The advent of the Holiday Season means it is time for the annual list of Application Performance Management (APM) predictions, the most popular post on APMdigest, viewed by tens of thousands of people in the IT community around the world every year. Industry experts — from analysts and consultants to users and the top vendors — offer thoughtful, insightful, and often controversial predictions on how APM and related technologies will evolve and impact business in 2017.
APMdigest not only covers APM, but also a variety of related technologies, and the predictions list does the same. In addition to APM, the related technologies covered include IT Operations Analytics (ITOA) also called Advanced IT Analytics (AIA), IT Service Management (ITSM), End-User Experience Management (EUEM), Network Performance Management (NPM), as well as infrastructure monitoring and cloud.
The 2017 APM Predictions List is the longest predictions list ever featured on APMdigest. Last year's list featured 30 prediction categories, while this year's list features 50 categories. This extensive list of predictions reflects the vast scope of digital transformation accompanied by revolutionary changes in the IT landscape. A few of the predictions overlap with last year's predictions, but most of the predictions are new ideas or next steps into IT's brave new world.
Although many of the 2017 APM predictions are new and specific, the general technologies covered are very familiar — Analytics and Cloud for example — but explored in new ways.
One of the most popular topics discussed on previous lists, DevOps now has its own complete list of predictions on DEVOPSdigest for the second consecutive year. Most DevOps and development related predictions will be found on the DEVOPSdigest, however, DevOps does make an appearance on this year's APM list as well.
Some of these predictions may come true in the next 12 months, while others may be just as valid but take several years to be realized. Still others may be wishful thinking or unbased fears. But taken collectively, this list of predictions offers an interesting and valuable snapshot of what the APM industry is thinking about, planning, expecting and hoping for next year.
The predictions will be posted in 5 parts over the next 5 days.
A forecast by the top minds in Application Performance Management today, here are the predictions:
1. ADVANCED ANALYTICS TRANSFORMS APM
Digital, customer and user experience will continue to lead the way in helping to unify development, IT operations, ITSM and business stakeholders. But most vendors will continue to market much too narrowly to the opportunity. Look for emerging advanced IT analytics (or what the industry calls ITOA) solutions optimized to assimilate application/infrastructure performance and business outcomes in real-time, and predictively, as emerging manager of managers to transform the APM/DevOps universe.
VP of Research, Enterprise Management Associates (EMA)
Read Dennis Drogseth's blog: Transforming Operations, and IT as a Whole, with the Right Technology Investments
Monitoring is dead. Long live monitoring. In 2017 monitoring will remain critical to the successful delivery of stellar user experiences. But the real value will be from analytics, which harnesses the big data of application and infrastructure metrics and correlates them to business performance. Organizations will get insights never fully attainable before on user experience and its impact on customer loyalty and revenue.
VP of DevOps Solution Marketing and Management, CA Technologies
Read Aruna Ravichandran's blog: 3 DevOps Predictions for 2017
I see that APM is going to play a pivotal role in the ITOA movement while leveraging Advanced IT Analytics (AIA). In order for this to occur, APM and ITOA will need a seamless integration with an AIA solution, whether by vendor acquisitions or open integration that is platform agnostic.
Director of Customer Experience Management at the Auto Club Group and Founder of the APM Strategies Group on LinkedIn.
Read Larry Dragich's blog: End User Experience - Perceptions of Performance
2. ARTIFICIAL INTELLIGENCE: THE NEXT STEP IN ANALYTICS
We've gotten past the hype of the Big Data wave and AI is replacing analytics.
In 2017 we will see companies substantially rethinking the roles of the DevOps and operations teams. They will move away from viewing their main responsibilities as analyzing data and present results to their peers: in 2017, most of these analytic tasks will be taken over by intelligent monitoring software utilizing anomaly detection, big data analysis and artificial intelligence. There are two key drivers for this shift: 1) the ever-increasing complexity and scale of modern software and 2) scaling the teams needed to cover up to four times more of their application landscape is economically unviable to do. This fundamental move to AI-assisted intelligent monitoring systems will elevate monitoring to new stakeholders in the organization; especially executive management. Questions like "Is our application working fine?" or "Are our users happy?" will be answered instantly by voice-based multi-modal interfaces without requiring any human analysis.
VP, Chief Technology Strategist, Dynatrace
I see the future challenge for APM vendors to be around analytics. Solution providers will need to introduce Artificial Intelligence based on machine learning algorithms to help humans cope with the incredible complexity of the technology. With this, they will be able to better predict performance issues and their impact. When issues strike, solutions could execute self-healing remediation actions or if not possible provide automated root-cause analysis stats and the best recommendations to restore IT services within the shortest timeframe.
