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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

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...