What's Ahead for the Software Testing Industry in 2018?
January 12, 2018

Sven Hammar
Apica

Share this

As we enter 2018, businesses are busy anticipating what the new year will bring in terms of industry developments, growing trends, and hidden surprises. In 2017, the increased use of automation within testing teams (where Agile development boosted speed of release), led to QA becoming much more embedded within development teams than would have been the case a few years ago. As a result, proper software testing and monitoring assumes ever greater importance.

The natural question is – what next? Here are some of the changes we believe will happen within our industry in 2018:

AI Breakthroughs Will Begin

Organizations will make breakthroughs with machine learning and artificial intelligence in 2018, especially when it comes to using this technology to get a better understanding of their collected data.

Often, it's hard to see the physical manifestation of wider concepts like AI, but in our space, physical objects – “intelligent things” – fill that gap. Previously, IoT devices sent data for limited onward processing; now, machine learning means devices are capable of transforming that same data into actionable insight. Realtime feedback will change the behavior of our IoT devices for good.

Focus on Quality, Security and Resilience

Businesses will need to address the overall quality of their services as the competitive landscape evens out

Given the high level of major outages in 2017, it is evident that the industry has not been moving fast enough to address the explosive growth of the IoT and API economy. There are organizations that are leading the way and achieving great things in both testing and monitoring; however, most are still disproportionally focusing on speed rather than quality, security and resilience.

Looking into 2018, businesses will need to address the overall quality of their services as the competitive landscape evens out. This will result in a refocus on the monitoring of the customer experience and the need for extensive end-to-end testing, embedded within the delivery lifecycle.

Services Will be a Key Differentiator

In 2018, services will become more of the differentiating factor, as capabilities become more similar. Differentiation of services will come down to availability, ease of use and consistency of a quality experience.

The increased reliance on IoT devices, their data and their management will also drive the need for high availability of the API services that these devices will talk to. Monitoring the availability of these APIs will be the critical factor in ensuring that business can continue to run (especially in the manufacturing space), and that business intelligence data can be trusted by decision makers.

Customer Experience Will Become More Important Than Ever

Software testing and monitoring has historically been the realm of the IT team, be that the development teams for testing, or operations on the monitoring side.

In 2018, the digital transformation drive is underway in most enterprises, combined with the explosion of IoT devices and the data processing that derives from them. This will draw the focus onto both the quality of the application and the overall customer experience.

Consequently, both testing and monitoring should be of significant interest to the Chief Operating Officer and the Chief Marketing Officer within organizations, resulting in more rounded testing with team members coming from different parts of the business. That's a potential step change in the type of testing that would be carried out, as well as in the visibility within the business of monitoring results and testing success.

The Way We Validate Results Will Change

2018 will see the adoption of AI, in the form of machine learning, by major software vendors who will be embedding it within their core applications. This machine learning will also become a standard platform for data analytics for new development initiatives. The IoT market will take greatest advantage from this adoption, as the volume of data needing analysis grows exponentially.

This is going to challenge the testing community as new ways of testing and validating the results from AI need to be identified and embedded within the development lifecycle.

Sven Hammar is Chief Strategy Officer and Founder of Apica
Share this

The Latest

September 22, 2021

The world's appetite for cloud services has increased but now, more than 18 months since the beginning of the pandemic, organizations are assessing their cloud spend and trying to better understand the IT investments that were made under pressure. This is a huge challenge in and of itself, with the added complexity of embracing hybrid work ...

September 21, 2021

After a year of unprecedented challenges and change, tech pros responding to this year’s survey, IT Pro Day 2021 survey: Bring IT On from SolarWinds, report a positive perception of their roles and say they look forward to what lies ahead ...

September 20, 2021

One of the key performance indicators for IT Ops is MTTR (Mean-Time-To-Resolution). MTTR essentially measures the length of your incident management lifecycle: from detection; through assignment, triage and investigation; to remediation and resolution. IT Ops teams strive to shorten their incident management lifecycle and lower their MTTR, to meet their SLAs and maintain healthy infrastructures and services. But that's often easier said than done, with incident triage being a key factor in that challenge ...

September 16, 2021

Achieve more with less. How many of you feel that pressure — or, even worse, hear those words — trickle down from leadership? The reality is that overworked and under-resourced IT departments will only lead to chronic errors, missed deadlines and service assurance failures. After all, we're only human. So what are overburdened IT departments to do? Reduce the human factor. In a word: automate ...

September 15, 2021

On average, data innovators release twice as many products and increase employee productivity at double the rate of organizations with less mature data strategies, according to the State of Data Innovation report from Splunk ...

September 14, 2021

While 90% of respondents believe observability is important and strategic to their business — and 94% believe it to be strategic to their role — just 26% noted mature observability practices within their business, according to the 2021 Observability Forecast ...

September 13, 2021

Let's explore a few of the most prominent app success indicators and how app engineers can shift their development strategy to better meet the needs of today's app users ...

September 09, 2021

Business enterprises aiming at digital transformation or IT companies developing new software applications face challenges in developing eye-catching, robust, fast-loading, mobile-friendly, content-rich, and user-friendly software. However, with increased pressure to reduce costs and save time, business enterprises often give a short shrift to performance testing services ...

September 08, 2021

DevOps, SRE and other operations teams use observability solutions with AIOps to ingest and normalize data to get visibility into tech stacks from a centralized system, reduce noise and understand the data's context for quicker mean time to recovery (MTTR). With AI using these processes to produce actionable insights, teams are free to spend more time innovating and providing superior service assurance. Let's explore AI's role in ingestion and normalization, and then dive into correlation and deduplication too ...

September 07, 2021

As we look into the future direction of observability, we are paying attention to the rise of artificial intelligence, machine learning, security, and more. I asked top industry experts — DevOps Institute Ambassadors — to offer their predictions for the future of observability. The following are 10 predictions ...