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Description
A growing number of companies are shifting their operations to cloud platforms to enhance their digital transformation efforts. This transition necessitates a novel security solution that offers centralized oversight and administration for workloads within these cloud environments. AhnLab CPP serves as a cohesive cloud workload protection platform that emphasizes delivering tailored security, streamlined management, and adaptability for workloads across hybrid settings. It ensures extensive visibility and straightforward management for workloads operating on both on-premise and cloud servers, including AWS and Azure environments. The platform facilitates effortless operation through a single web-based management interface. With its modular CPP management, it allows for flexible configurations based on specific business needs. Additionally, it helps reduce costs by permitting targeted installation and utilization of security solutions. Moreover, it offers real-time malware scanning capabilities for both Windows and Linux servers while maintaining minimal resource and performance impact, ensuring that businesses can operate efficiently in a secure environment. Ultimately, AhnLab CPP represents a critical tool for organizations striving to safeguard their cloud workloads while embracing the advantages of digital innovation.
Description
Veritas Alta™ consolidates a wide range of crucial data services into one powerful platform. Designed specifically for contemporary workloads, this advanced suite of features is engineered to ensure top-notch security and performance at scale across a variety of environments, whether they be hybrid, multi-cloud, public, private, edge, or on-premises. If you handle data within the cloud, embracing Veritas Alta is essential. Experience unparalleled resiliency through automated, intelligent recovery and gain comprehensive visibility. Maintain performance, ensure availability, and enable seamless cross-cloud mobility for your business that never sleeps. Capture and visualize all relevant data, archive it anywhere you choose, and uncover what truly matters. Our adaptable, cloud-native framework integrates artificial intelligence, automation, and elasticity, providing the most economical, resilient, and self-defending cloud data protection on the market. For the utmost in cloud governance, Veritas Alta not only grants visibility across your entire operational landscape but also minimizes the attack surface, enhancing overall security. This holistic approach ensures that businesses can confidently navigate the complexities of modern data management.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Microsoft Azure
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
AhnLab
Country
South Korea
Website
global.ahnlab.com/site/product/productSubDetail.do
Vendor Details
Company Name
Veritas
Country
United States
Website
www.veritas.com/alta
Product Features
Cloud Workload Protection
Anomaly Detection
Asset Discovery
Cloud Gap Analysis
Cloud Registry
Data Loss Prevention (DLP)
Data Security
Governance
Logging & Reporting
Machine Learning
Security Audit
Workload Diversity
Product Features
Archiving
Access Control
Data Deduplication
Document Management
Email Archiving
Multimedia Archiving
Retention Management
Storage Management
Version Control
Web Archiving
eDiscovery
eDiscovery
Case Analytics
Compliance Management
Discussion Threads
Document Indexing
Document Tracking
Full Text Extraction
Keyword Search
Metadata Extraction
Topic Clustering