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The Modern NOC
IT OpsPredictionsfor 2018
Introduction
If Your Role Is: See These 2018 Predictions
The pace of IT automation in the last decade has been staggering. The data center has transformed. Workloads have migrated to the cloud. Applications have been re-architected to microservices. Both applications and infrastructure have become increasingly fragmented, distributed and dynamic. When IT operations becomes a bottleneck, the whole organization suffers.
It’s clear that to keep pace with continued digital transformation of the enterprise, IT Operations will continue to be rocked by paradigm shifts in 2018.
Automation has helped enterprise IT to modernize, and yet somehow the role of Service Operations has been left behind. When services go down, every minute means lost revenue. Front-line “level one” operators and engineers continue to be overwhelmed by the flood of event data generated by IT monitoring tools – especially alert data – causing stress and frustration. Whether called a NOC or DevOps or SREs, the teams responsible for delivering quality of service should heed the trends predicted in this ebook.
IT Executive
NOC Management
Tools Architect
NOC Operator/ Engineer
1 2 3 5 7 8
2 4 5 6
2 3 8
431 7 8 9
No matter your specific function in IT Operations, BigPanda is pleased to bring you these 2018 predictions.
1
2018 Implication for Your IT Operations team:
Forward-thinking digital businesses will continue to sunset their legacy vendor solutions in favor of newer, cloud-based alternatives.
DevOps Organizations reporting that by 2021,
All New Services will be Deployed in the Cloud 80%
80%
The Modern NOC - Predictions for 2018 | 1
2016 2018
On premises
2020 2022 2024
0%
20%
40%
60%
80%
Going for Flexibility: Enterprise Computing Workloads are Departing to the Cloud
Off premises Cloud providers
Legacy Maintenance Costs as part of Software
Total Cost of Ownership
The death knell is finally sounding for the legacy Event Correlation & Analysis
(ECA) market, long controlled by aging solutions from players such as IBM, HP,
BMC and CA. Cloud adoption and DevOps are finally killing the traditional
solutions stack. Infrastructure-as-code is supplanting the physical datacenter.
Mission critical environments with high workloads are moving to the cloud. The
centralized NOC is evolving to a more distributed model with complex incident
escalation workflows. Meanwhile the legacy ECA vendors are not investing in
any new features or innovation. Many enterprises feel stuck paying
“maintenance taxes” to these providers because they think it's too hard to
replace them. Other negative impacts include the cost of hardware, the cost of
downtime required for upgrades, and the retirement of skilled resources with
legacy expertise.
Legacy Event Management Solutions Enter a Death Spiral
Sources: Gartner,Forrester, IBM
Source: Gartner
Source:
Increased Investment in IT Automation Benefits Digital Operations
In 2017, only one-fifth of organizations included “modernizing IT Operations” in
their overall digital transformation strategy, according to a study by Digital
Enterprise Journal. In 2018 we expect this number to double, with 40 percent of
top-performing enterprises increasing their investment in IT automation
technologies as a business strategy. We've reached a tipping point. Most
enterprise IT organizations have automated the software development lifecycle.
They have virtualized the datacenter. Now a clear majority of organizations - 63
percent - express the desire to improve their IT alerting & notification
capabilities, including automated incident escalation processes. This increased
investment will comprise not just new automation technologies, but IT “service
operations” – the people and processes that keep IT services operating
smoothly.
2018 Implication for Your IT Operations team:
Consider increasing investment in automated alert management capabilities as part of a drive to digital operations.
2
Implementing Automation Software
Expanding Existing Automation Footprint
Other
29%
201851%
71%
40%
53%
The Modern NOC - Predictions for 2018 | 2
Source:
Increase in Interest in IT Automation since 2011
Source: Digital Enterprise Journal
Digital Transformation Initiatives that will be
Supported by AI/Machine Learning, by 2019
Source: IDC
CIOs citing Machine Learning as a Core
Investment Priority
Source: ServiceNow
More Intelligent Monitoring Will Not Solve the Alert Noise Problem
Alert storms remain as inclement as ever. New machine learning offerings by
monitoring tools such as Splunk ITSI and AppDynamics/Perspica, while
encouraging, will not entirely solve this persistent alert management problem.
Applying intelligent capabilities to diagnostic monitoring data can better
identify anomalies so that humans don't have to configure them, but this
approach will still produce too many alerts. Machine learning when applied to
alert data that’s correlated across ALL enterprise monitoring tools provides a
more holistic view of critical incidents by adding change data and other
contextual information necessary to speed MTTR.
2018 Implication for Your IT Operations team:
Evaluate new machine learning offerings with a primary goal of reducing the total number of incidents requiring manual review.
