Kloudfuse 4.0 delivers AI-governed observability and scalable workload isolation
Kloudfuse has announced the general availability of Kloudfuse 4.0. The release helps enterprises meet rising compliance requirements, adopt AI-driven observability with production-grade governance, and scale their observability infrastructure without platform bottlenecks, while keeping every byte of telemetry data inside their own cloud environment.
Kloudfuse 4.0 addresses three converging pressures: the FIPS 140-2 sunset on September 22, 2026, after which NIST will move all FIPS 140-2 certificates to the Historical List, the enterprise adoption of AI agents that query production systems without adequate governance, and the operational demand for observability platforms that scale like the infrastructure they monitor.
“Enterprise buyers should not have to choose between strong security and operational simplicity. We built Kloudfuse 4.0 so that customers start with a security posture that meets the expectations of regulated environments, without being forced into a separate product or a more complex deployment model. That means faster security reviews, broader deployment confidence, and a platform organizations can standardize on across both commercial and federal workloads,” said Pankaj Thakkar, CEO, Kloudfuse.
Enterprise MCP server
The Kloudfuse MCP Server gives AI agents governed, natural-language access to production observability data across metrics, logs, traces, profiling, RUM, and APM. Every query is authenticated to a user identity. A query safety layer rejects unscoped or resource-intensive queries before execution. Every interaction is audit-logged. The server is centrally managed as an enterprise service, not a local tool on individual developer machines.
Kloudfuse 4.0 introduces workload isolation, allowing platform teams to scale ingestion, query, and control plane independently based on actual demand. Multi-rollup resolution eliminates recording rules by computing long-range and SLO metrics at query time from raw data. The Metrics Cardinality Explorer surfaces exactly which label combinations drive storage cost before the bill arrives.
“Ingestion, query, and control plane workloads do not behave the same way, so they should not be forced to scale the same way. Treating them as shared compute creates architectural debt that compounds with every new service and every increase in telemetry volume. Kloudfuse 4.0 introduces workload isolation so each layer can be tuned and scaled independently, improving both efficiency and resilience at enterprise scale,” said Ashish Hanwadikar, CTO, Kloudfuse.
“At our scale, reliability depends on how quickly teams can identify issues, understand service dependencies, and take action with confidence. Kloudfuse has helped simplify that by giving our teams a more unified view of production behavior across the platform. With Kloudfuse 4.0’s workload isolation, we can also scale observability infrastructure more deliberately as demand grows, without creating new operational bottlenecks. That combination strengthens both reliability execution and long-term resilience.” Michael Kuperman, Chief Reliability Officer & GM, Zscaler, concluded.