6 ways DevOps automation will change in 2020
As more organizations adopt DevOps automation and strategies, usage of automation evolves. In 2020, there are several changes you are apt to see, such as seamless infrastructure, AI and data science collaborations, zero-touch automation, and more. Read on to discover what are the biggest automation trends of 2020, and how they might impact your pipelines.
DevOps is a software development strategy that combines development and operations teams into one
collaborative group. It typically incorporates agile methodologies, continuous integration / continuous delivery (CI/CD) workflows, and automation tooling. The goal of DevOps is to deliver high-quality software as quickly as possible.
DevOps requires clear communication between team members and often involves a significant change in perspective from traditional workflows. In exchange, it can enable teams to develop efficient, effective, sustainable, and secure workflows.
DevOps automation benefits
DevOps is widely adopted due to the benefits it provides over traditional, siloed approaches. In particular, it is often adopted due to how its adoption of automation improves processes. These improvements include:
- Reduces the implementation and delivery time of services
- Increases the productivity of development and operations teams
- Saves costs by reducing manual work and optimizing resources
- Standardizes processes for faster delivery and greater reliability
- Improves performance and reduces redundancy in tooling
DevOps automation can benefit a wide range of projects, from government IT to commercial software delivery. It enables teams to embrace current technologies and to optimize processes, leaving more time for innovation.
6 ways DevOps automation will change in 2020
In this section, you’ll find a review of six automation trends that are set to change DevOps pipelines.
1. Demand for infrastructure automation governance
As organizations adopt more automation tools and increase their number of automated processes, governance becomes vital. Due to this, organizations will begin prioritizing automation compliance, security, and cost audits in 2020.
This increased governance will require organizations to monitor and validate:
- How automation is built – including what safeguards or checks are put in place and how systems are monitored
- How it is used – including who is using it and what systems or services have access to automation tools
- How it is secured – including how secrets are managed, how access is managed, and how vulnerabilities are identified
- How it is optimized – including cost control measures, resource management, and performance verification
To ensure effective governance, organizations will need to invest in and implement comprehensive control
mechanisms. These mechanisms need to supply visibility into their systems and cover a range of environments, including in the cloud and on-premises.
2. Drive for seamless infrastructure
Automation tooling will become more integrated into systems and processes. Those teams with on-premises
expertise will customize tooling to better integrate with existing infrastructures. Meanwhile, smaller or less expert teams will consume pre-built plug-ins and replace incompatible resources and tooling. This demand will open the market for managed solutions as well as new products.
To achieve seamless infrastructure, teams will need to:
- Evaluate how automation is used and current infrastructure limitations
- Manage a balance of technical debt and new tooling
- Ensure that team roles are fairly represented and supported by any automation that is adopted
3. Inclusion of AI and data science
Automation is often tied to both AI and data science. It uses the former to direct actions and is used in the latter to perform analyses efficiently. However, both AI and data science can also be used to improve automation processes and efficiency. For example, DevOps teams can analyze log data to determine where to make pipeline optimizations. Or, they can use AI to adaptively determine testing suites or deployment times. Both of these uses will increase as teams try to achieve even greater productivity.
The inclusion of AI and data science will also increase in other departments. For example, pipelines similar to those used in DevOps can be used by marketing teams to provide hyper-personalized content to customers. Hyper-personalized content uses individual customer data to supply content that closely matches personal interests and preferences. This use of automation pipelines in other areas of business will create a demand for more intelligent and specialized automation tooling.
4. Maturation of SRE role
Site Reliability Engineering (SRE) is a predecessor of DevOps. It combines aspects of development, operations, and infrastructure management into a single role. For many organizations, the leap from siloed roles to fully combined responsibilities was too great. However, the adoption of DevOps has created an overlap of many team members’ knowledge and skillsets. This overlap makes a single, unified SRE role more accessible and achievable.
This growing accessibility is especially important as more of operations processes and tooling relies on code. For example, the growth of infrastructure as code that is common in many cloud deployments. To manage expanding pipelines and other automated processes, team members will need to develop SRE skillsets and adopt SRE responsibilities.
5. Availability of zero-touch automation
Zero-touch automation involves setting automated processes that then use machine learning to adapt to
changing conditions and needs. It is currently being developed primarily in telecom industries but has potential in a variety of fields.
As this technology is refined, you can expect to see it adopted into DevOps pipelines. With effective integration, zero-touch automation could further improve the agility and speed of software development and deployment.
6. Increased trust and communication
At the foundation of DevOps is collaboration, which relies on trust and communication between team members. To improve the effectiveness and efficiency of DevOps processes, organizations must work to foster and increase this trust and communication. To achieve these gains, organizations will leverage automation to provide support for teams. Two ways this can be achieved are:
Better incorporation of feedback and alerting tools – these tools improve process visibility and accountability. When individuals can see the work that each member is doing and participate in its evaluation, they gain respect and trust for other members.
Automated environment creation – in particular staging environments. Staging environments can help bridge the gap between development and release. As teams see that products are reliably ready for production without intervention, they will gain trust in their automated infrastructures.
DevOps, just like other agile methodologies, promotes a dynamic workflow. Change is a huge part of the process, so it’s only natural automation itself will undergo massive change. As automation technologies continue to absorb practices and tooling from other fields, DevOps automation becomes more sophisticated, enabling DevOps teams to do more in less time.