2016 DevOps Predictions - Part 4
December 18, 2015

In DEVOPSdigest's first annual list of DevOps Predictions, experts — analysts and consultants, and the top vendors — offer thoughtful, insightful, often controversial and sometimes contradictory predictions on how DevOps and related technologies will evolve and impact business in 2016. Part 4 covers analytics, SaaS, testing and more.

Start with 2016 DevOps Predictions - Part 1

Start with 2016 DevOps Predictions - Part 2

Start with 2016 DevOps Predictions - Part 3

AUTOMATING DEVOPS WITH ANALYTICS

Over the past five years, DevOps teams have focused on automating the delivery of applications into production using provisioning/release/build/config automation tools. It's now time for DevOps teams to automate the way they support applications in production by leveraging software analytics and machine learning to automate the manual tasks of incident detection, troubleshooting and root cause analysis. Relying on humans to manually analyze or search for answers makes no sense in a culture of agility and automation. DevOps teams need to start leveraging machine learning technologies so they can automate much of the tedious tasks that still exist for supporting applications.
Steve Burton
Chairman, VP of Product Marketing, Moogsoft

The increasing complexity of enterprise applications has resulted in too many moving parts that impact the quality of service to end users. While monitoring tools successfully exposes more performance metrics than ever, the growing number of charts that visualize symptoms does not make manual root cause analysis via correlation easier any more. DevOps teams will start looking for tools that automatically interpret and analyze performance data, so that they could ensure high SLA while spending most of their time on developing new functionality.
Priit Potter
Co-founder and CEO, Plumbr

Next year, we will see DevOps teams augment traditional APM tools and rule-based monitoring with behavioral analytics. By complementing the output of already-valuable APM tools with a behavioral analytics solution, previously unknown anomalous behavior can be identified in near real-time, enabling fast moving DevOps teams to remain agile by focusing more on deploying and testing new software and less on sorting through a sea of alerts. With more data being created than ever before, behavioral analytics powered by automated unsupervised machine learning will enable DevOps teams to transform gained insights into a competitive advantage.
Mike Paquette
VP of Products, Prelert

NEW ANALYTICS TOOLS FOR TRACKING CHANGES

While DevOps and other agile methodologies already allow IT to deliver changes into production at an overwhelming pace, we see how this is also introducing real challenges from a stability perspective, leaving IT ops vulnerable. Although most performance incidents ultimately result from changes (about 85% of incidents can be traced to changes, according to Gartner), monitoring and analyzing changes is still overlooked by DevOps and Ops teams. We expect to see a new generation of analytics-powered DevOps and ITOA tools that will help deal with the challenges introduced by DevOps by collecting and analyzing all actual changes across entire environments, assessing their impact and thus allowing IT teams to plan accordingly. Monitoring all actual changes and analyzing them together with release and deployment data, will allow for smooth, error free releases. Specifically, these analytics tools will be able to identify key gaps between pre-production, production and DR; detect inconsistency and missing pre-requisites that impede deployments; validate deployments by accuracy and consistency; identify root-causes of stability issues due to deployments. IT won't have to sacrifice stability for agility anymore.
Sasha Gilenson
CEO, Evolven

BUSINESS INTELLIGENCE VITAL TO DEVOPS SUCCESS

Analytics will focus on both IT and Business analytics. The first major implications will be a decline in monitoring tools and more correlation between existing tools. Major companies will reliaze that they have all the tools they need but they don't connect them correctly. Business analytics is a large market but very immature. The rise of DevOps will help business analytics focused companies grow.
Coen Meerbeek
Online Performance Consultant and Founder of Blue Factory Internet

DEVOPS LEVERAGES SAAS

Over the past few years DevOps has become an accepted approach and philosophy for building and managing today's systems. My prediction is that 2016 will see a lot of mainstream adoption of DevOps, in particular in the large enterprise. This means more adoption of technologies that make up the modern DevOps toolkit, primarily SAAS services. Over the past few years, people have really started to move away from the on-prem, "roll your own" solutions, and some of the old dinosaurs that tried to provide everything in one box. Now, DevOps professionals are more often taking advantage of specific, cloud-based services that are more flexible, require less investment up front, and practically zero management.
Trevor Parsons
Senior Director, Log Management & Search, Rapid7

In 2016 the adoption of cloud delivered SaaS offerings will begin to take hold in areas that, especially for the larger more established enterprises, have so far been largely off limits. Long held assumptions concerning the necessity to host applications on-premises such as those responsible for infrastructure management will be challenged as the demonstrable security and reliability of cloud hosting services becomes broadly accepted. The industry sectors that are assumed to be unable to take advantage of these software product delivery options will start to experiment and rethink their assumptions leading to a previously unthinkable revolution in how they take advantage of third party services. With SaaS comes the opportunity to benefit from the continuous development and deployment principles of DevOps and those vendors already practicing this methodology internally will be best placed to exploit this exciting new frontier.
John Diamond
Principal Solutions Architect, Entuity

