What are MTTx Metrics Good For? Let’s Find Out.

  • What are common MTTx metrics and why are they used?
  • What are some problems with relying on MTTx metrics?
  • How can I make MTTx metrics more helpful?
  • How do I move away from shallow metrics?
  • How better metrics help build a blameless culture

Common types of MTTx metrics

Table of common types of MTTx Metrics such as mean time to detect, how this metric is measured, and common usage.

What are some problems with relying on MTTx metrics?

How can I make MTTx metrics more helpful?

  • The severity of the incident
  • How the incident was discovered (internally or via customer report)
  • The service area disrupted
  • The resources used in responding to the incident (such as runbooks, backups)
  • Other monitoring data about the system when the incident occurred (such as server load)
  • If the MTTA for customer-reported incidents is much higher than for internally detected incidents, can you create a faster pipeline for processing customer reports? Or, is there a way your monitoring could detect the issue so customer reports are less frequent?
  • If using a certain runbook leads to lower MTTR metrics, what about that runbook could be adopted into other runbooks?
  • If one area of service has very high MTTD, what monitoring tools could you implement to catch incidents faster?

Moving away from shallow metrics

Focusing on customer impact with SLOs

Examining outliers instead of focusing on averages

Look at the story of real work behind your incidents

How better metrics help build a blameless culture

  • Employees are hesitant to raise issues that might improve the system if it will negatively affect the metric
  • When the metric reaches an undesirable level, employees may blame others to avoid being blamed
  • Employees will hesitate to take risks or innovate if they fear it could negatively impact the metric
  • Employees may even misreport data to artificially inflate the metric, especially if jobs, promotions, or bonuses depend on it

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