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APM is More Than a Software Product

Oliver Cole

I have been in the performance engineering business for about 30 years. I get involved early on during system development and move off as the systems move to maintenance. Then, I move onto the next one.

I sometimes get called in to troubleshoot a performance crisis. I have sometimes been compared to a locust moving onto the next greenfield and, at other times, compared to Kwai Chang Caine (of Kung Fu fame), wandering the earth sowing justice, peace and performance.

Whichever you choose, I have noticed some similarities between the various projects that I have worked on.

1. Speed to Meet the Need

There are two aspects to performance engineering:

- To speed up the system to meet the required response times

- To talk the customer into lowering their response time requirements

It continually amazes me how high level system people will start off with unnecessarily fast response requirements. One customer wanted sub-second browser response time, even though the user would stare at the resulting web page for many minutes. Really, it was ok if it took a couple of seconds to fetch the web page.

So don't feel afraid to talk your customers into a lower performance criteria.

2. Keep Track of Your History

Performance requirements are always patchy. Yes, they get the big ones (user response time), but it is totally typical for the subcomponents to not have requirements on them, making it unclear where and how to make the end user response times. Complicating this, generally, all of the discussions leading to the system designs are lost. There was a big debate as to how large the system should be for how many users. Someone chose that 256 CPU server monster, but what was their thinking? Half way through the project, when the response requirements have been relaxed and the number of users has been increased, it sure would be nice to look though those emails and see what people were thinking so you can estimate what system changes need to be made to accommodate the business changes.

So during the early phases, have an archive account to which people can cc "important" emails. Later, these can be reviewed and all that wonderful history and knowledge will make the system change and maintenance a lot easier.

3. Dev vs. Ops

The development people do not really address the maintenance phase of the project. The development people are in a heated rush to meet performance goals and deadlines while not over running costs. The project managers are very focused on the deadline of "going live".

Then the system goes live, everyone throws a party and then they realize that they have not planned well for this lesser period of effort: maintenance. What artifacts did the developers leave the maintainers? Did they leave a workable load test? Did they leave a well organized set of production diagnostics implemented as part of the application? Did they leave proper alert monitoring? Did they leave proper daily reporting?

Ideally, the last stage of development is to set up the system for long term, cost effective maintenance, not the first stage of maintenance. This task is properly done when the development team is still available, not after the brightest are gone to their next adventure. As much as possible the maintenance tasks (such as daily reports, regression tests and load tests) should be automated and that may require changes to the system, changes that the development team can do easily, but will be much more difficult for the whittled down maintenance team.

4. An APM Solution Itself is not the Solution

Management often feels that buying a tool will solve a problem. "We have performance problems so we will buy an APM solution." This belief often results in shelfware: management has underestimated the effort to implement the solution.

Yes, an APM solution is good. But you need to have enough labor to implement it and look at and understand the results. Plan on it up front. Don't focus on the capital cost to your organization, focus on how it will integrate into your organization and what will be done on an ongoing basis.

5. How Important is Performance?

How important is your project? Everyone feels that their project is important, but some are more so than others. Some systems really are not that performance intensive. So, you can save money by not worrying so much about performance; a high performing system is more expensive to monitor and maintain than one that requires less performance.

Make the decision early on as to how important performance is. If it is important, make sure that it is considered important by everyone. If it is not so important, embrace that too and make clear goals for performance. Even if performance is not important, clearly indicate the goals. Even easy to reach goals should be articulated.

I have seen systems where the performance goal is to wait for users to complain, then address it. Sometimes that works fine.

Oliver Cole is President of OC Systems.

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APM is More Than a Software Product

Oliver Cole

I have been in the performance engineering business for about 30 years. I get involved early on during system development and move off as the systems move to maintenance. Then, I move onto the next one.

I sometimes get called in to troubleshoot a performance crisis. I have sometimes been compared to a locust moving onto the next greenfield and, at other times, compared to Kwai Chang Caine (of Kung Fu fame), wandering the earth sowing justice, peace and performance.

Whichever you choose, I have noticed some similarities between the various projects that I have worked on.

1. Speed to Meet the Need

There are two aspects to performance engineering:

- To speed up the system to meet the required response times

- To talk the customer into lowering their response time requirements

It continually amazes me how high level system people will start off with unnecessarily fast response requirements. One customer wanted sub-second browser response time, even though the user would stare at the resulting web page for many minutes. Really, it was ok if it took a couple of seconds to fetch the web page.

So don't feel afraid to talk your customers into a lower performance criteria.

2. Keep Track of Your History

Performance requirements are always patchy. Yes, they get the big ones (user response time), but it is totally typical for the subcomponents to not have requirements on them, making it unclear where and how to make the end user response times. Complicating this, generally, all of the discussions leading to the system designs are lost. There was a big debate as to how large the system should be for how many users. Someone chose that 256 CPU server monster, but what was their thinking? Half way through the project, when the response requirements have been relaxed and the number of users has been increased, it sure would be nice to look though those emails and see what people were thinking so you can estimate what system changes need to be made to accommodate the business changes.

So during the early phases, have an archive account to which people can cc "important" emails. Later, these can be reviewed and all that wonderful history and knowledge will make the system change and maintenance a lot easier.

3. Dev vs. Ops

The development people do not really address the maintenance phase of the project. The development people are in a heated rush to meet performance goals and deadlines while not over running costs. The project managers are very focused on the deadline of "going live".

Then the system goes live, everyone throws a party and then they realize that they have not planned well for this lesser period of effort: maintenance. What artifacts did the developers leave the maintainers? Did they leave a workable load test? Did they leave a well organized set of production diagnostics implemented as part of the application? Did they leave proper alert monitoring? Did they leave proper daily reporting?

Ideally, the last stage of development is to set up the system for long term, cost effective maintenance, not the first stage of maintenance. This task is properly done when the development team is still available, not after the brightest are gone to their next adventure. As much as possible the maintenance tasks (such as daily reports, regression tests and load tests) should be automated and that may require changes to the system, changes that the development team can do easily, but will be much more difficult for the whittled down maintenance team.

4. An APM Solution Itself is not the Solution

Management often feels that buying a tool will solve a problem. "We have performance problems so we will buy an APM solution." This belief often results in shelfware: management has underestimated the effort to implement the solution.

Yes, an APM solution is good. But you need to have enough labor to implement it and look at and understand the results. Plan on it up front. Don't focus on the capital cost to your organization, focus on how it will integrate into your organization and what will be done on an ongoing basis.

5. How Important is Performance?

How important is your project? Everyone feels that their project is important, but some are more so than others. Some systems really are not that performance intensive. So, you can save money by not worrying so much about performance; a high performing system is more expensive to monitor and maintain than one that requires less performance.

Make the decision early on as to how important performance is. If it is important, make sure that it is considered important by everyone. If it is not so important, embrace that too and make clear goals for performance. Even if performance is not important, clearly indicate the goals. Even easy to reach goals should be articulated.

I have seen systems where the performance goal is to wait for users to complain, then address it. Sometimes that works fine.

Oliver Cole is President of OC Systems.

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...