Uptime vs. Availability: Impact on SLAs

Reliability is paramount in the IT world that’s always-on. As a customer, whenever you interact with a piece of software or technology, you assume it to be always up and available. But, if you ask for an SRE, it’s virtually impossible. Incidents occur, outages happen; it’s inevitable. But how you respond to them can make all the difference.

And to respond accurately, you have to understand the key differences between uptime and availability. It significantly affects business operations, costs, and your customers’ satisfaction. In this blog, we will explore uptime vs. availability, how they impact your business, and their relation to SLA, SLO and SLI. 

What is uptime?

Uptime refers to the time period when a system is operational and “up” for your end users. It is often measured by the percentage of time your system is up and running. For example, if your service never faced a downtime in the past 3 months, the uptime is 100% for that specific time period. Here’s how to calculate downtime costs to better assess its impact.

An outage or even a planned downtime will affect your uptime percentage. Here’s a calculator to help you calculate uptime:

Now that you know how to measure uptime, let’s have a look at a real-world example that signifies that it’s tough to keep up with 100% uptime. Take the Crowdstrike outage for an example in July 2024. A faulty device driver update for their Falcon software caused a widespread crash that affected millions of users. Unplanned and yet a company top tier resources couldn’t achieve 100% uptime. It reinforces that, in the real world, there will always be occasional downtime or even planned downtime for unexpected bugs, or other unforeseen issues.

What is availability?

Availability is the measurement of the proportion of time your system is accessible and operational to your users. This factors in both your uptime and scheduled maintenance as it shows your service reliability, and accountability for active operations. Data shows that downtime can cost anywhere from $25,000 to $500,000 every hour, underscoring why organizations closely monitor availability. This analysis helps companies set realistic SLAs and prioritize investments in redundancy and rapid repaid mechanisms. 

Here’s a calculator to help you calculate your SLAs, SLOs, and SLIs accurately:

Now that we know what both these metrics stand for, which metric do you prioritize at your organization? Well, when comparing these two metrics, consider the difference between them as OEE (overall equipment effectiveness) and TEEP (total effective equipment performance). They both are important but calculating them incorrectly can lead to costly outcomes. Let’s dive deeper into understanding them with a metaphor.

The iceberg principle to look beyond the surface of uptime vs. availability

The Iceberg principle is a powerful metaphor that explains why reported uptime can be misleading. While many service providers showcase their impressive metrics often aiming for five-nines (99.999% uptime) in their SLAs (Service Level Agreements), this number represents only the tip of the iceberg.

The visible uptime

Uptime shows that servers, networks, or applications are running and meeting basic health checks. But, IT teams often use terms like "five-nines" to communicate a high level of operational reliability but it only tells a part of the story. Here’s a visual representation of the iceberg that we kept mentioning throughout the blog. Save it.

Hidden availability challenges

Beneath the surface, hidden availability challenges such as incident severity levels, slow response times, and degraded service quality can impact users despite high uptime. These underlying problems can compromise overall operational availability, ultimately affecting customer satisfaction and business continuity.

To tackle these challenges, one has to ensure they have an effective monitoring tool to find incidents before they occur. It doesn’t end here, you also need a powerful incident response software like Zenduty that can help your teams at every step of your incident response lifecycle, empowering them to reduce MTTR and MTTA.

Formula for uptime and availability metrics

When IT teams and SRE professionals set aggressive SLAs and SLOs aiming for high uptime, often targeting five-nines (99.999%), it's necessary to understand the right formulas to measure both uptime and overall availability.

Uptime is typically calculated as a simple ratio of the time a system is operational versus the total time in a given period. The formula is:

Uptime % = (Total operating time/Total time) x 100

For example, if your system is up for 8,760 hours in a non-leap year except for 8.77 hours of downtime, then:

Uptime % = (8760 - 8.77/8760) x 100 ≈ 99.9%

Availability goes a step further by factoring in not only downtime but also the speed at which systems recover from failures. A widely used formula in reliability engineering is:

Availability = MTBF/MTBF+MTTR

MTBF (Mean Time Between Failures) is the average operational period between breakdowns.

MTTR (Mean Time To Repair) is the average time required to restore service after a failure.

For instance, if a system fails once every 720 hours (MTBF) and takes 0.083 hours (5 minutes) to repair (MTTR), then:

Availability = 720/720+0.083 ≈ 99.99%

Uptime vs. Availability

What other key metrics are relevant surrounding uptime and availability?

While uptime vs. availability are core metrics for assessing system reliability, they only tell part of the story, just like the iceberg. For IT teams focused on achieving five‑nines performance, a broader set of performance indicators is essential to capture the full picture of service health. Here are some key metrics to consider other than these:

Mean Time Between Failures (MTBF): This metric quantifies the average operational period between system failures. A higher MTBF indicates a more reliable system, helping IT teams understand the frequency of unplanned outages.

Mean Time to Repair (MTTR): MTTR measures the average time it takes to restore service after a failure. Lower MTTR values mean faster recovery, which is critical for maintaining availability and meeting SLA targets.

Mean Time to Detect (MTTD) and Mean Time to Acknowledge (MTTA): These metrics gauge how quickly issues are identified and responded to by IT teams. Rapid detection and acknowledgment are crucial for minimizing downtime and ensuring a seamless user experience.

Response Time and Latency: Beyond knowing that a system is “up,” measuring response times and latency provides insight into how quickly and efficiently the system is delivering services. High latency can significantly impact perceived availability, even if uptime metrics remain high.

Error Rates: Tracking the frequency of system errors (such as HTTP 500 errors for web applications) helps pinpoint underlying issues that might not cause complete downtime but can degrade user experience and overall availability.

Recovery Time Objectives (RTO) and Recovery Point Objectives (RPO):These are critical for disaster recovery planning. RTO defines the maximum acceptable time to restore a service after an outage, while RPO sets the tolerable data loss window. Both are essential when negotiating SLAs and ensuring continuous operation.

Service Level Agreement (SLA) Compliance: Regularly monitoring adherence to SLA metrics (which often include a blend of uptime, response time, and MTTR) ensures that the service meets contractual obligations and user expectations.

User Experience Metrics: Real User Monitoring (RUM) and synthetic monitoring can provide direct insights into how end users perceive service availability. Metrics like page load times and transaction success rates are invaluable for correlating technical performance with customer satisfaction.

We hope this blog helped you understand the difference between uptime and availability and busted some myths around them. If you’re leading your IT teams, this will give you a bigger picture of what really matters.

Also, Don't settle for mere "up" status when you can transform your incident management into a well-oiled, five‑nines system! 

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Frequently asked questions about uptime vs. availability