Today’s IT Under Pressure:
IT operations teams have been tasked to deal with exponential data growth, hybridization, a myriad of operational tools, countless metrics, ever increasing false alert volume, security threats and topping them off with budget cuts, growing customer demands, stringent SLA requirements. All this puts ITOps teams in a tough spot. However, these same paradigm shifts have also led to in drastic increase in monitored assets, numerous operational tools, and exponential growth of operational data. As a result, modern IT organizations are facing challenges in these three key areas:
- Ever Increasing Alert and Event Noise
- Complex and Lengthy IT Problem Resolution Process
- Inability to effectively predict and prevent IT service degradations or outages.
Path to Modern IT – Proactive, Predictive & Autonomous
Though the details of the path may look different for each organization, below illustration is a common path with respect to outcomes. The essence is in adoption of a modern AIOps platform that has both in-built data collection as well as rich 3rd party integrations to ensure access to all operational data. Once the data access requirement is put in place, then advanced AI/ML algorithms and analytics are applied to address the key challenges mentioned earlier. The solutions for the three Focus areas can be summarized as below
- Alert Noise Reduction & Correlation
Fine granular controls and advanced clustering algorithms are used to eliminate noise and group multiple alerts into actionable incidents along with classification for easy prioritization and routing to the appropriate teams.
- Automated Incident Response
NOC/SOC and serviced desk teams are provided with contextual insights for quick diagnosis and access to relevant tools for immediate remediation. Overtime, its self-learning capabilities allow the system to even auto resolve the incidents.
- Proactive Situation and Stack Monitoring
Operation teams can select their critical assets/services for proactive monitoring and gain continuous visibility of key health and performance data across the stack. Apart from that, predictive/forecasting algorithms will provide insights into future alerts/incidents.