Looking Back at 2017 APM Predictions - Did They Come True? Part 2
January 10, 2018

Jonah Kowall
Kentik

Share this

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.

Start with Looking Back at 2017 APM Predictions - Did They Come True? Part 1, to see which predictions did not come true.

The following predictions were spot on, and outline key shifts in the landscape for 2017:

Confusion around AIOps


GARTNER RENAMED IT, WHICH WAS THE PLAN ALL ALONG

AIOps tools today are not a reality, but hopefully it will happen over time

Any time there is a shift in technologies, where vendors are moving from an older technology concept to a newer one Gartner adapts the market definition. In the case of ITOA, as the core concept was reporting on data, which needed to, and eventually moved towards automated analysis of data via machine learning (ML). At the time of advancements in ML Gartner shifted the definition from ITOA to Algorithmic IT Operations (AIOps). Vendors began adopting and applying these new capabilities, and AIOps was becoming a reality. The next phase is automating these analyses and taking action on the data and insights. Hence Gartner changed it to Artificial Intelligence for IT Operations and expanded the scope significantly. AIOps tools today are not a reality (see reasons above), but hopefully it will happen over time. This shift was always the plan at Gartner, but something which needed to evolve over a couple of years. The adoption of ML has been rapid, but we are a far cry from true AI today, even when vendors claim they may have it. They do not, at least not unless they are IBM, Google, Facebook, or a very small handful of other companies. Most vendors in the IT Operations space are not yet taking advantage of public cloud providers’ AI platforms.

Better predictive analysis and machine learning

This one was spot on, we've seen a speedy adoption of more advanced ML, and better predictive capabilities in most products on the market. Although some vendors have had baselining for over a decade, now all products do some form of baselining in the monitoring space. Much more work is being done to improve capabilities, and it's about time!

APM products increasing scale


BUT STILL LACK MARKET LEADING TIME SERIES FEATURES

In 2017 APM products have begun to scale much more efficiently than in the past (with a couple of exceptions), but there is still a lack of market-leading time-series features in APM products, especially when looking at granular data (second level). There is yet another set of tools used for scalable and well-visualized time series from commercial entities and open source projects. I expect this to change eventually, but for now, we have fragmentation in this area.

APM tools evolve to support serverless


BUT EARLY

This prediction came true in 2017, but defining what "support" of serverless (which I prefer to call FaaS) entails is a nebulous term. Most APM tools support collecting events from the code, which require code changes. Code changes are not ideal for those building or managing FaaS, but that's the current state. FaaS vendors are quite closed in exposing the internals of their systems, and some have provided proprietary methods of tracing them. I predict this opens up in 2-3 years to allow a more automated way of monitoring FaaS.

APM in DevOps Toolchain


AND INCREASING

This one has been true for the last 4+ years in fact, but as toolchains increase in complexity the integration of APM into both CI and CD pipelines continues to mature. In the CI/CD space, more advanced commercial solutions include better integration with APM tools as part of their products. Increased polish is needed, and will continue over the coming years.

Hybrid application management


HAS BEEN TRUE FOR YEARS

Hybrid has been typical for a while now and hence is not a prediction but a historical observation. APM tools running at the application layer have been managing across infrastructure for years, I would guess 8+ years, in fact. Today's applications are increasingly hybrid, meaning they encompass several infrastructures, languages, and frameworks. Due to this diversity, APM is critical in managing highly distributed interconnected applications.

APM + IoT


BUT HAS BEEN HAPPENING FOR YEARS, AND NOW PRODUCTS BEGIN TO EMERGE

The measurement of IoT usage and performance is an accurate prediction, another one which is correct, and became even more real with the launch of several IoT product capabilities within leading APM tools. I began seeing this about three years ago with the connected car and set-top boxes specifically. Since connected cars and set-top boxes have a decent amount of computing resources are instrumented with end-user monitoring (browser/javascript/or other APIs) or the running code on the device are treated as a typical end-user or application component within APM tools. The solution providers of these products who discovered this early were able to offer better and more predictable experiences, via observation. This is the reason specific IoT products were introduced in 2017. Great prediction!

Please provide feedback on my assessment on twitter @jkowall or LinkedIn, and if you enjoyed reading this let me know and I’ll be happy to provide my analysis of the 2018 APMdigest predictions next year!

Jonah Kowall is CTO of Kentik
Share this

The Latest

September 16, 2021

Achieve more with less. How many of you feel that pressure — or, even worse, hear those words — trickle down from leadership? The reality is that overworked and under-resourced IT departments will only lead to chronic errors, missed deadlines and service assurance failures. After all, we're only human. So what are overburdened IT departments to do? Reduce the human factor. In a word: automate ...

September 15, 2021

On average, data innovators release twice as many products and increase employee productivity at double the rate of organizations with less mature data strategies, according to the State of Data Innovation report from Splunk ...

September 14, 2021

While 90% of respondents believe observability is important and strategic to their business — and 94% believe it to be strategic to their role — just 26% noted mature observability practices within their business, according to the 2021 Observability Forecast ...

September 13, 2021

Let's explore a few of the most prominent app success indicators and how app engineers can shift their development strategy to better meet the needs of today's app users ...

September 09, 2021

Business enterprises aiming at digital transformation or IT companies developing new software applications face challenges in developing eye-catching, robust, fast-loading, mobile-friendly, content-rich, and user-friendly software. However, with increased pressure to reduce costs and save time, business enterprises often give a short shrift to performance testing services ...

September 08, 2021

DevOps, SRE and other operations teams use observability solutions with AIOps to ingest and normalize data to get visibility into tech stacks from a centralized system, reduce noise and understand the data's context for quicker mean time to recovery (MTTR). With AI using these processes to produce actionable insights, teams are free to spend more time innovating and providing superior service assurance. Let's explore AI's role in ingestion and normalization, and then dive into correlation and deduplication too ...

September 07, 2021

As we look into the future direction of observability, we are paying attention to the rise of artificial intelligence, machine learning, security, and more. I asked top industry experts — DevOps Institute Ambassadors — to offer their predictions for the future of observability. The following are 10 predictions ...

September 01, 2021

One thing is certain: The hybrid workplace, a term we helped define in early 2020, with its human-centric work design, is the future. However, this new hybrid work flexibility does not come without its costs. According to Microsoft ... weekly meeting times for MS Teams users increased 148%, between February 2020 and February 2021 they saw a 40 billion increase in the number of emails, weekly per person team chats is up 45% (and climbing), and people working on Office Docs increased by 66%. This speaks to the need to further optimize remote interactions to avoid burnout ...

August 31, 2021

Here's how it happens: You're deploying a new technology, thinking everything's going smoothly, when the alerts start coming in. Your rollout has hit a snag. Whole groups of users are complaining about poor performance on their devices. Some can't access applications at all. You've now blown your service-level agreement (SLA). You might have just introduced a new security vulnerability. In the worst case, your big expensive product launch has missed the mark altogether. "How did this happen?" you're asking yourself. "Didn't we test everything before we deployed?" ...

August 30, 2021

The Fastly outage in June 2021 showed how one inconspicuous coding error can cause worldwide chaos. A single Fastly customer making a legitimate configuration change, triggered a hidden bug that sent half of the internet offline, including web giants like Amazon and Reddit. Ultimately, this incident illustrates why organizations must test their software in production ...