The proliferation of storage facilities in today’s businesses is exceeding the capacity of IT operations and security teams to cost-effectively manage an increasingly complex environment.
Already stretched thin, teams are faced with the daunting task of protecting large IT environments with siled tools, old data, and other barriers that create an “incomplete” risk environment. And simply adding another bolted part to the patchwork quilt of technical solutions is a recipe for failure.
While automation programs are growing in many areas, achieving the desired results often falls short of expectations. Regarding threat detection and response, for example, a SANS Institute survey revealed that “64 percent of organizations have integrated automated response mechanisms, but only 16 percent have fully automated processes.”
The increasing fragmentation of data streams and networks is a major obstacle preventing IT teams from seeing everything in their environment, further complicating efforts to accelerate artificial intelligence (AI), machine learning (ML), and automation of processes and procedures.
To reap the full benefits of AI and ML, including overcoming staffing and budget constraints, IT operations and security teams must begin by refocusing on high standards of cyber hygiene that lead to greater efficiency and reduced risk – the foundations of endpoint visibility and control, regardless of whether natural scale.
A new approach to storage management and security
Autonomous Endpoint Management (AEM) is the next evolution in endpoint management and security, achieving:
- Real-time cloud intelligence to measure and analyze even the smallest impact of a change to confidently predict the impact of an endpoint change in real time.
- Automation and orchestration that scale and extend the value of valuable technology.
- Deployment templates and rings ensure that disruption is minimized by rolling out endpoint change to match the rhythm of the business.
AEM has the potential to enable reliable implementation and use of AI and ML by providing a real-time data base from millions of data points, quickly analyzing trends in sensors and usage patterns across all data points. It will deliver valuable, tailored recommendations to IT teams and make changes automatically – securely, with a centralized management component.
Unifying data streams and increasing visibility will connect security and IT operations teams to ensure that everyone sees and uses the same data. Implemented effectively, AEM will break down silos by providing a single source of transformed truth that both sides of the organization can rely on.
Instead of chasing dozens of false alarms, those teams will gain immediate visibility into critical issues on business endpoints and oversee automated fixes to address them. Tested defaults will then be replicated in playbooks that can be extended across the organization.
An AEM implementation will strengthen operational resilience and prevent disruptions, continuously monitor and automate compliance checks, and improve an organization’s security posture by identifying, prioritizing, and remediating endpoint risks.
Organizations hoping to reap the full benefits of AI and ML should look to AEM and its ability to drive IT resilience and reliability, reduce risk, and empower IT and security teams to confidently use AI and ML to solve organizational problems – instead of contributing to them.
For more information on AEM, visit www.tanium.com/autonomous-endpoint-management.
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