System Availability Calculator
Estimate uptime, downtime, redundancy effect, SLA margin, and maintenance impact for home lab services.
| Availability Target | Downtime Per Year | Downtime Per Month | Common SLA Meaning |
|---|---|---|---|
| 99% | 87.60 hours | 7.30 hours | Basic personal service |
| 99.5% | 43.80 hours | 3.65 hours | Good lab service with manual recovery |
| 99.9% | 8.76 hours | 43.8 minutes | Common small business SLA target |
| 99.95% | 4.38 hours | 21.9 minutes | Managed service with tighter response |
| 99.99% | 52.6 minutes | 4.38 minutes | Requires tested redundancy and automation |
| 99.999% | 5.26 minutes | 26.3 seconds | Specialized design with few shared risks |
| Pattern | Formula Used | Best Fit | Hidden Dependency |
|---|---|---|---|
| Serial chain | A1 × A2 × A3 | Single host or single path service | One weak component reduces the whole service |
| Parallel nodes | 1 - (1 - A)n | Load balanced web or app workers | Balancer and shared data must be available |
| Warm standby | Primary plus failover factor | NAS replica, VM failover, secondary WAN | Promotion scripts and manual steps add risk |
| Quorum storage | Majority of nodes online | Ceph, etcd, database raft groups | Network partition can defeat healthy nodes |
| Geo failover | 1 - site-failure2 | Public service with remote backup site | DNS TTL, replication lag, and credentials |
| Profile | Typical Stack | Default Target | Maintenance Style |
|---|---|---|---|
| Single mini server | One host, one LAN, local disk | 99.0% to 99.5% | Manual patches, owner-operated |
| NAS plus app host | Separate storage and compute | 99.5% to 99.9% | Storage windows planned first |
| Two-node HA pair | Clustered hypervisors, shared state | 99.9% | Rolling host maintenance |
| Three-node cluster | Quorum control plane and replicas | 99.9% to 99.95% | Drain one node at a time |
| Geo failover service | Primary site plus remote standby | 99.95%+ | Failover drills before claiming SLA |
| Scenario | Likely Target | Design Cue | Downtime Driver |
|---|---|---|---|
| Media server | 99% to 99.5% | UPS plus quick restore backup | Host updates and storage checks |
| Home Assistant | 99.5% to 99.9% | UPS, Zigbee backup, VM snapshot | Power, SD card, add-on updates |
| Remote access VPN | 99.9% | Dual WAN or hosted backup tunnel | ISP outage and router patches |
| Personal mail | 99.9% to 99.95% | Secondary MX and monitored storage | DNS, spam filtering, disk capacity |
| Public blog | 99.95%+ | CDN, static cache, secondary origin | Origin deploys and database changes |
Availability refers to the total amount of time that your service is up and functioning. Availability isnt a promise, but rather a mathematical numbers that calculates the total amount of each event that could potentially prevent your service from functioning. Each of these events has the potential to reduces the availability of your service; disk failure, power flicker, and software update that hangs your machine are just a few of the many failure that could reduce availability.
Consequently, you must manage your availability budget; the difference between reliable and unreliable services is how much of your availability budget you have left after spending it on planned maintenance and improvements. The calculator provide these mathematical calculations after you provide information about your hardware. You must provide availability percentage for each of the layers of your hardware, the number of nodes behind each service, and information about your storage redundancy.
What Availability Means and How to Count Downtime
Additionally, you must provide the number of hours that you will spend maintain your service. The calculator accounts for both your desired SLA and the risks of your hardware by providing a combined figure. Each of these categories are separate from the others due to the fact that fast front-end servers do not necessarily means fast storage servers.
An alternative to manually entering your specification into the form is to select a preset setup for your hardware. Most people will then adjust the availability budget number according to the specific nature of the services that run on the same hardware. For example, a media server and a mail server may run on the same hardware, but each require different amount of uptime.
A mail server may require a fast response to any incidents, but a media server may have more lenience in how fast it can come back online. The availability calculator allow you to adjust the values for MTTR and the number of nodes that your servers use to calculate how this affects the total number of hours that your servers will be down each year. The architecture of your servers has more impact on availability than the components of your hardware.
For example, if your architecture is set up in a serial fashion, the failure of any one component will take down your entire service. In contrast, if you have a number of redundant nodes for your services, but those redundant nodes all share the same components (such as a load balancer, network switch, and shared UPS), the failure of that shared component will take down all of your node. Additionally, warm standbys require manual intervention to take over control of your servers in the case that something fail, which may not be convenient during the time that you require the warm standby server to go online.
These different formulas accounts for the different architectures of your servers so that you can compare the availability of each without having to manually calculate each one yourself. Some of the biggest portions of your availability budget are allocated to maintenance. For example, if you have three nodes that your service is distributed across, rolling out an update to each node will consume some of your availability budget each year.
This time also applies to any other maintenance of your servers, such as storage maintenance, firmware flashing, and data restores from backups. Each of these items should of have its own line item within your availability budget so that you can determine if a particular task is worth the amount of downtime that it will create. Many of the components of your servers may fail simultaneously.
For example, all of the nodes behind your load balancer may be redundant, but they all rely upon the same components; the same network switch, the same uninteruptible power supply (UPS), and the same DNS record. Should any of those shared components fail, all of your nodes behind the load balancer may fail as well. While the availability calculator will not account for all of the shared dependencies between components of your servers, the calculator will remind you to consider availability of components like the network and power available to your servers, as well.
Many incident will not match the average availability numbers that you enter into the calculator. For example, resolving an incident caused by a bad software update will take many hours, but replacing a failing disk may only take twenty minutes. Consequently, you should track the actual time that it takes to resolve incidents (MTTR); tracking this number will provide the best data for the availability calculator.
As you track actual MTTR, the availability budget that is calculated will better reflect what you experience with your servers. The two tables on the page provide a description of what certain percentages of availability mean in terms of the number of hours that your servers will be down each year. These tables allow you to determine the number of hours that you can afford to lose with your current data center and servers.
Once you know how many hours that you can lose, you can determine whether your current server architecture is sufficient to handle the demands of your users. If your current architecture is not sufficient, you will know that you need to add another layer of redundancy to increase availability. Your goal is not to have perfect availability with your servers, but you do want to ensure that you have enough availability to account for unexpected outage.
