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Looking Back at 2017 APM Predictions - Did They Come True? Part 1

Jonah Kowall

I enjoy the end of the year. Getting some downtime from the constant phone calls and meetings allows me to reflect and plan for a new year ... Planning for a new year often includes predicting what’s going to happen. However, we don't often enough look back at the prior year’s predictions to see if they actually came to fruition. That is the purpose of this analysis. I have picked out a few key areas in APMdigest's 2017 Application Performance Management Predictions, and analyzed which predictions actually came true.

Many of the 2017 predictions were not particularly predictive, but instead "observations" of what is happening and how it will accelerate or shift. Without better ground rules for what a prediction is, it's hard to say what the list is and is not. I have picked out a few key areas which encompass several of these predictions. I'm not calling out the individual predictions, which often do not align with Application Performance Management (APM) trends, but instead, serve a specific vendor (gotta love Marketing).

Review the 2017 APM Predictions on APMdigest

The first four key areas below are the predictions that didn’t come true. In addition to the the ones I have called out here, there were many predictions which have been failing for years that vendors wish would come true. Unfortunately for them, that didn't happen in 2017. Hopefully, they don't post the same prediction for 2018. :)

The following few 2017 predictions had several predictions which fell into a category:

The convergence of infrastructure metrics and APM metrics

Although many tools combine APM and infrastructure metrics, most enterprises still use separate tools due to organizational silos

Although many tools combine APM and infrastructure metrics, most enterprises still use separate tools due to organizational silos. The enterprises which run significant infrastructure continue to deploy monitoring tools for each team — meaning teams running data centers still buy tools for DCIM, network, servers, storage, and other infrastructure technologies. Those implementing cloud infrastructure often use cloud provider tools or other infrastructure monitoring tools which do a better job in those environments, and better handle time series. APM tools, have for a while had lightweight capabilities for infrastructure monitoring, and often may replace more capable infrastructure monitoring technologies, especially when migrating to managed data centers or public cloud.

Adoption of platforms to tie monitoring data together

While there are many products which attempt to tie together data coming from multiple monitoring tools, the integration posts challenges for most. Although some of these products are gaining adoption, it's not impactful to the market today. We haven't seen a shift in this market in 2017, and I doubt it will change in 2018.

AI replacing manual analysis

My perspective on AI is documented. AI is still not prominent in solutions today, even though people have been predicting it for years. The advances in making RCA faster have been helpful to users, but the manual analysis of data continues to be standard today, and likely will be for the foreseeable future. We didn't see a shift in 2017, but as I talk about below, predictive analysis and machine learning are becoming more prominent.

Data-centric to event-centric


BUT WILL BECOME TRUE AT SOME POINT

This one was ahead of its time and is a trend which has been occurring for several years. Instead of event-based systems replacing data based systems, I believe there will be an augmented platform to handle both request-response systems and data-based systems. There are many business reasons to have both capabilities within software architectures, and monitoring will naturally have to evolve to handle both types of software systems. Today most of the "event-based" monitoring systems are done with log analysis tools, as tracking events over time is often a challenge for most monitoring tools. There are some which have been able to show change over time, but not managing of event-based architectures. This will be a continuing trend driven by event-based programming and push models for notifications commonly found in technologies built on top of technology such as Node.js or other event-based frameworks.

Read Looking Back at 2017 APM Predictions - Did They Come True? Part 2, outlining the 2017 APM Predictions that came true.

Hot Topics

The Latest

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...

In MEAN TIME TO INSIGHT Episode 15, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Do-It-Yourself Network Automation ... 

Zero-day vulnerabilities — security flaws that are exploited before developers even know they exist — pose one of the greatest risks to modern organizations. Recently, such vulnerabilities have been discovered in well-known VPN systems like Ivanti and Fortinet, highlighting just how outdated these legacy technologies have become in defending against fast-evolving cyber threats ... To protect digital assets and remote workers in today's environment, companies need more than patchwork solutions. They need architecture that is secure by design ...

Traditional observability requires users to leap across different platforms or tools for metrics, logs, or traces and related issues manually, which is very time-consuming, so as to reasonably ascertain the root cause. Observability 2.0 fixes this by unifying all telemetry data, logs, metrics, and traces into a single, context-rich pipeline that flows into one smart platform. But this is far from just having a bunch of additional data; this data is actionable, predictive, and tied to revenue realization ...

64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...

