Artificial Intelligence for IT Operations
Harness the power of automation and analytics to become more agile, proactive, and predictive in your IT operations.
IT is faced with more apps, systems and platforms than ever to keep up and running in peak condition. Any compromised link in the chain can have a domino effect costing the business millions of dollars in lost revenue or employee productivity.
Today’s IT operations needs to be equipped with better and more complete diagnostic data, machine learning and automation capabilities, and innovative analytics to pivot and visualize data for comprehensive app profiling and faster troubleshooting.
Frequent releases, transient cloud resources, numerous tools and platforms, and thousands of containers to manage and orchestrate—the complexity of the modern app environment is magnified by constant change.
Modern cloud-native environments generate 18x more monitoring and observability data than traditional monolithic apps—but legacy APM is not up to the task of collecting, storing, and processing this volume of (big) data.
IT is constantly challenged to do more with less. Automation and analytics help relieve the human workload and aid speedy problem resolution, freeing up valuable time and expertise for strategic projects.
Prioritize the development efforts that will have the most overall business impact by identifying the backend components implicated in the most important transactions, by processing time, volume or financial value. Performance Graph maps crucial dependencies and helps you prioritize troubleshooting and optimization projects based on business relevance and impact.
Be proactive with automated anomaly detection that alerts you to unusual performance behavior before end user SLAs are breached. Surface unsuspected issues with pattern recognition to identify groups of related transactions and metrics, and quickly find the needle in the haystack.
Automatically sift through common attributes across overall application performance issues or issues with particular user activities to narrow down the field of potential culprits. Understand user satisfaction and set thresholds based on performance baselines or aggregate scoring systems (e.g., Apdex or MOS scores).
Save time by automating repetitive tasks, and empower lower level teams to resolves issues without escalating to more expensive resources. Build a library of remediation actions for end user device-based problems and maintain a complete log of the remedial actions taken, their success or failure, and who implemented them.
