Top 6 DevOps trends to look for in 2023

DevOps is a philosophy and set of practices that aim to improve collaboration and communication between software development and operations teams and to streamline the process of building, testing, and deploying software. CI/CD is a key component of this process, as it helps to automate the build, test, and deployment steps, which can speed up the software development process and reduce the risk of errors or issues in the production environment.

With advances in technology, applications are becoming much more capable in terms of functionality and value delivery. However, this also means that their underlying microservices architecture is increasing in complexity, and working on their deployments at scale is a huge challenge. 

Organizations are in pursuit to tackle these challenges and improve “how they DevOps”. Due to this, the dynamics of DevOps teams in terms of their processes, toolchains, workflows, policies, and infrastructure keep changing. For companies who are in the process of adopting DevOps or wish to accelerate their DevOps maturity, it makes sense to keep track of these changing DevOps trends. 

It is difficult to predict such changes in the field of DevOps with certainty, as the technology landscape is constantly evolving. However, here are a few potential trends that may emerge in DevOps in the coming years, a few of which are also being implemented right now as you read this blog:

1. Serverless Computing

Serverless Computing is a cloud computing execution model in which the cloud provider dynamically allocates resources to run applications, and the user pays only for the resources used during the execution of their applications. In serverless computing, the user does not have to worry about the underlying infrastructure and can focus on writing and deploying their code.

Serverless computing can be a good fit for applications that have variable workloads or that only need to run for a short period of time because it allows the user to pay only for the resources used while the application is running. This can be more cost-effective than using traditional servers, which are paid for whether they are being used or not.

There are a number of cloud providers that offer serverless computing platforms, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). These platforms allow users to deploy their code as functions, which are executed in response to events or triggers, such as an HTTP request or the arrival of new data.

DevOps and serverless computing can work together to enable the continuous delivery of applications. By following the practices of continuous integration and continuous delivery, developers can build, test, and deploy their code quickly and reliably. Serverless computing can then be used to run the application in a flexible and cost-effective way.

2. Low-Code Platforms

Low-code platforms are indeed a useful tool for extending the benefits of agile and DevOps. They allow developers to build and deploy applications quickly and easily, without having to write a lot of code. This can be especially beneficial for organizations that need to develop and deploy applications quickly, as it allows them to respond to changing business needs and market conditions more effectively.

Low-code platforms can also be a good fit for organizations that want to adopt a DevOps approach, as they can facilitate collaboration between developers and IT operations teams. By using a low-code platform, developers can focus on building and testing the application, while IT operations teams can focus on deployment and monitoring. These platforms usually integrate with all major DevOps tools and thus help in becoming a single interface for managing CI/CD.

Overall, low-code platforms can be a valuable tool for organizations looking to adopt agile and DevOps practices, as they can help to accelerate the development process and improve the quality and reliability of applications.

3. Greater Application of AI/ML

Machine learning and artificial intelligence may play a larger role in DevOps in the future. For example, machine learning algorithms could be used to predict and prevent problems in the software development process, or to optimize resource utilization in the cloud for cloud cost management. Through ML, deployment platforms are expected to become more intelligent with the kind of meaningful insights that they offer. Teams would be able to predict the probabilities of their deployments failing, and learn how to fix any breaking point that can be a potential cause for a failure. 

In addition to improving automation and issue resolution, AI can also enhance collaboration among DevOps teams. For example, AI can be used to analyze communication patterns among team members and identify areas for improvement. AI can also be used to provide recommendations for improving workflow processes.

Overall, the integration of AI/ML into DevOps has the potential to significantly improve the efficiency and effectiveness of software development and management. However, it is important for organizations to carefully consider the implications of using them and to ensure that it is used ethically and responsibly.

4. More Emphasis on Security

As software becomes increasingly complex and the threat landscape evolves, security will become an increasingly important consideration.  The current state of DevOps shows that most teams have successfully implemented a shift-left approach when it comes to testing and code scans. However, emphasis has to be given to progressing further with a focus on leveraging secure tools and workflows. There is a shift towards platforms that offer Dynamic secrets management and a comprehensive RBAC. Teams are now looking at fully automating private cluster deployments thanks to the secure whitelisted channels that a few of these platforms offer. These and many similar security features help in driving compliance and governance for enterprises in BFSI, Telco, Utility, and other industries. 

The emphasis on security in the way that is enabled by these platforms indirectly helps move towards implementing DevSecOps. The main principle of DevSecOps is the integration of security into the continuous integration and continuous delivery (CI/CD) pipeline.

Overall, the goal of DevSecOps is to improve the security of applications while also allowing for rapid development and deployment. By integrating security into the CI/CD pipeline and promoting collaboration among development, security, and operations teams, organizations can build and deploy more secure applications faster and more efficiently.

5. A Shift Towards Standardizing Deployments & True Automation

There is an emergence of many end-to-end DevOps platforms that are built to be low-code. Additionally, they focus on introducing standardization to deployments; something which has been a major obstacle that prevents teams from scaling and controlling their deployments. Using standardized CI/CD pipelines enables teams to reuse a specific pipeline for deploying microservices that are similar in nature by just tweaking a few parameters where required. This helps tackle bloating up of pipelines and streamlines pipeline management. 

These low-code platforms also help implement true meaningful automation which has long been a key principle in DevOps but its implementation has always been isolated and non-uniform, given the fragmented tools and workflows across teams. This trend is likely to continue in the future with the focus being on true end-to-end automation through DevOps platforms. Automation can help to reduce the time and effort required to build, test, and deploy software, which can increase efficiency and speed up the development process. Post-deployment automation too goes a long way in helping detect downtimes and initiating instant rollbacks to ensure higher application availabilities. 

6. Rise of Hybrid Cloud Environments

Many organizations are moving towards a hybrid cloud model, where some workloads are run on-premises and others are run in the cloud. Requirements also dictate the need for having applications running across multiple cloud regions with many shared resources. This trend is likely to continue in the coming years, and DevOps practices will need to adapt to support not just hybrid cloud deployments but also simplified cross-cluster monitoring, backups, and more. 

Conclusion

It is true that DevOps has become increasingly popular in recent years, with many organizations adopting it to improve the efficiency and effectiveness of their software development and delivery process. By leveraging the latest DevOps trends and technologies, organizations can leverage the full potential of DevOps and focus on delivering high-quality software quickly and reliably.