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DevOps disruptors in 2019

(Image credit: Image Credit: Profit_Image / Shutterstock)

A new year inevitably brings challenges and opportunities for businesses across the world, and in the run up to the festive period we’re likely to see experts from all industries make predictions on the processes and strategies which most will help businesses to grow during the year ahead.

What’s less well covered by the media, but still crucial to business growth, is what’s happening behind the scenes in application development and testing. The DevOps function - in theory the seamless integration of app development, testing and quality assurance - is increasingly being recognised as a strategic business function, as it powers the delivery of products and services with maximum efficiency, speed and quality. Innovations in this field may be make or break for a business.

So let’s have a look at the game changing innovations in 2019.

1. AI and machine learning will speed up DevOps quality analysis

Machine learning (ML) is now being successfully applied in all walks of life, and the development community is no exception. Development teams need to analyse more data and are have less time to do it, whilst their margin of error also decreases constantly. Tools such as machine learning and predictive analytics offer a way to address these challenges. Undoubtedly, good use of data helps developers make smart decisions based on fact, not on assumptions.

Crucially, ML and AI solutions will automate the slicing and dicing of data to quickly provide root-cause analysis for issues that are detected during the DevOps pipeline testing activities. At Perfecto, we believe that up to 80 per cent of issues have a pattern, so being able to categorise them is important: Are twenty per cent of my errors related to poor coding? Is a similar percentage due to security issues? Being able spot patterns and usefully classify them is a vital part in eliminating errors and smoothing the testing pipeline.

When it comes to measurable impact, real life use-cases are already showing the potential benefits of ML. For example, the ability to transcribe speech plays an important role in chatbot or accessibility applications - which are growing in popularity and fulfilling a genuine need for thousands of users.

Perhaps the biggest benefit of AI is the ability to analyse your entire Continuous Integration activities. AI can provide an overview of how your pipeline is working, and how changes you make affect it - oversight which would take significant time and effort ordinarily.

Away from the lab as the market demand grows, businesses need to find a way to be a step ahead of their competitors and able to predict their consumers’ needs. Predictive analytics plays a key role here as it allows businesses to analyse customer data to better understand (and predict) what new products and features they’ll want next.

Making the most of data relies on a fundamental mindset shift. In all business areas there is a fear that the ‘bots are coming’ for jobs, but in testing particularly this type of tech is enhancing developers’ abilities not replacing it.

2. Continuous testing will rely on Open Source Software

In 2019, we see will be a significant shift from commercial testing to open source tools, which will have a dramatic effect on the testing vendors in the market.

There are several reasons for this. We all know that continuous testing is a critical component for optimising DevOps pipelines, and by its definition, to continuously test teams must be able dramatically scale the number of tests being executed, including running full regression cycles nightly as opposed to end of the Dev cycle and a massive “shift-left” of testing, all the way to the pre-commit and per-commit level.

However, traditional commercial solutions struggle to meet the demands of continuous testing in two ways. Firstly, they do not scale, nor do they have the reliability to meet continuous testing requirements. Secondly, with shift-left, the persona of the test author shifts from QA to Dev. All this means that  yesterday’s commercial solutions are simply not a fit for today’s developers.

Instead, Open Source solutions are a vital piece of making continuous testing a reality. True open source frameworks such as Appium, Selenium, Nightwatch.js, Angular and Quantum are being widely adopted in the industry to enable continuous testing on huge scale. Away from open source itself, free platforms such as Espresso and XCUITest are targeted directly at developers authoring tests, making their jobs quicker and easier too. We believe that vendors in the testing space must embrace these open source frameworks as part of their offering and ideally provide value-add on top of them (enterprise support, extended capabilities, better reporting, etc.) if they are to maintain a competitive advantage.

3. Microservices will have a significant impact on DevOps

Microservices isn’t a new trend - but it’s one which will continue to make inroads in the DevOps community in the year ahead. The premise of microservices is to make the Software Development Lifecycle (SDLC) as independent as possible - slicing and dicing your product into different, discreet, services. This means if something breaks, you can identify and fix it quickly, without the whole application of service falling over.

On the development side, you can introduce new capabilities or functions into a single area of a product without affecting other parts. This is a mature and agile approach to app development which allows companies to bring services and updates to market much more quickly. Indeed, at Perfecto our own portfolio of cloud services is based on microservices - and it’s paying dividends for us. If we want to push a new service, or update a function, we’re able to do so quickly - and with no disruption. Crucial for happy customers.

Effectively, the microservices architecture is all about doing one thing well, and we know that this is a significant shift from designing monoliths that are conglomerates of many "services" lumped into one. But, breaking down the large bulky team that developed the monolith into multiple smaller (and more nimble) teams benefits all, and it’s one which teams must adopt if they’re going to continue to succeed.

So, with significant developments on the horizon, and the opportunity to build on the successes of 2018’s trends, the potential for developer teams to make strides in the year ahead is promising. Companies that have implemented DevOps have already seen increased business efficiency and faster deployment, and approaches like microservices, open source solutions and the clever use of machine generated data mean that these smart companies will be able to deliver quality services quicker and more efficiently than ever. Those who don’t, simply, risk being left behind.

Eran Kinsbruner, lead technical evangelist, Perfecto
Image Credit: Profit_Image / Shutterstock

Eran Kinsbruner
Eran Kinsbruner is the lead technical evangelist at Perfecto and the author of the digital quality handbook. He is a software engineering professional with nearly 20 years of experience at companies such as Matrix, Qulicke & Soffa, Sun Microsystems, General Electric, Texas Instruments and NeuStar. He holds various industry certifications such as ISTQB, CMMI, and others. Eran is a recognized mobile testing influencer and thought leader. He is also a patent holding inventor (test exclusion automated mechanism for mobile J2ME testing), public speaker, researcher, and blogger.