Looking Back at 2017 APM Predictions - Did They Come True? Part 1

Jonah Kowall

I enjoy the end of the year. Getting some downtime from the constant phone calls and meetings allows me to reflect and plan for a new year ... Planning for a new year often includes predicting what’s going to happen. However, we don't often enough look back at the prior year’s predictions to see if they actually came to fruition. That is the purpose of this analysis. I have picked out a few key areas in APMdigest's 2017 Application Performance Management Predictions, and analyzed which predictions actually came true.

Many of the 2017 predictions were not particularly predictive, but instead "observations" of what is happening and how it will accelerate or shift. Without better ground rules for what a prediction is, it's hard to say what the list is and is not. I have picked out a few key areas which encompass several of these predictions. I'm not calling out the individual predictions, which often do not align with Application Performance Management (APM) trends, but instead, serve a specific vendor (gotta love Marketing).

Review the 2017 APM Predictions on APMdigest

The first four key areas below are the predictions that didn’t come true. In addition to the the ones I have called out here, there were many predictions which have been failing for years that vendors wish would come true. Unfortunately for them, that didn't happen in 2017. Hopefully, they don't post the same prediction for 2018. :)

The following few 2017 predictions had several predictions which fell into a category:

The convergence of infrastructure metrics and APM metrics

Although many tools combine APM and infrastructure metrics, most enterprises still use separate tools due to organizational silos

Although many tools combine APM and infrastructure metrics, most enterprises still use separate tools due to organizational silos. The enterprises which run significant infrastructure continue to deploy monitoring tools for each team — meaning teams running data centers still buy tools for DCIM, network, servers, storage, and other infrastructure technologies. Those implementing cloud infrastructure often use cloud provider tools or other infrastructure monitoring tools which do a better job in those environments, and better handle time series. APM tools, have for a while had lightweight capabilities for infrastructure monitoring, and often may replace more capable infrastructure monitoring technologies, especially when migrating to managed data centers or public cloud.

Adoption of platforms to tie monitoring data together

While there are many products which attempt to tie together data coming from multiple monitoring tools, the integration posts challenges for most. Although some of these products are gaining adoption, it's not impactful to the market today. We haven't seen a shift in this market in 2017, and I doubt it will change in 2018.

AI replacing manual analysis

My perspective on AI is documented. AI is still not prominent in solutions today, even though people have been predicting it for years. The advances in making RCA faster have been helpful to users, but the manual analysis of data continues to be standard today, and likely will be for the foreseeable future. We didn't see a shift in 2017, but as I talk about below, predictive analysis and machine learning are becoming more prominent.

Data-centric to event-centric


BUT WILL BECOME TRUE AT SOME POINT

This one was ahead of its time and is a trend which has been occurring for several years. Instead of event-based systems replacing data based systems, I believe there will be an augmented platform to handle both request-response systems and data-based systems. There are many business reasons to have both capabilities within software architectures, and monitoring will naturally have to evolve to handle both types of software systems. Today most of the "event-based" monitoring systems are done with log analysis tools, as tracking events over time is often a challenge for most monitoring tools. There are some which have been able to show change over time, but not managing of event-based architectures. This will be a continuing trend driven by event-based programming and push models for notifications commonly found in technologies built on top of technology such as Node.js or other event-based frameworks.

Read Looking Back at 2017 APM Predictions - Did They Come True? Part 2, outlining the 2017 APM Predictions that came true.

Hot Topics

The Latest

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...

In MEAN TIME TO INSIGHT Episode 15, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Do-It-Yourself Network Automation ... 

Zero-day vulnerabilities — security flaws that are exploited before developers even know they exist — pose one of the greatest risks to modern organizations. Recently, such vulnerabilities have been discovered in well-known VPN systems like Ivanti and Fortinet, highlighting just how outdated these legacy technologies have become in defending against fast-evolving cyber threats ... To protect digital assets and remote workers in today's environment, companies need more than patchwork solutions. They need architecture that is secure by design ...

Traditional observability requires users to leap across different platforms or tools for metrics, logs, or traces and related issues manually, which is very time-consuming, so as to reasonably ascertain the root cause. Observability 2.0 fixes this by unifying all telemetry data, logs, metrics, and traces into a single, context-rich pipeline that flows into one smart platform. But this is far from just having a bunch of additional data; this data is actionable, predictive, and tied to revenue realization ...

64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...