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Availability ≠ Responsiveness

Robin Lyon

How many of us IT professionals have been in a meeting similar to this: The chairs of various departments throughout the company are sitting around a long table and are giving a monthly summary.  IT presents that the applications, network and servers were some amount of 9’s available and may explain an outage. The meeting goes on and then one of the heads explains a failure to meet department goals by stating some application was "slow."


IT is asked about it but unfortunately can only present data upon number of tickets and general up time. The slow comment is then picked up another department and IT is left in the untenable position of defending its metrics and supposedly achieved goals while other departments are blaming IT for lack of productivity. 

The real problem is one of communication of expectations. IT has data that supports availability but the customer is complaining of slowness. Slowness is a subjective term and for IT to resolve the difficulty different metrics and SLAs are needed. Fortunately, there is a perfectly good way to measure slowness – time. When we think of availability we need to understand we are actually speaking of capacity while the users are interested in throughput. 

By measuring transaction time (the amount of time it takes for the user to commit an action and receive the corresponding data from the program they are using) IT can state how fast an application is working in objective terms. SLAs can be established that some percentage of the transactions during a reporting period will be completed within a certain amount of time. This allows business decisions based upon performance and is a salve for the mysterious "slow" comment.

Availability is one of the early metrics IT has used to create a simple number to represent complex systems. 

Robin Lyon is Director of Analytics at AppEnsure.

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Availability ≠ Responsiveness

Robin Lyon

How many of us IT professionals have been in a meeting similar to this: The chairs of various departments throughout the company are sitting around a long table and are giving a monthly summary.  IT presents that the applications, network and servers were some amount of 9’s available and may explain an outage. The meeting goes on and then one of the heads explains a failure to meet department goals by stating some application was "slow."


IT is asked about it but unfortunately can only present data upon number of tickets and general up time. The slow comment is then picked up another department and IT is left in the untenable position of defending its metrics and supposedly achieved goals while other departments are blaming IT for lack of productivity. 

The real problem is one of communication of expectations. IT has data that supports availability but the customer is complaining of slowness. Slowness is a subjective term and for IT to resolve the difficulty different metrics and SLAs are needed. Fortunately, there is a perfectly good way to measure slowness – time. When we think of availability we need to understand we are actually speaking of capacity while the users are interested in throughput. 

By measuring transaction time (the amount of time it takes for the user to commit an action and receive the corresponding data from the program they are using) IT can state how fast an application is working in objective terms. SLAs can be established that some percentage of the transactions during a reporting period will be completed within a certain amount of time. This allows business decisions based upon performance and is a salve for the mysterious "slow" comment.

Availability is one of the early metrics IT has used to create a simple number to represent complex systems. 

Robin Lyon is Director of Analytics at AppEnsure.

Hot Topics

The Latest

Significant improvements in operational resilience, more effective use of automation and faster time to market are driving optimism about IT spending in 2025, with a majority of leaders expecting their budgets to increase year-over-year, according to the 2025 State of Digital Operations Report from PagerDuty ...

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PagerDuty

Are they simply number crunchers confined to back-office support, or are they the strategic influencers shaping the future of your enterprise? The reality is that data analysts are far more the latter. In fact, 94% of analysts agree their role is pivotal to making high-level business decisions, proving that they are becoming indispensable partners in shaping strategy ...

Today's enterprises exist in rapidly growing, complex IT landscapes that can inadvertently create silos and lead to the accumulation of disparate tools. To successfully manage such growth, these organizations must realize the requisite shift in corporate culture and workflow management needed to build trust in new technologies. This is particularly true in cases where enterprises are turning to automation and autonomic IT to offload the burden from IT professionals. This interplay between technology and culture is crucial in guiding teams using AIOps and observability solutions to proactively manage operations and transition toward a machine-driven IT ecosystem ...

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