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Looking Back at 2018 APM Predictions - Did They Come True? Part 2

Jonah Kowall

I would like to highlight some of the predictions made at the start of 2018, and how those have panned out, or not actually occurred. I will review some of the predictions and trends from APMdigest's 2018 APM Predictions.

Here is Part 2:

Start with Looking Back at 2018 APM Predictions - Did They Come True? Part 1

Microtrends

The use of chatbots and other connected assistants have not yielded any benefits in the IT Operations space in 2018, but there are many emerging startups in this area looking to change that over the coming years. While several companies such as ServiceNow and Microsoft made acquisitions in this market, they haven’t produced anything tangible, especially not in 2018. Time will tell if these are a passing fad or they become a cornerstone of computing.

IoT is still nascent, especially in the APM market. The predictions about its growing importance and adoption of APM for IoT are still generally immature and early stage. There are some incredible stories for those doing this, but it’s still a very small number today. Those predictions around IoT are likely too early.

Similarly, Blockchain doesn’t even go there, way too early considering how few real implementations of Blockchain are implemented in production at this point. Maybe in another five years, we can begin to make some predictions, but it will likely be longer before Blockchain performance management solutions are needed by the market.

Culture and Communication

The biggest barrier to transformation is culture and people. This has been clear from every major CIO survey conducted in the last 10 years of economic growth in this bull market. Our communications and the way we do incident response have evolved significantly. The players in this space are solving an extremely important problem, one which MAY change the culture of an organization. This trend will continue as these technologies become essential to better communication of increasingly distributed workforces.

The codification of the role of the SRE by the excellent second book from Google has helped the industry understand how to apply DevOps in an even more concrete manner. The predictions about SRE were spot on, as SRE has become the gold standard for managing and operating applications. Still early for most organizations, but now on the radar. There were several predictions about SRE for the past year. I would, however, say that the vendors who predicted DevOps and culture change by a tool were sadly far from reality. Tools don’t change cultures, but cultural changes often require tool changes.

Wrapping up a great 2018, I wish everyone a productive and creative 2019 where we can listen, learn, innovate, share, and advance our group of APM vendors and practitioners. There are many problems to solve, and new approaches being invented daily by this amazing community.

Hot Topics

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.

Looking Back at 2018 APM Predictions - Did They Come True? Part 2

Jonah Kowall

I would like to highlight some of the predictions made at the start of 2018, and how those have panned out, or not actually occurred. I will review some of the predictions and trends from APMdigest's 2018 APM Predictions.

Here is Part 2:

Start with Looking Back at 2018 APM Predictions - Did They Come True? Part 1

Microtrends

The use of chatbots and other connected assistants have not yielded any benefits in the IT Operations space in 2018, but there are many emerging startups in this area looking to change that over the coming years. While several companies such as ServiceNow and Microsoft made acquisitions in this market, they haven’t produced anything tangible, especially not in 2018. Time will tell if these are a passing fad or they become a cornerstone of computing.

IoT is still nascent, especially in the APM market. The predictions about its growing importance and adoption of APM for IoT are still generally immature and early stage. There are some incredible stories for those doing this, but it’s still a very small number today. Those predictions around IoT are likely too early.

Similarly, Blockchain doesn’t even go there, way too early considering how few real implementations of Blockchain are implemented in production at this point. Maybe in another five years, we can begin to make some predictions, but it will likely be longer before Blockchain performance management solutions are needed by the market.

Culture and Communication

The biggest barrier to transformation is culture and people. This has been clear from every major CIO survey conducted in the last 10 years of economic growth in this bull market. Our communications and the way we do incident response have evolved significantly. The players in this space are solving an extremely important problem, one which MAY change the culture of an organization. This trend will continue as these technologies become essential to better communication of increasingly distributed workforces.

The codification of the role of the SRE by the excellent second book from Google has helped the industry understand how to apply DevOps in an even more concrete manner. The predictions about SRE were spot on, as SRE has become the gold standard for managing and operating applications. Still early for most organizations, but now on the radar. There were several predictions about SRE for the past year. I would, however, say that the vendors who predicted DevOps and culture change by a tool were sadly far from reality. Tools don’t change cultures, but cultural changes often require tool changes.

Wrapping up a great 2018, I wish everyone a productive and creative 2019 where we can listen, learn, innovate, share, and advance our group of APM vendors and practitioners. There are many problems to solve, and new approaches being invented daily by this amazing community.

Hot Topics

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.