3
The Modern NOC - Predictions for 2018 | 3
61%
More Enterprises Adopt Application-centric Monitoring
Enterprise IT operations teams are finding it hard to stretch their traditional
monitoring tools and strategies to cover dynamic, cloud native workloads. The
traditional "bottom-up" approach of very granular monitoring of individual
infrastructure components increasingly doesn't work in public clouds with their
elastic scaling and ephemeral resources. In 2018 forward-looking enterprises
will monitor business services & apps, not components. This focus on
"top-down" application-centric monitoring stresses user experience, transaction
availability and SLA compliance to measure service performance. It uses service
mapping to identify the stable, long-lived cloud elements on which any given
application depends.
2018 Implication for Your IT Operations team:
Eliminate infrastructure monitoring siloes by mapping application & service dependencies critical to delivering high availability & performance to the end user.
4
The Modern NOC - Predictions for 2018 | 4
IT Organizations reporting
Higher Customer Expectations
for Experience & Engagement
Source: Digital Enterprise Journal Source: Gartner
Source: Trace3 Research Source: Digital Enterprise Journal
IT Organizations citing Application
Performance Monitoring as
Important/ Critically Important
Average Cost of a Data Center
Outage
Average Cost per Minute for
Service Outages
68%
$740K $72K
Continued IT Staffing Shortage Drives Continued Service Automation
As enterprises continue to add new workloads and scale up relentlessly, they
will need to do so without adding additional NOC/IT Ops headcount. Humans
simply don’t scale very efficiently. The need for existing IT staff to focus on
solving business-oriented problems via digital innovation will drive the
continued automation of mundane manual IT tasks. For example, IT engineers
can concentrate on improving the customer experience only if intelligent
auto-remediation of critical incidents helps maintain service
availability/reliability without their intervention. By employing increasingly
autonomous technology to reduce MTTR and increase uptime, expert IT
resources can be refocused on adding business value.
2018 Implication for Your IT Operations team:
Plan for the continued shortage of skilled workers by automating whatever can be automated, especially in managing IT events.
5
Functions Suffering from Skills Shortage, according to IT Leaders
Big data/ analytics
Enterprisearchitecture
Business analysis
Technicalarchitecture
Security& resilience
Projectmanagement
Development
42%34% 34% 32%
28% 26% 25%
83%
The Modern NOC - Predictions for 2018 | 5
Organizations reporting the Tech Talent
Shortage has Hurt their Business83%Source: Indeed.com
Source: LinkedIn
Job Growth for Machine Learning
Experts, since 2012
1.4M 9.8XEstimated Number of
Open/unfilled IT Positions by 2020
Source: U.S. Department of Labor Statistics, Gartner
Sources:
Enterprises Will Demand BetterIT Operational Visibility
6
The Modern NOC - Predictions for 2018 | 6
45% 46%
90% 40%
IT Organizations reporting
5 or more Blind Spots in the
IT Service Value Chain
Source: Digital Enterprise Journal
IT Leaders Citing Delivery of
Better Business Intelligence as
an Operational Priority
Source: Harvey Nash/KPMG
CIOs say Greater Automation
Increases the Accuracy & Speed
of DecisionsSource: ServiceNow
CIOs who will Lose their Jobs
within 5 years due to Failure to
Deliver Business OutcomesSource: Gartner
In 2018, the nascent IT Operational Analytics marketplace will accelerate in
maturity. IT will be expected to share its business intelligence data with the rest
of the business. The focus on delivering better customer experiences will
demand IT actively optimize service performance and availability. This in turn
will drive the need for solutions that deliver operational visibility with robust
visual analytics. Moreover, ITOA will help rationalize machine learning and
monitoring tool investments. Enterprises will have clear visibility into which
“solutions” are not solving anything, and which ones are worth their weight in
gold. Gartner warns that up to 40 percent of today's CIOs could be turned out if
they fail to efficiently and reliably provide high quality results to the businesses
they serve.
2018 Implication for Your IT Operations team:
Start experimenting with emerging ITOA tools. Decide which metrics IT will share with executive leadership to support digital transformation.
IT Event Hubs Emerge in Open Integration Platforms
Open integration has been a key component of many IT operations platforms,
with some claiming to be a “system of record” thanks to wide interoperability
with myriad apps and tools. However, market momentum will build for
integration hubs specific to IT event management. Several vendors are offering
their version of a central incident data bus that marries ITOM monitoring to
ITSM ticketing systems. These special integration hubs incorporate real-time
monitoring data, change data, runbooks, even non-IT data streams – anything
that can add necessary context for speedier MTTR. Such hubs could perfectly
support intelligent workflows such as auto-remediation performed by ITSM
systems. Seamless integration between monitoring tools and IT operational
analytic systems could flow through them. “Event hubs” will exist in parallel, not
as a replacement, with systems of record.
