Our comments:
DevOps Engineer
Limited Impact of AI on the Job
13.33%
level of automation
0%
100%
This section reviews the 3 main tasks associated with the job studied and assesses the potential level of automation induced by AI ('AI Automation Impact').
The modeling uses 8 criteria detailed on the 'Methodology' page.
The modeling uses 8 criteria detailed on the 'Methodology' page.
Tasks | AI Automation Impact |
---|---|
Collaborate closely with developers and operations teams to automate and optimize workflows | Moderate |
Set up and maintain tools and infrastructure for continuous application deployment | Low |
Monitor application performance and ensure its availability | Significant |
Through our research, we have identified two pivotal categories of skills that will be impacted by AI-driven automation :
- 'At-risk skills,' which are likely to become obsolete due to their susceptibility to automation
- 'Future-proof skills', which are projected to retain their value and resist automation, thereby ensuring their relevance in the forthcoming job market.
At-risk Skills | |
---|---|
Implementation & maintenance of continuous integration/deployment tools | With the evolution of cloud technologies and "as-a-service" tools, it has become increasingly easier to establish and manage CI/CD pipelines without the need for deep human intervention. Tools like GitHub Actions, GitLab CI/CD, and others offer more user-friendly methods to manage these pipelines. |
Basic monitoring and alerting | Automated monitoring and alert systems have become the norm. Tools like Prometheus, Grafana, and others can automatically detect anomalies and send alerts without requiring complex manual setup. |
Future-proof Skills | |
---|---|
Inter-team collaboration | The ability to collaborate closely with developers, operational staff, and other stakeholders is crucial. This "human" skill is difficult to automate as it requires effective communication, conflict resolution, and a nuanced understanding of the needs and challenges of each team. |
Workflow optimization | While some tools might suggest improvements, the ability to analyze and rethink existing workflows to make them more efficient requires critical thinking and a deep understanding of the processes. This skill combines technical understanding with an overview of the development process. |
How does AI impact this job type ?
Get the full analysis
In the sphere of DevOps, the proliferation of AI-based tools, while streamlining the monitoring and optimization of infrastructures, injects a nuanced complexity, requiring professionals to adeptly interpret data and make discerning judgements.
This necessitates DevOps professionals not only to actively engage with AI-enhanced analytics but also to integrate a context-driven decision-making approach, which is deeply rooted in a comprehensive understanding of system interactions, a keen awareness of end-user needs, and a strategic alignment with the company’s overarching objectives