Originally sourced from DZone. This article reflects predictions made at the start of 2017 and is preserved here as a historical reference for DevOps practitioners.
At the start of 2017, DevOps analysts, practitioners, enterprise customers, and technology vendors put forward a range of forecasts — some optimistic, some cautionary, and a few directly contradicting one another. Taken together, they painted a picture of a discipline maturing rapidly but still wrestling with cultural, organisational, and tooling challenges.
Below are nine predictions that defined the DevOps conversation entering 2017.
1. DevOps at Scale
If 2016 was the year DevOps went mainstream, 2017 was expected to mark the rise of DevOps at scale. Early adoption figures were already high, but the challenge shifted from getting started to driving DevOps practices across the entire software delivery lifecycle — not just isolated teams or projects.
A key indicator of this shift was growing interest in Continuous Testing across the full application delivery pipeline. The goal was not only to “shift left” — engaging testing earlier in the SDLC — but also to “shift right”, applying consistent quality practices through staging and production environments.
2. DevOps Becomes Mission-Critical
As development velocity increased and enterprise environments grew more complex, DevOps principles were expected to move from “nice to have” to genuinely mission-critical. Large enterprises already dealing with wide gaps between development and production environments were forecast to deepen their reliance on DevOps practices to manage the complexity introduced by continuous delivery pipelines and automation at scale.
3. DevOps as Competitive Advantage
2017 was predicted to see DevOps emerge as a meaningful competitive differentiator. Organisations with mature DevOps capabilities would be better positioned to launch new services faster, iterate based on customer feedback, and adapt to changing market conditions. As end users came to expect rapid, iterative improvements to the products and services they consumed, organisations without that delivery agility would find themselves at a disadvantage.
4. DevOps Failures Would Surface
Not all predictions were optimistic. Several experts warned that 2017 would also bring high-profile DevOps failures — and that those failures would be instructive.
The pattern predicted was familiar: organisations investing in DevOps tooling (CI servers, automation platforms, deployment pipelines) without addressing the underlying cultural and organisational changes that make those tools effective. Buying Jenkins and standing up automation scripts is not sufficient to achieve faster delivery without sacrificing quality. The root cause in most failure cases was expected to be teams looking for shortcuts and avoiding the harder work of genuinely changing how software is built and delivered.
“Having Jenkins and automation is not enough to achieve faster delivery without sacrificing quality.”
5. Digital Transformation Goes Mainstream
2017 was widely tipped as the year when digital transformation initiatives would stop being the province of technology-native companies and become a survival requirement for traditional enterprises. The pressure to deliver business capabilities through software — rather than manual processes — was forecast to become unavoidable across most industries.
A key tension identified was that while application teams increasingly wanted to abstract away infrastructure concerns, the reality of infrastructure behaviour (latency, availability, compliance requirements) would continue to surface at the application layer, regardless of how heavily outsourced or cloud-hosted that infrastructure was.
6. BizDevOps: Aligning Development with the Business
A significant theme for 2017 was the emergence of BizDevOps — extending the collaboration model beyond Development and Operations to include business stakeholders. Analysts predicted that organisations would use DevOps practices to align software delivery more tightly with business objectives, KPIs, and outcomes.
DevOps tooling was expected to evolve to provide broader visibility into the relationship between release cycles and business performance data. The goal: help engineering and operations teams make decisions informed by real business impact, rather than purely technical metrics.
7. Business-Centric Agile
Related to BizDevOps, 2017 was predicted to be the year of business-centric Agile. With DevOps teams demonstrating real progress on collaboration and delivery speed, attention would shift up the stack toward the business buyer and end user.
This meant creating shared context between technical teams and business stakeholders through clearer requirements documentation and shared delivery goals. Regulatory pressures — including emerging frameworks like the EU-US Privacy Shield — and the need to support omnichannel user experiences were cited as drivers that would force a more integrated approach to business-aligned agile delivery.
8. DevOps Expands Across IT Disciplines
DevOps practices were forecast to extend beyond their traditional home in application development and deployment pipelines. Areas such as security, testing, and database management were expected to receive greater attention and budget in 2017 — specifically because they were increasingly identified as the biggest bottlenecks preventing faster application releases.
The concept of DevSecOps — integrating security practices directly into the CI/CD pipeline — was beginning to gain traction, and 2017 was seen as a year when that integration would become more structured and deliberate.
9. Monitoring Becomes a First-Class DevOps Concern
Perhaps the most forward-looking prediction: 2017 would be the year monitoring and observability moved to the centre of DevOps practice. Until that point, most tooling and process investment had concentrated on the pre-production side of the pipeline — build, test, and deploy automation. The post-deployment feedback loop had received comparatively little attention.
Analysts predicted that maturing DevOps programmes would shift focus toward production monitoring, particularly as architectures became more complex (microservices being the primary example). New monitoring technologies and updated evaluation models were expected to emerge to support this shift.
Looking Back at 2017’s DevOps Predictions
These nine predictions capture a discipline at an inflection point: widespread in name, but still uneven in execution. The themes they raised — scaling beyond pilot teams, aligning with business outcomes, building observability into production, and confronting cultural rather than purely technical change — remained relevant well beyond 2017 and continue to shape DevOps practice today.
The most durable lesson embedded in these forecasts may be the simplest: tooling alone does not make a DevOps transformation. The organisations that succeeded were those willing to address the harder problems of culture, collaboration, and continuous improvement alongside their investment in automation.