2020 Application Performance Management Predictions - Part 2
December 12, 2019
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Industry experts offer thoughtful, insightful, and often controversial predictions on how APM and related technologies will evolve and impact business in 2020. Part 2 covers AIOps, AI and Machine Learning (ML).

Start with 2020 Application Performance Management Predictions - Part 1


AIOps will continue to be a core enabling foundation for a growing number of analytic platforms, however its meaning as a brand-defining term will gradually fade behind other types of differentiations. These differentiations include use cases — from performance, to DevOps, to change and capacity management and cloud migration, as just a few examples. Other changes will reflect design point and integration priorities in areas such as APM and ITSM, or more granularly, automation technologies, service modeling and dependency mapping, and data resources overall.
Dennis Drogseth
VP of Research, Enterprise Management Associates (EMA)

The AIOps term will fall out of favor in 2020, as all ops products will include AI in one form or another, thus limiting its role as a meaningful differentiator. Instead, ops technologies will focus on specific, differentiated AI-enabled capabilities that go beyond the simple "machine learning for anomaly detection" basics.
Jason Bloomberg
President, Intellyx


The first major outage based on an "AI decision" will happen in 2020, which will lead to a slowing of interest in this area. It will move back to "decision support" as people become more skeptical and risk-averse. The EU's "understandable AI" initiative will then help and reassure people and re-ignite interest in 2022.
Antony Edwards
COO, Eggplant


In 2019, real users on IT Central Station have noted how AIOps can reduce MTTR and help perform root cause analysis. As this market category is growing, ways to improve its learning curve and increase usability would help promote it further among a wider audience.
Russell Rothstein
Founder and CEO, IT Central Station

The demand for AIOps in the enterprise will continue to rise as AI and machine learning have taken the industry by the jugular. Due to an expansion in the number of workloads — both in public cloud and on-premises — and an increase in application complexity, investment in AIOps will increase and ultimately lead to better business outcomes. Today’s challenges place a premium on differentiated vendor solutions powered by AI/ML and big data analytics techniques that can help modern IT operations evolve from traditional monitoring to observability to actionability.
Ram Chakravarti
CTO, BMC Software

2019 has seen enterprises take the initial steps with AIOPs to generate insights from the large volume of data in near real time — even as their own monitoring implementation matures. Moving forward in 2020 and beyond — AIOps will see greater acceleration in adoption as enterprises mature from anomaly detection to automated triage and remediation. We will also see AIOPs expanding to different workloads and domains. However for all the hype that AIOPs is generating — enterprises need to create an end to end strategy from eliminating noise to automated remediation to deliver real benefits.
Jayanti Murty
CTO, Digitate


Machine learning models that take months to construct may never make it into production. Key challenges such as infrastructure, speed and scales along with continuous model accuracy are hindering successful deployment. MLOps, a practice for collaboration and communication between data scientists and operations professionals to help manage the production machine learning lifecycle, will become an IT imperative in 2020 to simplify the integration of AI workloads with the organization's core infrastructure which will accelerate machine learning deployment and enable enterprises to more readily experience the business benefits of machine learning models.
Karen Krivaa
VP of Marketing, GigaSpaces Technologies


In their next phase, AI and ML will become our allies (not our replacements). The next few years will be about finding the sweet spot where you put human power and human thinking first, then add just the right amount of AI and ML to make things more efficient. Rather than automating operations out of the way, AI and ML can be an ally; something teams can lean on to help cut down on inefficiencies.
Tim Armandpour
SVP of Engineering, PagerDuty


There aren't enough eyes on the planet to dashboard-watch an application into first-rate, enterprise scale performance. The sheer complexity, diversity, volatility, and non-stop innovation that constitute an application's execution and experience defeat the human capacity to keep track of what's going on where and who's using what how — never mind how well. 2020 will see AI move toward center stage in strategies for the comprehension and effective management of applications. AI-directed autonomous action will become the norm.
Valerie O'Connell
Research Director, Enterprise Management Associates (EMA)


AI tools will be increasingly applied to user/customer experience. The criticality of improving customer experience to gain a marketplace advantage is on every CXO's mind and AI will play a growing role here by more comprehensively analyzing customer interactions and data use.
Bhanu Singh
VP Product Development and Cloud Operations, OpsRamp

Read more 2020 AI predictions from Bhanu Singh: How AI Will Evolve for IT in 2020


AI will have a significant impact on the nature of work, systems, and operations. Most organizations have not yet adopted AI in a meaningful way. 2020 will be the year that AI becomes more widely adopted within operations teams in part because the use cases are coming into focus. Companies looking to improve monitoring and observability are eyeing the power of AI to automate and augment the work of software developers. While AI will play an increasingly important role for those managing cloud based systems, it is not a replacement for the real need for developers to up their observability game.
Kelsie Pallanck
Senior Content Director, O'Reilly and co-chair of O'Reilly's Infrastructure & Ops Conference


By 2025, "real time" won't be good enough. The industry will need to move beyond real time to become predictive. Soon, real-time technology won't feel fast enough. We will need to go one step further to actually predict what's coming before it happens — like a meteorologist predicting the weather. Large sets of accurate data can provide context and highlight emerging patterns, revealing degrees of probability. With a little help from AI, prediction is within reach.
Tim Armandpour
SVP of Engineering, PagerDuty


In 2020, the #1 question enterprises will ask of vendors is: "Can your AIOps platform or solution manage my hybrid-cloud environment?" That's because, while 2020 will see further cloud migration, on-prem and/or legacy apps and services will continue to be important. No enterprise wants to end up with fragmented and silo-ed AIOps investments that recreate past problems. Powerful, unified AIOps platforms that can easily handle hybrid cloud environments will rule.
Mohan Kompella
VP Product Marketing, BigPanda

Go to 2020 Application Performance Management Predictions - Part 3, covering more about AIOps.

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