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Resolve vs clarify questions
Resolve vs clarify questions












resolve vs clarify questions
  1. #Resolve vs clarify questions full#
  2. #Resolve vs clarify questions series#

Because instead of running a product until it fails, most of the time we’re running a product for a defined length of time and measuring how many fail.įor example: Let’s say we’re trying to get MTTF stats on Brand Z’s tablets. We can run the light bulbs until the last one fails and use that information to draw conclusions about the resiliency of our light bulbs.īut what happens when we’re measuring things that don’t fail quite as quickly? Things meant to last years and years? For those cases, though MTTF is often used, it’s not as good of a metric.

resolve vs clarify questions

With an example like light bulbs, MTTF is a metric that makes a lot of sense. You’ll need to look deeper than MTTR to answer those questions, but mean time to recovery can provide a starting point for diagnosing whether there’s a problem with your recovery process that requires you to dig deeper. Are your maintenance teams as effective as they could be? If they’re taking the bulk of the time, what’s tripping them up?

resolve vs clarify questions

Are you able to figure out what the problem is quickly? Are there processes that could be improved? Is there a delay between a failure and an alert? Are alerts taking longer than they should to get to the right person? The problem could be with your alert system. Because there’s more than one thing happening between failure and recovery. However, if you want to diagnose where the problem lies within your process (is it an issue with your alerts system? Is the team taking too long on fixes? Does it take too long for someone to respond to a fix request?), you’ll need more data. This is a high-level metric that helps you identify if you have a problem. Is it as quick as you want it to be? How does it compare to your competitors?

#Resolve vs clarify questions full#

This MTTR is a measure of the speed of your full recovery process. On the other hand, MTTR, MTBF, and MTTF can be a good baseline or benchmark that starts conversations that lead into those deeper, important questions.

#Resolve vs clarify questions series#

Some of the industry’s most commonly tracked metrics are MTBF (mean time before failure), MTTR (mean time to recovery, repair, respond, or resolve), MTTF (mean time to failure), and MTTA (mean time to acknowledge)-a series of metrics designed to help tech teams understand how often incidents occur and how quickly the team bounces back from those incidents.Ī lot of experts argue that these metrics aren’t actually that useful on their own because they don’t ask the messier questions of how incidents are resolved, what works and what doesn’t, and how, when, and why issues escalate or deescalate. Which is why it’s important for companies to quantify and track metrics around uptime, downtime, and how quickly and effectively teams are resolving issues. Glitches and downtime come with real consequences. In today’s always-on world, outages and technical incidents matter more than ever before.














Resolve vs clarify questions