Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Microsoft 365 services are productive and reliable, but data loss can occur for various reasons. For example, a user may accidentally delete data or a ransomware infection may spread from local computers whose folders are synchronized with the cloud storage. Thus, Microsoft 365 backup is important for data protection and business continuity. With backups, you can recover the needed data and ensure uninterrupted workflows.

Here’s the reality most security teams are already living: over 80% of employees are using unapproved AI tools at work, and nearly half are actively hiding it from IT. The question facing every organization is no longer whether to adopt artificial intelligence — it’s how to secure the sensitive data flowing into it every single day. This is the governance gap.

The era of human-centric API consumption is officially ending. Over the past year, enterprises have rapidly transitioned from simply experimenting with Generative AI to deploying autonomous AI agents that drive core business operations. These agents act as digital employees. They utilize Large Language Models (LLMs) for reasoning, Model Context Protocol (MCP) servers for connectivity, and internal APIs for execution. This evolution has fundamentally altered the enterprise attack surface.

Opti9 recently announced it has been approved as an authorized reseller for Anthropic models through Amazon Bedrock, further strengthening its ability to deliver secure, enterprise-grade AI solutions on Amazon Web Services (AWS). In October, AWS enabled its Solution Provider Partners to resell Amazon Bedrock, a fully managed service that provides access to a wide range of leading foundation models from top providers.

The debate over lift and shift versus refactoring is one of the most persistent in cloud migration planning. It’s also frequently framed as a binary choice when it shouldn’t be. Most organizations will do both — the question is which approach applies to which workload, and in what order. Getting this decision wrong is expensive. Over-refactoring adds months to migration timelines and cost that’s difficult to justify.

For years, AI was the defender’s advantage. In the last 30 days, that narrative inverted — AI is now leaking data, generating malware, refusing to shut down, and erasing billions in market value. AI-enabled attacks rose 89% year-over-year. A single model leak wiped $14.5 billion from markets in one day. An AI agent compromised 600+ firewalls across 55 countries without a human operator. And another AI agent refused to shut down when commanded.

Your CNAPP shows green across every posture check—hardened clusters, compliant configurations, no critical CVEs—but when your board asks "Are our AI agents safe in production?", you cannot answer with confidence because your tools see the infrastructure, not what the agents actually do at runtime.