DATA SHEET 1 Predict and prevent outages with ServiceNow® Predictive AIOps Businesses depend on digital services to engage customers, automate processes, drive innovation, and unlock business insights. IT operations is responsible for delivering these business-critical services and needs to ensure they are always available and responsive. Service downtime can become an enormous challenge. Many IT organizations continue to operate in silos, using multiple tools to monitor the health of individual domains, such as cloud and serverless infrastructure, applications, networks, storage, and more. Operations teams struggle to keep up with the volume of events and logs. And since the data is complex, it takes much longer to triage and get to the root cause of the problem. The ServiceNow solution ServiceNow® Predictive AIOps uses AI to predict issues, prevent disruption, and automate remedial actions. Instead of dealing with innumerable events, you get actionable alerts, helping identify and resolve service issues before users are impacted. By applying Generative AI, teams see complex alerts in a simple text, aided with a description of the problem and insights. Predictive AIOps analyzes logs and metrics in a new way to detect application behavior that traditional monitoring techniques do not address since they mainly deal with grouping for preprogrammed failure scenarios. Predictive AIOps uses advanced machine learning and analytics techniques to proactively uncover and resolve complex, unforeseen service issues, including in evolving virtualized and cloud environments. In addition to traditional monitoring, ServiceNow Cloud Observability helps ingest cloud-native telemetry, enhancing the operations team’s ability to monitor service issues for the modern and distributed stack. Benefits Predict and prevent service outages Identify potential service issues before they cause service outages and degradations that impact your business. Fix issues faster Leverage machine learning and automation to reduce event noise, transform events into actionable alerts, pinpoint issues, diagnose likely root causes, identify potential fixes, and automate remediation. Focus on what matters Prioritize resolution of issues based on their service and business impact. Lower cost and raise productivity Resolve service issues with an intuitive. intelligent single pane of glass that makes it easier to proactively identify, diagnose, and resolve service issues. Get Generative AI to help Leverage Now Assist for ITOM reduces the time to triage alerts with a simplified summary and analysis, enabling even the L1 agents to understand the issue. Leverage existing investment Consolidate events from multiple monitoring tools using a wide range of out-of-the-box connectors and flexible, easy-to- use custom integration framework. ServiceNow Predictive AIOps Workflow Source: Accenture case study Source: Korber customer story Source: Knowledge 2023 DATA SHEET Top capabilities of Predictive AIOps • Event Management processes events, tags, and metrics to reduce noise. It also consolidates events from your existing monitoring tools, using AIOps techniques to turn a flood of these events into a small number of meaningful alerts. This reduces event volumes by up to 99%. If you don’t have a CMDB yet, the Tag- based Alert Clustering technique helps correlate alerts based on the tags. When Event Management is used in conjunction with Service Mapping, you can see the service impact of these alerts, providing interactive service maps that make it easy to identify and prioritize service issues. It also carries out automated root cause analysis, showing which CIs are the most probable cause of a service issue and associated confidence scores. This significantly reduces the time needed to diagnose service outages and degradations. • Log Analysis and Anomaly Detection identifies potential service issues before they cause service outages and degradations. It uses machine learning to identify normal operating patterns in logs, traces, and metrics—for example, specific log sequences or correlations between log field values over time. This includes correlating logs across different sources, such as a load balancer and its connected web servers. You can stream logs from Azure Monitor, Amazon S3, Amazon CloudWatch, Kafka, REST API, etc. It then looks for antipatterns— disruptions in normal operational behavior—raising an alert against a corresponding CI when a significant antipattern is detected. This allows you to respond early and prevent service issues rather than reacting once they occur. And because Log Analysis uses unsupervised learning, it automatically uncovers complex, distributed patterns without human intervention, including unanticipated patterns not foreseen by your IT operations team. In addition, there’s an intuitive dashboard to visualize and track log alerts and anomalies. • Metric Analytics collects raw metrics from the ServiceNow® Agent Client Collector and