CONSOLIDATION OF AUTOMATION TOOLS

Automation is proven to enable DevOps speed and efficiency. In 2016 we'll start to see IT organizations simplify automation with tool chain consolidation. Infrastructure automation and application stack automation tools will start to merge, and IT organizations will look to use one tool that works across data center, private cloud and public cloud environments.
Kurt Milne
VP of Product Marketing, CliQr

PERFORMANCE TESTING BECOMES CRITICAL COMPONENT OF DEVOPS

In 2016, performance testing will come to be viewed as a first class component of a continuous delivery and DevOps pipeline, and as being essential to overall software quality practices. This will happen through the adoption of emerging open sources tools that provide the right capabilities for modern performance testing automation. Developers and DevOps teams will be able to implement performance testing patterns and practice more easily, and better drive overall quality initiatives in their organizations.
Michael Sage
Chief Evangelist, BlazeMeter

2016 will be the year where we start seeing an increased focus on app testing as a critical part of the application development lifecycle. Access to cloud-based, scalable and turnkey testing tools that integrate well with continuous delivery flows will be paramount. The DevOps tools conversation will expand from continuous integration and infrastructure configuration solutions to a broader set that includes scalability testing and performance testing, as well as unit testing. Seamless testing is critical for any DevOps flow to succeed, for the DevOps promise to be delivered and for businesses to achieve the right speed of execution.
Paola Moretto
Founder and CEO, Nouvola

LOAD TESTING MOVES TO THE CLOUD

In 2016, we'll see more enterprises moving load testing to the cloud. Companies are under constant pressure to deliver products and services to the market faster than ever before. Meanwhile, business owners are exhausted by in-house IT departments with slower than needed delivery cycles. In this dichotomy, performance must not be sacrificed. By using load testing from the cloud capabilities, the business and technology teams both get what they need: Technology gets an affordable, secure way to test system and application performance before it reaches production, and the business doesn't have to wait so long that it loses competitive advantage.
Todd DeCapua
Chief Technology Evangelist, Hewlett Packard Enterprise

DEVOPS APPLIED TO INFRASTRUCTURE DELIVERY

DevOps moves out of delivering skunkworks and front office applications toward the back office, taking over infrastructure delivery for most customers. Gaining momentum inside more traditional enterprises, DevOps has been proving its worth as a way to replace slow and inefficient service delivery. The time is right for agile processes to completely take over other areas, and make IT infrastructure delivery faster, more reliable and more accountable.
Brian Promes
Director of Product Marketing, SevOne

Read 2016 DevOps Predictions - Part 5, the final installment of DevOps predictions.

Share this

Industry News

July 08, 2025

BrowserStack announced the launch of BrowserStack AI, a suite of AI agents integrated throughout the testing lifecycle to help software teams accelerate release cycles, improve test coverage, and boost productivity by up to 50%.

July 08, 2025

Coder introduced a major platform upgrade designed specifically for enterprise teams working with AI coding agents.

July 08, 2025

LambdaTest has announced the release of SmartUI’s Smart Branching and Baseline Management.

July 08, 2025

Lens by Mirantis announced the availability of Lens Prism, a fully-integrated, production-grade artificial intelligence (AI) assistant embedded directly within the Lens integrated development environment (IDE).

July 08, 2025

vFunction announced GenAI-powered capabilities to refactor and rearchitect applications.

July 08, 2025

Payara announced a strategic partnership to help enterprises modernize their Java applications with a codeless, lift-and-shift migration solution, reducing infrastructure and cloud costs and boosting performance and scalability.

June 26, 2025

Backslash introduced a new, free resource for vibe coders, developers and security teams - the Backslash MCP Server Security Hub.

June 26, 2025

Google's Gemma 3n is the latest member of Google's family of open models. Google is announcing that Gemma 3n is now fully available for developers with the full feature set including supporting image, audio, video and text.

June 26, 2025

Google announced that Imagen 4, its latest text-to-image model, is now available in paid preview in Google AI Studio and the Gemini API.

June 26, 2025

Payara announced the launch of Payara Qube, a fully automated, zero-maintenance platform designed to revolutionize enterprise Java deployment.

June 25, 2025

Google released its new AI-first Colab to all users, following a successful early access period that had a very positive response from the developer community.

June 25, 2025

Salesforce announced new MuleSoft AI capabilities that enable organizations to build a foundation for secure, scalable AI agent orchestration.

June 25, 2025

Harness announced the General Availability (GA) of Harness AI Test Automation – an AI-native, end-to-end test automation solution, that's fully integrated across the entire CI/CD pipeline, built to meet the speed, scale, and resilience demanded by modern DevOps.

With AI Test Automation, Harness is transforming the software delivery landscape by eliminating the bottlenecks of manual and brittle testing and empowering teams to deliver quality software faster than ever before.

June 25, 2025

Wunderkind announced the release of Build with Wunderkind — an API-first integration suite designed to meet brands and developers where they are.

June 25, 2025

Jitterbit announced the global expansion of its partner program and new Jitterbit University partner curricula.