Gain visibility, manage health, and optimize digital assets and services with AIOps.
The Artificial intelligence for IT Operation is called AIOps. AIOps is the NextGen and future of IT Operation. AIOps integrates advance algorithms and AI for analyzing the raw data from the numerous sources and provide meaningful information to speed service delivery, increase IT efficiency and deliver an exceptional user experience.
Going forward, AIOps will play a key role in enabling new efficiency for IT Ops teams. It will also make practical the adoption of complex next-generation technologies that cannot be managed successfully using tradition solutions.
Key drivers for AIOps
With massive growth of AI and wider adoption of Digital Economy, the traditional IT management techniques are becoming obsolete to manage increasing complexity and responding to the changes spontaneously.
AIOps addresses the challenges of speed, scale and complexity that todays’ leaders are facing. Here are the main key drivers for AIOps adoption.
Data Analysis and quick decisions – Today’s IT infrastructure and APM landscape generates massive amount of data that human can’t parse and derive meaningful insights. Here AIOps can be used to consume the data, develop intelligence around and provide meaningful information around it.
Faster Response Time – Growing the complexity of the enterprise tools landscape and massive data increases the volumes of alarms and services tickets. Manually it’s very difficult to keep eyes on all the incoming and respond fast.
Predictive Maintenance – Proactively predicting the issue and acting before it hits the service delivery is the key priority for any service delivery to deliver exceptional user experience. And, AIOps can play a vital role by leveraging its machine learning and advance analytics.
Enable the culture of self-service – With intelligent automation and right real-time information at hand, AIOps foster the culture of do it yourself. Its holds the owner of code, infrastructure and support team accountable for delivering the services faster, cheaper and better.
Use Cases
Proactive Bottleneck Identification – AIOps can be used to predict the serious bottleneck and avoid the service disruption by leveraging huge data and analytics.
Self-Healing – AIOps can be used to avoid service disruption by remediating issues automatically without any manual intervention. Self-healing is a very powerful feature of AIOps and can be used to solve complex IT operations like performance, monitoring, configuration by proactively detecting the problems and remediating before its impact the services.
Root Cause Analysis – AIOps can be used to analyze log files, help desk emails, incident management tools and incident logs to analyze the root cause of the problem and find the relevant remediation. This is really complex problem to be analyze and reach to a conclusion by the human.
Alarm Monitoring – With growing IT complexity and increasing devices with the realm of the connected world, it’s very difficult for human to monitor the alarms and deliver services at the expected speed. Hence, AIOps can be used to monitor the real time alarms raised by different devices (servers, firewalls), analyze the nature of the problem, engage the right team, and if require remediate the issue without any manual intervention.
Intelligent Automation – AIOps can help the IT Operation team to become more productive by leveraging RPA bots and Chatbots. RPA can be used to automate repetitive, mundane and highly transactional activities, wherein, ChatBots can enable human like conversation and bridge communication gap.
Company : Rede Consulting Services
Contact : info@rede-consulting.com
Website : www.rede-consulting.com
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