How Much Data Availability is Enough?

I bet that some of you reading the title of this blog post scoffed at it. I mean, in this day age, isn’t round-the-clock availability for every application and user just a basic requirement?

No, it shouldn’t be. Let’s discuss.

Availability is traditionally discussed in terms of the percentage of total time that a service needs to be up. For example, a system with 99% availability will be up and running 99% of the time and down, or unavailable, 1% of the time.

Another term used to define availability is MTBF, or mean time between failure. More accurately, MTBF is a better descriptor of reliability than availability. However, reliability has a definite impact on availability. In general, the more reliable the system the more available it will be.

In this Internet age, the push is on to provide never-ending uptime, 365 days a year, 24 hours a day. At 60 minutes an hour that mean 525,600 minutes of uptime a year. Clearly to achieve 100% availability is a laudable goal, but just as clearly an unreasonable one. Why? Because things break, human error is inevitable, and until everybody and everything is perfect, there will be downtime.

The term five nines is often used to describe highly available systems. Meaning 99.999% uptime, five nines describes what is essentially 100% availability, but with the understanding that some downtime is unavoidable (see the accompanying table).

Table 1. Availability versus Downtime

Availability Approximate downtime per year
In minutes In hours
99.999% 5 minutes .08 hours
99.99% 53 minutes .88 hours
99.95% 262 minutes 4.37 hours
99.9% 526 minutes 8.77 hours
99.8% 1,052 minutes 17.5 hours
99.5% 2,628 minutes 43.8 hours
99% 5,256 minutes 87.6 hours
98% 10,512 minutes 175.2 hours
(or 7.3 days)

Even though 100% availability is not reasonable, some systems are achieving availability approaching five nines. DBAs can take measures to design databases and build systems that are created to achieve high availability. However, just because high availability can be built into a system does not mean that every system should be built with a high-availability design. That is so because a highly available system can cost many times more than a traditional system designed with unavailability built into it. The DBA needs to negotiate with the end users and clearly explain the costs associated with a highly available system.

Whenever high availability is a goal for a new system, database, or application, careful analysis is required to determine how much downtime users can really tolerate, and what the impact of an outage would be. High availability is an alluring requirement, and end users will typically request as much as they think they can get. As a DBA, your job is to investigate the reality of the requirement.

The amount of availability that should be built into the database environment must be based on service level agreements and cost. How much availability does the business require? And just as importantly, how much availability can the business afford to implement?

That is the ultimate question. Although it may be possible to achieve high availability, it may not be cost-effective, given the nature of the application and the budget available to support it. The DBA needs to be proactive in working with the application owner to make sure the cost aspect of availability is fully understood by the application owner.


I'm a data management strategist, researcher, and consultant with over three decades of experience in all facets of database systems development and implementation.
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