7
16,590
18,850
2017 2018
The Modern NOC - Predictions for 2018 | 7
2018 Implication for Your IT Operations team:
Not all vendor claims of “open integration” are created equal. Evaluate them for their ability to add contextual data to speed incident resolution.
Source: Digital Enterprise Journal
Organizations Leveraging Machine Learning
that Report an Improvement in MTTR63%
Number of APIs Listed on ProgrammableWeb Directory
IT Buyers Will Start to Distinguish between Flavors of Machine Learning
In 2017 the differences between "open" and "closed" machine learning approaches
was something that only the most sophisticated IT buyers understood. To others, all
the buzz around AIOps from IT press and analysts seemed like so much marketing
fluff. However, as early forward-leaning enterprises begin to have more success with
applying machine learning to IT Ops, buyers will become more savvy. Half of IT
organizations are already applying machine learning in support more complex tasks
such as incident response, beyond simply managing alert volumes. Organizations will
have to decide between dual approaches. Black box, or “closed” machine learning, is
locked down and thoroughly trained with data by expert engineers before going into
production. White box, or “open” machine learning, is more exposed and transparent,
allowing greater user control on the fly. The correct model for any given IT
organization will depend on its unique environment and specific requirements.
2018 Implication for Your IT Operations team:
Keep any evaluation of machine learning technology focused on its ability to deliver the benefits promised, in a fully auditable fashion.
8
The Modern NOC - Predictions for 2018 | 8
CIOs who are Advancing beyond the
Automation of Routine Tasks to more
Complex Decisions
Sources: ServiceNow
Source: Gartner
Data Centers that Will Fail Operationally
if AI/Machine Learning Is Not Effectively
Applied
52%
30%
Serverless Enters the Mainstream Discussion
Serverless Computing is the next evolutionary step for software architecture in
the face of digital transformation. In the data center, going serverless moves
beyond provisioning virtual machines to buying dynamic workloads. More
forward-looking enterprises will start exploring serverless architecture in 2018.
Why? Because going serverless reduces many risks associated with scaling
digital operations. Visibility is important to manage alert volumes and ensure
the performance of service workloads. There's still a long way to go before
serverless becomes the dominant paradigm, but the coming year will see the
concept become part of the mainstream dialogue regarding the future of IT
Operations. By 2020, Gartner predicts that serverless will emerge as a leading
platform architecture for cloud-native application services.
2018 Implication for Your IT Operations team:
Your enterprise IT organization should begin playing with serverless in research & development, if not yet in production.
9
The Modern NOC - Predictions for 2018 | 9
Physical Servers
Virtual Machines/Containers
Functions
Source: Adrian Cockcroft
$100 - $1,000 per month
$10 - $100 per month
$1 - $10 per month
42%
Source: Trace3 Research
Average Increase in Annual IT Operating Cost per
Server with a Performance Monitoring Solution $800
AWS Lambda Revenue
Growth, 2016 to 2017
+5%
+12%
Serverless Solution Adoption Rates
2016 2017
References
Databorough: “Software Maintenance Productivity Factors”.
Digital Enterprise Journal: “Modernizing IT Operations for Digital Economy”, August 2017
Forrester Research: “Automation Drives the I&O Industrial Revolution”, November 2017
IDC: “The Dawn of the DX Economy and the Rise of the Digital-Native Enterprise”, November 2016
ServiceNow: “The Global CIO Point of View”, October 2017
Gartner: “End-User Experience Monitoring Is the Critical Dimension for Enterprise APM Consumers”, September 2016
Co.Design: “Dollars And Sense - The Business Case For Investing In UI Design”, March 2012
Trace3 Research: “360 View Trend Report: IT Operations Monitoring & Analytics”, February 2017
Digital Enterprise Journal: “Modernizing IT Operations for Digital Economy Research Study”, August 2017
Gartner: "Service Providers are Waging War Against U.S. Talent Shortage With Unconventional Methods," 2015
Indeed.com: “Is the Tech Talent War Hurting Innovation? Hiring Managers and Tech Recruiters Respond”, December 2016
Harvey Nash/KPMG: “CIO Survey 2017 - Navigating Uncertainty”
ProgrammableWeb API Directory
Adrian Cockcroft: Monitorama 2016, “Monitoring Challenges”, June 2016
About BigPanda
BigPanda Inc. enables Enterprise IT to intelligently automate
and scale Service Operations to meet the complex demands of
the modern datacenter. The company’s algorithmic machine
learning platform turns IT noise from fragmented clouds, teams,
applications and monitoring tools into actionable insights to
speed the resolution of IT incidents. Many of the world’s largest
enterprises such as Intel, Workday, News Corp, Macy’s, and Cisco
rely on BigPanda to power their Service Operations.
www.bigpanda.io
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