Senior Director of Product Marketing, IT Alerting and IoT, Everbridge
With the surge in business data, investing in analytics will no longer be a choice; it will become a necessity driven by need to have a competitive edge. With plenty of analytics solutions available in the market, the key factors that enterprises look for will be the ease of use to derive the insights they need. In line with this, analytics solutions that can leverage emerging technologies such as advanced machine learning, and AI capabilities to analyze data across complex data systems for better decision making, will find larger adoption.
Product Analyst, ManageEngine
3. APM CATCHES WAVE OF MACHINE LEARNING
The big prediction is the wave of Machine Learning experiments/products that will be applied to aspects of APM.
2017 will mark the year of Machine Learning. Every major IT vendor is including ML in their various solutions and offering this on their cloud. For Application Performance Management this means a shift towards cloud based, intelligent, solutions that can digest both structured (e.g. traditional graph structured data, end user sessions, transaction traces, etc) as well as unstructured data (e.g. logs, crash dumps, etc). Powered by Machine Learning, the APM solution will be able to intelligently detect anomalies, cluster and correlate (un)structured data and predict outages faster, discover dependencies, topologies and relationships automatically among the hybrid IT estate. No matter how often and quickly it changes and throughout the entire application lifecycle from development into production.
Senior Principal Product Marketing Director, Oracle
Two big trends could affect IT Service Management in 2017: Machine Learning and Big Data Analytics. With the application of machine learning, IT service desks can turn "intelligent" with contextual assistance to end users and enable faster resolution of tickets by technicians. The focus on big data analytics would help IT service desk teams mine large volumes of data in the service desk and glean insights that lead to high impact service delivery.
Product Manager, ManageEngine
4. ALGORITHMIC IT OPS EMERGES
The sheer volume of data generated by applications and infrastructure will only increase, resulting in data overload. For the first time, IT Operations teams will embrace an algorithmic approach – also known as Algorithmic IT Operations, or AIOps – to detect signal from noise to ensure successful service delivery. AIOps platforms will provide IT Operations teams with situational awareness and diagnostic capabilities that were not previously possible using manual, non-algorithmic techniques.
Senior Product Marketing Manager, BigPanda
Read Michael Butt's blog: Preventing Outages During the Holiday Shopping Season
5. AIOPS CONFUSION
We predict rising confusion over Gartner's poorly thought out AIOps (Algorithmic Infrastructure Operations), as people think "AI" stands for "artificial intelligence," and Gartner's guidance on algorithms is out-of-date and overly simplistic.
6. IT GAME CHANGER: INTELLIGENT ALERTING
The APM market will continue to experience growth, however, intelligent routing technologies for alerts will become increasingly important and will commoditize the APM market. Intelligent alerting will be big next year as more and more companies realize that monitoring alone isn't good enough. Knowing that there is a problem is one thing, but telling a person who can address a specific problem is an IT game changer.
Product Marketing Director and DevOps Evangelist, Automic Software
7. USERS DEMAND ROOT CAUSE ANALYSIS
We believe that web complexity will only continue to increase, as companies try harder to deliver strong digital experiences, extending their infrastructure to include third-party services such as CDNs and cloud providers. Organizations will realize there can be a nasty side effect: more potential points of failure and a harder time finding the root cause of issues, with each added second of delay leading to more lost revenues. Organizations will understand that this sea of information, no matter how big, is useless without actionable insights. As a core foundation of their APM efforts, they will demand solutions that can pinpoint root causes with unparalleled speed and accuracy.
Director of Industry Innovation, Catchpoint
We've seen companies running 200 IT ops tools or more. Each of these tools triggers separate feeds into different dashboards, and – in spite of providing effective monitoring for their "slice" of the application stack – has created a new problem of monitoring overload. Customers will start to add a layer of analytics on top of these monitoring tools to "connect the dots" across the entire stack. By analyzing performance data and alerts combined with the relevant application topology, users can recognize the difference between inconsequential anomalies and actual performance problems. What customers are asking for is a root cause analysis, not more alarms.
JF Huard, Ph.D.
Founder and CTO, Perspica
8. DEEP LEARNING API ACCELERATES ITOA CONVERGENCE
Democratization of deep learning APIs will accelerate convergence of IT Operations Analytics by easing the merge of distinct data sources like APM, change management, operations management infrastructure monitoring for delivering even more intelligent insight to IT Operations leaders.
Product Marketing Director, Workload Automation, Automic Software
9. ITOA CHALLENGE: METRICS AVAILABILITY
Enterprises will realize that APM metrics (response time, throughput, errors, etc. per transaction) are the single most important set of metrics in their ITOA strategies. But enterprises and APM vendors will struggle to make these crucial metrics available for the broad set of custom developed and purchased applications and transactions that most enterprise live with. Integration of these most important metrics with metrics that capture the behavior of cloud based infrastructures will prove to be a massive challenge.
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