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.
The Latest
Developers need a tool that can be portable and vendor agnostic, given the advent of microservices. It may be clear an issue is occurring; what may not be clear is if it's part of a distributed system or the app itself. Enter OpenTelemetry, commonly referred to as OTel, an open-source framework that provides a standardized way of collecting and exporting telemetry data (logs, metrics, and traces) from cloud-native software ...
As SLOs grow in popularity their usage is becoming more mature. For example, 82% of respondents intend to increase their use of SLOs, and 96% have mapped SLOs directly to their business operations or already have a plan to, according to The State of Service Level Objectives 2023 from Nobl9 ...
Observability has matured beyond its early adopter position and is now foundational for modern enterprises to achieve full visibility into today's complex technology environments, according to The State of Observability 2023, a report released by Splunk in collaboration with Enterprise Strategy Group ...
Before network engineers even begin the automation process, they tend to start with preconceived notions that oftentimes, if acted upon, can hinder the process. To prevent that from happening, it's important to identify and dispel a few common misconceptions currently out there and how networking teams can overcome them. So, let's address the three most common network automation myths ...
Many IT organizations apply AI/ML and AIOps technology across domains, correlating insights from the various layers of IT infrastructure and operations. However, Enterprise Management Associates (EMA) has observed significant interest in applying these AI technologies narrowly to network management, according to a new research report, titled AI-Driven Networks: Leveling Up Network Management with AI/ML and AIOps ...
When it comes to system outages, AIOps solutions with the right foundation can help reduce the blame game so the right teams can spend valuable time restoring the impacted services rather than improving their MTTI score (mean time to innocence). In fact, much of today's innovation around ChatGPT-style algorithms can be used to significantly improve the triage process and user experience ...
Gartner identified the top 10 data and analytics (D&A) trends for 2023 that can guide D&A leaders to create new sources of value by anticipating change and transforming extreme uncertainty into new business opportunities ...
The only way for companies to stay competitive is to modernize applications, yet there's no denying that bringing apps into the modern era can be challenging ... Let's look at a few ways to modernize applications and consider what new obstacles and opportunities 2023 presents ...
As online penetration grows, retailers' profits are shrinking — with the cost of serving customers anytime, anywhere, at any speed not bringing in enough topline growth to best monetize even existing investments in technology, systems, infrastructure, and people, let alone new investments, according to Digital-First Retail: Turning Profit Destruction into Customer and Shareholder Value, a new report from AlixPartners and World Retail Congress ...