Kloudfuse 3.5 Unifies AI and Traditional Observability While Achieving Federal Security Compliance

One platform for complete visibility, control, and AI-ready operations BENGALURU, India, December 03, 2025 - As enterprises race to deploy AI applications, they're discovering that their observability infrastructure can't keep pace. Traditional monitoring tools built for cloud-native workloads don't understand LLM behavior, token consumption, or prompt-response patterns. Adding AI-specific monitoring creates new silos. Observability costs spiral unpredictably, and compliance becomes a maze of fragmented data policies across disconnected platforms. Kloudfuse today launched Kloudfuse 3.5 to solve this fragmentation. The unified observability platform introduces Model Context Protocol (MCP) integration for natural language queries, FIPS 140-2/3 validated cryptographic modules for regulated industries, and comprehensive platform engineering controls, delivering complete visibility across traditional and AI workloads without separate tools or unpredictable costs. "The observability industry created this problem by treating every new technology as a separate product," said Ashish Hanwadikar, CTO and Co-Founder of Kloudfuse. "We took the opposite approach: integrate LLM telemetry directly into APM using OpenTelemetry standards. Platform teams get the same operational control over AI workloads as traditional services. Our MCP server unifies signals across metrics, logs, traces, and events for comprehensive insights through natural language queries, one platform, one instrumentation approach, predictable costs." Since launching Kloudfuse 3.0 in November 2024, Kloudfuse has shipped over 50 major capabilities, proving that unified observability doesn't require fragmented tools, vendor lock-in, or choosing between AI capabilities and cost control. AI-Native Observability: Natural Language Queries Meet LLM Monitoring Kloudfuse 3.5 introduces natural language access to observability data through the Model Context Protocol. Instead of constructing complex queries or navigating multiple dashboards, engineers can ask questions in plain language: "Show me services with elevated error rates in the last hour," or "Which deployments caused memory spikes today?" The MCP server translates these requests into FuseQL, queries across metrics, logs, and traces, and returns comprehensive insights linking application behavior to infrastructure impact. Platform teams can leverage this for automated workflows, building agents that trigger incident responses, analyze capacity trends, or identify cost anomalies. The standards-based implementation works across LLM providers, avoiding vendor lock-in at the AI layer just as OpenTelemetry avoids it at the observability layer. Kloudfuse 3.5 also integrates LLM monitoring directly into APM.. It tracks prompt and completion tokens across providers, monitors model latency and error rates, and correlates AI requests with backend service performance, all through unified OpenTelemetry instrumentation. Teams deploying AI applications get full-stack visibility without adding separate monitoring tools or duplicate agents. Federal Security Certifications for Regulated Industries "For enterprises in regulated sectors, FIPS validation isn't optional, it's contractually required," said Pankaj Thakkar, CEO and Co-Founder of Kloudfuse. "Major observability vendors haven't pursued these certifications, leaving enterprises choosing between comprehensive monitoring and compliance requirements. Kloudfuse 3.5 eliminates that trade-off." Kloudfuse 3.5 implements FIPS 140-2/3 validated cryptographic modules across data ingestion, storage, queries, and API access. Building on FIPS validation, the platform establishes a clear FedRAMP authorization pathway with NIST 800-53 security controls and automated compliance reporting. Combined with VPC deployment, organizations retain complete data sovereignty, as observability data never leaves customer infrastructure. "At Zscaler's scale, observability must be both robust and compliant," said Kishore Thakur, Senior Director, Cloud Platform Engineering at Zscaler. "Kloudfuse handles our massive data volumes while meeting FIPS 140-2 compliance and FedRAMP pathway requirements. For enterprises with strict compliance needs, this combination of flexibility, security, and innovation is exceptional." Data Governance: Managing Access and Compliance Enterprise data governance requires more than encryption. It demands control over who accesses what data, how long it's retained, and how changes are tracked. Kloudfuse 3.5 delivers comprehensive data governance across all telemetry streams with data scrubbing that lets teams preview records before deletion, apply filters targeting specific data, and maintain audit trails for GDPR, HIPAA, and internal compliance requirements. Stream-specific RBAC and identity management implement granular access control through labels and tags. Engineering teams access only their service telemetry. Security