How AIOps help DevOps?.

Oct 5, 2021. By Anil Abraham Kuriakose

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How AIOps help DevOps?

In today's world, digitization is the main objective of every IT team. Due to this, the IT teams should manage their IT environment with regular changes without any IT system downtime. The key challenge here is the productivity and agility of people building and managing the IT systems are very low due to the lack of the right toolsets. This creates a very serious consequence to the business's operations. When your business services malfunction, you start to lose your customers, and your revenue drops. When IT teams are fire-fighting to fixing emergencies, their agility suffers, and innovation shrinks. But the current business demands a seamless IT operation to grow, compete and lead.

Historically, IT organizations grew along with new technology adoption regularly. But, the advent of cloud computing led to a world of microservices and serverless applications. Due to this, IT organizations generate too much unstructured IT data for ITOps teams to monitor and understand unknown problems manually and legacy systems and data. This situation creates a demand for a technology that can analyze and interpret meaningful inferences from all unstructured data available from the modern IT environment. Everyone agrees that Artificial Intelligence (AI) is the technology that can streamline the IT operations and help ITOps teams to improve observability, quickly detect and resolve issues, avoid outages, and regain control over entire systems.

AIOps vs. DevOps: The Difference
DevOps is the best IT system development and operations methodology that increases the speed of development and deployment. It is a set of specific practices that improves the activities of IT teams. Using DevOps principles, the IT teams can work together very efficiently. The DevOps approach helps the development and operations teams improve collaboration with a shared passion for achieving organizational goals. On the other hand, AIOps is a multi-layered approach to automating IT operations and AI model-driven auto-remediation. The automated system improves the DevOps-driven IT transformation and enhances the agility of the organization. The importance of AIOps will increase with modern cloud-native enterprise applications running between multiple cloud providers and required to be monitored with real-time observability.

How Does AIOps Enhance DevOps? 1. AIOps improves decision-making capability AIOps brings key Artificial Intelligence (AI) based techniques to IT operations, including anomaly detection, unknown pattern matching, predictive observability, historical and causal analysis, incident recognition, and root cause analysis. These advanced approaches help the IT management with better decision-making capability purely driven by data, insights, and guided responses. Also, this eliminates human error due to the volume of data and noises created due to data volume. In addition to the analytics benefits, cognitive automation allows your staff to focus on resolution instead of detection and save the cost of operations.

2. AIOps reduces the meantime to repair through better observability Adopting AIOps improves business agility through a high level of observability with its intelligent management layers. Using advanced AI model-driven incident recognition helps to reduce the Mean Time to Detect (MTTD) to a great extend. In addition, the Deep Reinforcement Learning-driven automation enables the IT operations team to auto-remediate incidents and reduce the MTTR (Mean Time to Repair. With the faster MTTD and MTTR, the IT operations team can eliminate fire-fighting and respond quickly to production incidents.

3. AIOps enables predictive DevOps DevOps adoption improves the organization's agility, but frequent releases reduce the quality of the services due to defects and broken features. But these service degradations should be resolved before the service outage, and it is required to have predictive analytics to pinpoint these issues much before these are incurred. That's how AIOps driven predictive analytics helps in reducing the frequent service degradation.

4. AIOps enables automated IT operations Low touch IT operations is an idea that the software environment can be automated to a great extend that there's a limited need for an operations team to manage it. The highly automated situation helps the engineering team focus on more strategic development activities instead of mundane operational ones. Even the best-automated DevOps environment requires human oversight and intervention when things go wrong, or something needs to be updated.

5. AIOps streamlines the collaboration The AIOps provides greater analytics and inferences that facilitate collaboration within the IT organization and between IT and other business departments. The AI-driven business value dashboards help the IT team communicate effectively about the business-oriented metrics across the board and help justify the IT investments in terms of business value. For IT organizations, the AIOps platforms make teamwork more productive with advanced and predictive analytics. Also, AIOps helps IT organizations in situations where IT operators are geographically separated; the AIOps platform facilitates remote collaboration with streamlined IT Operations.

AIOps: A Key Element for Effective DevOps In the future, the only way to manage the technology that had been created yesterday, creating today, and will be created by tomorrow by DevOps teams is with AI. AI-based IT will free up humans resources to focus on strategic activities that drive maximum profitability for your business. To learn more about AIOps, please visit our AIOps Platform Page

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