The proliferation of endpoints in today’s enterprises is outpacing the ability of IT operations and security teams to cost-effectively manage increasingly complex environments.
Already stretched thin, teams face the daunting task of securing vast IT estates with siloed tools, stale data, and other hindrances that create the perfect “imperfect” environment for vulnerabilities. And simply adding yet another bolted-on component to an existing patchwork quilt of technology solutions is a recipe for failure.
While automation initiatives expand in multiple areas, achieving desired outcomes frequently falls short of aspirations. Regarding threat detection and response, for example, a SANS Institute survey revealed that “64% of organizations have integrated automated response mechanisms, but only 16% have fully automated processes.”
The burgeoning fragmentation of data streams and networks is a major hindrance preventing IT teams from seeing everything in their environments, which further complicates efforts to accelerate artificial intelligence (AI), machine learning (ML), and automation of processes and practices.
To realize the full benefits of AI and ML, including overcoming staffing and budget limitations, IT operations and security teams must start with refocusing on high cyber hygiene standards that result in greater efficiency and reduced vulnerabilities – the fundamentals of endpoint visibility and control, regardless of the environment’s scale.
A new approach to endpoint management and security
Autonomous endpoint management (AEM) is the next evolution in endpoint management and security, leveraging:
- Real-time cloud intelligence to measure and analyze even the smallest effect of change to confidently predict the impact of endpoint change in real time.
- Automation and orchestration that scales and extends the value of precious expertise.
- Deployment templates and rings to ensure disruptions are minimized by rolling out endpoint change to match the rhythm of the business.
AEM has the potential to enable reliable AI and ML implementation and usage by providing a foundation of real-time insights from millions of data points, instantly analyzing sensor trends and usage patterns across endpoints. It will deliver prioritized, tailored recommendations to IT teams and automate changes – safely, with a centralized governance component.
Unifying data streams and increasing visibility will connect security and IT operations teams to ensure everyone is seeing and leveraging the same data. Successfully implemented, AEM will break down silos by providing a converged single source of truth both sides of the organization can trust.
Instead of chasing countless false alarms, those teams will gain instant visibility into critical issues on enterprise endpoints and oversee automated remediations to address them. Tested automations will then be iterated into playbooks that can be extended throughout the organization.
The implementation of AEM will bolster operational resilience and avoid disruptions, continuously monitor and automate compliance checks, and enhance an organization’s security posture by proactively identifying, prioritizing, and remediating endpoint risks.
Organizations hoping to realize the full benefits of AI and ML should look to AEM and its ability to foster IT resiliency and reliability, reduce risk, and provide IT and security teams with the newfound ability to confidently implement AI and ML that will solve organizational problems – instead of contributing to them.
For more insight into AEM, visit www.tanium.com/autonomous-endpoint-management.
