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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.

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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

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 ...

In March, New Relic published the State of Observability for Media and Entertainment Report to share insights, data, and analysis into the adoption and business value of observability across the media and entertainment industry. Here are six key takeaways from the report ...

Regardless of their scale, business decisions often take time, effort, and a lot of back-and-forth discussion to reach any sort of actionable conclusion ... Any means of streamlining this process and getting from complex problems to optimal solutions more efficiently and reliably is key. How can organizations optimize their decision-making to save time and reduce excess effort from those involved? ...

As enterprises accelerate their cloud adoption strategies, CIOs are routinely exceeding their cloud budgets — a concern that's about to face additional pressure from an unexpected direction: uncertainty over semiconductor tariffs. The CIO Cloud Trends Survey & Report from Azul reveals the extent continued cloud investment despite cost overruns, and how organizations are attempting to bring spending under control ...

Image
Azul

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ...