history, our deployment practices, and our track record. The answers are what separate platforms you can depend on from platforms you have to hope for.