other monitoring tools, raising events against CIs when there is a performance anomaly. This allows you to identify service degradations that can lead to service outages. Predictive AIOps uses machine learning to model normal metric behavior automatically and set adaptive thresholds, eliminating the significant effort needed to manually set thousands of thresholds—although these can be set manually if required. It also allows you to score anomalies based on how likely they are to lead to a service outage and provides heat maps and other tools that allow you to visualize and analyze metric data. Prioritize service health & resilience Import telemetry from APM tools to define error budgets, service level indicators, and objectives (SLI/SLO). Policy-driven metrics improve service reliability tremendously. Drive lower MTTRs with on-call scheduling Empower teams to self-manage their on-call schedules (e.g., timing, frequency, members). SRE teams can self-govern escalation triggers and policies Correlate alerts without needing a CMDB Tag-based alert correlation lets you group alerts based on similar alerts without needing a CMDB. The tags are derived from alert information from monitoring tools, further reducing event noise. This feature provides rapid time to value since it’s helpful even if you haven’t discovered your IT infrastructure yet. Instantly see and investigate service issues Predictive AIOps comes with Operator Workspace that gives you a consolidated view of your business services. Prioritized service health issues are highlighted on an intuitive, color- coded service health dashboard, making it easy to identify issues at a glance. Prioritized alerts with ML-driven correlation Express List provides an intuitive and fast way to visualize critical alerts. It offers alert correlation based on machine learning. You can also provide feedback on the usefulness of these alert groups and even add or delete alerts. This feedback can automatically adjust the way alert grouping works in the future.Express List with Link View 2 DATA SHEET Resolve service issues faster with automatic remediation You can configure Predictive AIOps to respond automatically to alerts, helping you to resolve service issues faster. For example, you can use Flow Designer and IntegrationHub to create remediation actions called a Playbook, such as retrieving log files, freeing up disk space, restarting a service, or attaching a knowledgebase article to the alert. These actions are triggered when an alert meets specific criteria that you define, or you can manually initiate these actions simply by right- clicking on the corresponding CI. You can also trigger tasks such as auto-closing an alert or creating incidents, change requests, security incidents, field service work orders, and customer service cases. 3 SN_DataSheet_TEMPLATE_JAN_2022 Express List with Now Assist for ITOM Now Assist for IT Operations Management Now Assist for ITOM tackles this issue head-on. It uses the power of Generative AI to replace cryptic alert descriptions with simplified, plain-language summaries that let operators quickly understand what an alert indicates. It also provides an intelligent alert analysis, drawing on collective knowledge across the ServiceNow ITOM customer base to identify which issues may have caused the alert and suggest the next steps. Operators can easily access this information directly from the Express List by choosing both group and individual alerts, putting intelligent insights at their fingertips. 96% Events to alert reduction 96% Increase in productivity We’re leveraging the AIOps capabilities of the ServiceNow platform to predict/prevent issues and transform into a self-healing state. ServiceNow Infrastructure and Operations Source: ServiceNow Digital Technology customer story Intuitive alert triaging at your fingertips Express List provides a faster path to seeing alert details, including the issue, grouping, tags, root cause, and application map. Having this information in a single place helps the operations team quickly investigate issues, drill into details, create incidents, and also take remediation actions. The advanced rule enrichment n is also available to take specific actions such as applying business context, tags, correlation, and grouping preferences. DATA SHEET 3 SN_DataSheet_TEMPLATE_JAN_2022 servicenow.com/ITOM A superior AIOps experience Express List: The Express List is a game-changer for triaging issues. It provides a consolidated view where users can efficiently triage alerts, correlate alerts, timeline view, see probable root causes, visualize link view maps, and simplify alert text using Now Assist. With real-time updates, dynamic filtering, and an intuitive preview pane, users can stay on top of their alert workflows and take immediate action with unparalleled ease and speed. Integration Launchpad: With the Integration Launchpad, users can access a hub of seamless connections to various external tools and services.