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Is AIOps the future of DevOps?
Technology enhances our lives by improving quality and automating mundane chores. Likewise, artificial intelligence (AI) gives DevOps a boost. AIOps, as we call it, will be a game-changer in the DevOps world by increasing response speed, adding business context, and raising DevOps effectiveness. For instance, DevOps firms at the forefront of technology adoption have been urged to pursue a self-provisioning infrastructure for application deployment.
DevOps has altered how development and IT operations teams work to build and deploy new digital services, apps, features, and updates since its introduction in the late 2000s. DevOps has contributed to streamlining the production process, resulting in more efficient workflows and reliable service. However, many teams faced a persistent obstacle as services continually evolved or received new features and updates.
This article will examine the evolution of AIOps and its implications for the future of DevOps teams.
What Path Has Led Us Here?
DevOps was initially conceived to foster a more collaborative work environment between developers and IT operations. In a conventional production team environment, developers worked independently from operations. It was common for developers to hand off their code to a central IT team and forget about it. With DevOps, product ownership is shared, and teams collaborate across silos to create a more streamlined and effective workflow. With DevOps, production teams could deploy new services and upgrades more quickly. At the same time, developers could focus on designing innovative new features without having to deal with continual escalations.
Even though DevOps changed the game for production and deployment operations, teams still faced an additional obstacle. The SREs (Site Reliability Engineers) and DevOps teams were responsible for detecting and resolving incidents. This necessitated sifting through many alerts to determine where incidents occur inside the service or infrastructure. Teams must also comprehend the many linkages between certain data pieces and identify which teams or individuals must be notified to address an issue.
Regarding DevOps, AI technology and tools have helped increase automation and productivity. For example, AIOps helped IT operations teams overcome the problem of incident detection and resolution by automating those procedures to detect and resolve incidents in real-time – and even preventing their occurrence.
How AIOps Benefit DevOps Teams?
AIOps and DevOps interact to enable development, production, and operations teams to collaborate more effectively, work more efficiently, and maintain a customer-centric focus. AIOps can support DevOps teams in several significant ways, including:
Permit operators to work more efficiently. AIOps emphasizes enhancing and constructing a scalable and dependable service rather than simply ensuring its functionality.
- Smart noise reduction.
By integrating AI into your infrastructure, operations are expedited as machine learning algorithms adapt to your team’s individual needs and surroundings, combining alarms and assisting in sifting through the noise to identify meaningful warnings.
- Learn from previous and related occurrences.
As incidents are identified and resolved, AIOps learn from these occurrences and can identify trends based on past incidents. By gaining knowledge from these incidents over time, AIOps can recognize anomalies that depart from known patterns and forecast future incidents.
- Automate routine corrective actions.
AIOps enables autonomous remediation by learning from and adapting to recognize and address events. This means that AIOps can trigger bespoke actions to do remediation and frequently prevent this from occurring.
What does AIOps Offer?
AIOps is ideal for DevOps teams that wish to take advantage of the numerous advantages of artificial intelligence and machine learning. With proactive problem detection and automated remediation, IT operations teams are free to concentrate on enhancing services to deliver an ideal user experience to customers. In addition, AIOps aids in ensuring service dependability without requiring ongoing scaling of operations employees to maintain product functionality. The focus is now on innovation and creativity, while artificial intelligence and machine learning increase incident response and reduce unscheduled downtime.
Integrating AIOps with DevOps
AIOps readily connect with numerous existing tools and processes, enabling teams to maximize the value of the multiple data streams provided by various applications and infrastructures. Furthermore, AIOps digests and analyzes these different data points to comprehend the relationships between them and effectively monitor the system to ensure it is always functioning correctly.
Lastly, minimizing burnout is one of the most significant advantages of integrating AIOps and automation into your operations. Teams can now focus on what they do best, being creative and innovative, without continually resolving emergencies. When operators solely focus on problem resolution, they are more prone to experience burnout. With AIOps’ ability to automate these operations, teams can devote more time to enhancing a product or service and providing.
Ready to start integrating AIOps for your DevOps team? iVedha is ready to help our clients with this shift by providing them with tools, technologies, and innovations that bring scalability, speed, and quality.
Contact iVedha to learn more about how AIOps can automate your team’s incident detection and resolution processes.