By Raghav K.
IT operations are highly dependent on automation. Tools like Packer make DevOps automation a lot easier. However, there are new concepts. DevSecOps introduces security in development-to-release cycles, and DataOps introduces the power of analytics into the operational side of DevOps. The next big thing was to utilize AI and machine learning with big data analytics to help automate the system and make it more efficient. This practice is called AIOps.
All these practices zero-in on the concept of automating the process to extract as much value from the pipeline as possible without throwing away the core values of business practice. NoOps pushes the concept even further and introduces a level of automation that completely takes away any human intervention from the entire process.
DevOps is a commonly used term that relates to an efficient software release cycle. It is a prime indicator of collaboration that suggests collaborating between development and operations teams to find a solution. DevOps says everything must grow with the growth cycle of the organization and customers.
Team collaboration doesn’t necessarily define how well the operations or development teams can comprehend the workload associated with each other. The teams might not be deeply indulged in the core workloads of the opposite team and won’t have a full understanding of either development or operations perspective.
It does not matter if your release cycles are infrequent. However, if you release code frequently, you need an automated approach that accelerates software delivery, and that is where DevOps practices fit in perfectly.
NoOps does not mean “no operations whatsoever.” It references a scenario where automation takes care of every aspect of the operations perspective associated with the pipeline. NoOps refers to a situation where an IT environment becomes so automated from the underlying infrastructure using technologies like artificial intelligence (AI), machine learning, data analytics, and effective disaster recovery that there is no need for a dedicated team to manage software in-house.
Alibaba Cloud is working towards an infrastructure that can be managed at a level where O&M automation becomes a key aspect without the frontend noticing what is happening at the backend. Automation has to handle deployment, monitoring, testing, and integration independently. NoOps is a concept that introduces a self-diagnosing, self-healing, and self-sustainable architecture to your SDLC.
The development has increased container utilization since they are critical to the entire NoOps approach. The cloud-native architecture utilizes containers with Kubernetes as the basis of a streamlined and effective approach for application development and delivery. Containers help you deploy services and applications independently. They can also help with automation and with process standardization from build to deployment.
Containers can help you deliver lightweight and portable applications. Containers are self-sufficient and provide a complete platform for the application to run properly and efficiently without worrying about the underlying environment.
The development team will need to build the application, and the application will have the capability to run practically anywhere. NoOps allows developers to shed any worries about how the application will work, deploy, or function. NoOps takes care of the infrastructure-related configurations away from the developers and self-manages the infrastructure to reduce the operational burden related to the application.
Containers make application deployment easier and minimize application conflicts related to multiple environments to improve portability. Kubernetes image files can plug-and-play and run applications without any downtime. Continuous integration and delivery automates the delivery part of the SDLC and does not affect the integration part.
Containers provide high-performance, agility, and operational flexibility to enable cost-saving mechanisms and an effective software delivery approach. Containers can host microservices, which are loosely coupled independent services that make up a larger application. These microservices are highly scalable and provide individual modularization. Alibaba Cloud Auto Scaling further enables the applications to automatically adapt to a changing number of requests efficiently without any outages.
The NoOps platform enables monitoring and operations observability to resolve issues automatically. It is easy for the system to identify issues and initiate fixes with the AIOps’ intelligent alerts, logging, and metric collection.
Every solution that can be implemented to accelerate the build cycle of an application revolves around operations. NoOps is about automating the entire operations process by shaping up the infrastructure that allows seamless and unified operations management and eliminates any human counterparts.
DevOps is a culture; it is a baseline standard that defines the paradigm other practices like AIOps, NoOps, and DataOps are building on. In my opinion, NoOps is like AIOps and DataOps combined and took a step forward to automate at a level where the system becomes hyper self-sustaining. In the end, I hope the concept reaches the masses, and everyone adopts it for a better and accelerated application lifecycle.
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