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3 Takeaways from Velocity New York 2014 - and What This Means for APM

Laura Strassman

While exhibiting with the SmartBear AlertSite UXM team in Velocity last week, I managed to skip away from the booth quite a bit to squeeze in as many sessions as possible. The more sessions I attended, the more some common themes started materializing. The three themes that finally emerged are all very different, but are ultimately all related at the end of the day.


Here they are, my 3 big takeaways from Velocity NY 2014:

1. We live in a complex world of our own making

2. Failure is the nature of complex systems technological or organizational

3. Organizational change is necessary to effect solutions and sustain them

The theme of complexity appeared in several sessions ranging from fixing healthcare.com, to a very academic talk about complex systems, to stories about corporate deployments. There were a few layers to complexity. The first layer was about how as teams concerned with performance we were by our very nature, pushing systems to the edge and introducing complexity. The second layer revolved around how deployments are just so big that organizational complexity is introduced - who manages what? If the pieces are all managed separately, complexity is increased, organizationally.

Which leads directly to a discussion of failure. If we are pushing the edge, and delivering increasingly complex systems, then failures will happen. The nature of the discussion has to change from preventing all failure, to failing gracefully. What do we do when there is a failure? How have we planned, in advance, to handle a failure?

Efficiently handling failure involves a collaborative approach. I know you thought I was going to say that deploying great applications involves a collaborative approach, and it does but I think it’s more crucial for failures. At all the conferences I have been to this year, organization change has been a huge topic. It seems to have two parts to it:

1. Hero/Unicorn culture needs to be replaced by a team culture for the health of the organization and the health of the individual.

2. Performance, by its nature, requires a cross functional approach to be successful.

There seems to be a prominent backlash against the culture of the special individual that takes on heroic efforts and saves the day. I think this is partly due to a maturing of the industry but also there is an inherent conflict between this and the need to work cross functionally to solve problems in complex environments. Several sessions went in depth on this theme.

As I passed the first half dozen APM vendors or so when returning back to the exhibition hall with these themes fresh in my mind, the thought occurred to me that if any of these solutions planned to earn or keep the business of any of these other attendees leaving the same sessions I am, they had better be able to do the following:

1. Make it easier for teams to get their work done. If not help reduce complexity, then at very least you better provide efficient methods to help cope with complexity.

2. Help resolve the inevitable failures quickly.

3. Enhance collaboration, not impede it.

I suspect that APM vendors that fail to deliver on these items might not be exhibiting at Velocity Conferences for too long …


Laura Strassman is Sr. Product Marketing Manager at SmartBear Software.

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3 Takeaways from Velocity New York 2014 - and What This Means for APM

Laura Strassman

While exhibiting with the SmartBear AlertSite UXM team in Velocity last week, I managed to skip away from the booth quite a bit to squeeze in as many sessions as possible. The more sessions I attended, the more some common themes started materializing. The three themes that finally emerged are all very different, but are ultimately all related at the end of the day.


Here they are, my 3 big takeaways from Velocity NY 2014:

1. We live in a complex world of our own making

2. Failure is the nature of complex systems technological or organizational

3. Organizational change is necessary to effect solutions and sustain them

The theme of complexity appeared in several sessions ranging from fixing healthcare.com, to a very academic talk about complex systems, to stories about corporate deployments. There were a few layers to complexity. The first layer was about how as teams concerned with performance we were by our very nature, pushing systems to the edge and introducing complexity. The second layer revolved around how deployments are just so big that organizational complexity is introduced - who manages what? If the pieces are all managed separately, complexity is increased, organizationally.

Which leads directly to a discussion of failure. If we are pushing the edge, and delivering increasingly complex systems, then failures will happen. The nature of the discussion has to change from preventing all failure, to failing gracefully. What do we do when there is a failure? How have we planned, in advance, to handle a failure?

Efficiently handling failure involves a collaborative approach. I know you thought I was going to say that deploying great applications involves a collaborative approach, and it does but I think it’s more crucial for failures. At all the conferences I have been to this year, organization change has been a huge topic. It seems to have two parts to it:

1. Hero/Unicorn culture needs to be replaced by a team culture for the health of the organization and the health of the individual.

2. Performance, by its nature, requires a cross functional approach to be successful.

There seems to be a prominent backlash against the culture of the special individual that takes on heroic efforts and saves the day. I think this is partly due to a maturing of the industry but also there is an inherent conflict between this and the need to work cross functionally to solve problems in complex environments. Several sessions went in depth on this theme.

As I passed the first half dozen APM vendors or so when returning back to the exhibition hall with these themes fresh in my mind, the thought occurred to me that if any of these solutions planned to earn or keep the business of any of these other attendees leaving the same sessions I am, they had better be able to do the following:

1. Make it easier for teams to get their work done. If not help reduce complexity, then at very least you better provide efficient methods to help cope with complexity.

2. Help resolve the inevitable failures quickly.

3. Enhance collaboration, not impede it.

I suspect that APM vendors that fail to deliver on these items might not be exhibiting at Velocity Conferences for too long …


Laura Strassman is Sr. Product Marketing Manager at SmartBear Software.

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 ...