Kloudfuse Launches Kloudfuse 3.5: Revamping Enterprise Observability for the AI Era

One platform for complete visibility, control, and AI-ready operations

CUPERTINO, Calif., Dec. 02, 2025 (GLOBE NEWSWIRE) -- Kloudfuse, the AI-Powered Unified Observability platform, today announced the launch of Kloudfuse 3.5, transforming how enterprises monitor both traditional and AI workloads. The release integrates Model Context Protocol (MCP) server capabilities for natural language observability access, implements FIPS 140-2/3 validated cryptographic modules for regulated enterprises, and introduces platform engineering controls that give teams unprecedented visibility and cost management capabilities.

"Observability is at an inflection point. As organizations embrace AI and intelligent applications, the old model of fragmented tools, runaway costs, and vendor-controlled data no longer works," said Pankaj Thakkar, CEO and Co-Founder of Kloudfuse. "We built Kloudfuse 3.5 to fundamentally rethink what observability should be: unified, AI-ready, and built on a foundation of data freedom. Teams shouldn't have to trade visibility for control, or innovation for cost predictability. We're building the observability platform modern engineering teams deserve."

"The technical challenge we solved with 3.5 was making AI observability native, not bolted on," said Ashish Hanwadikar, CTO and Co-Founder of Kloudfuse. "We integrated LLM telemetry directly into our APM using standards-based OpenTelemetry, so platform teams get the same operational control over AI workloads as they do for traditional services. Our MCP server exposes Kloudfuse's full observability model, unifying signals across metrics, logs, traces, events, and mapping service and infrastructure dependencies. You can ask natural language questions and get the same comprehensive, correlated insights engineers get from the UI. That's the difference between adding AI features and building AI-native observability."

Since launching version 3.0 in November 2024, Kloudfuse has shipped over 50 major capabilities across AI and intelligent observability, enterprise security and compliance, platform engineering controls, query and analytics power, and OpenTelemetry-native architecture.

AI-Native Observability: From Infrastructure to Intelligence

Kloudfuse 3.5 bridges traditional infrastructure monitoring with intelligent systems through two breakthrough capabilities:

Model Context Protocol (MCP) Server: The Kloudfuse MCP server enables AI systems to query observability data using natural language from Claude, ChatGPT, or custom agents. Ask "What caused the latency spike in checkout yesterday?" and receive correlated insights across metrics, logs, traces, and infrastructure dependencies through FuseQL translation. Platform teams build custom agents for automated incident response, capacity planning, and cost optimization using standards-based access that works across LLM providers.
LLM Observability: Kloudfuse 3.5 integrates LLM monitoring directly into APM. Capture prompt and output tracing as events attached to distributed traces, track token usage supporting OpenAI, Anthropic, Google, AWS, and Azure, and monitor API failures and model-level errors. Integration with LangChain and LlamaIndex frameworks provides full-stack visibility through unified OpenTelemetry instrumentation, eliminating duplicate agents.

Security and Compliance: Built for Regulated Enterprises

"At Zscaler's scale, observability must be both robust and compliant, and Kloudfuse 3.5 continues to excel on both fronts," said Kishore Thakur, Senior Director, Cloud Platform Engineering at Zscaler. "The platform efficiently handles our massive data volumes across global deployments while meeting stringent security requirements, including FIPS 140-2 compliance and a FedRAMP authorization pathway. For enterprises operating at scale with strict compliance needs, Kloudfuse provides an exceptional combination of flexibility, security, and innovation."

FIPS 140-2/3 Validation and FedRAMP Authorization Pathway: Kloudfuse 3.5 implements FIPS 140-2/3 validated cryptographic modules throughout the platform, covering data ingestion, storage, queries, and API access, ensuring cryptographic functions meet government requirements. Building on FIPS validation, Kloudfuse establishes a clear FedRAMP authorization pathway with NIST 800-53 security controls, continuous monitoring, automated compliance reporting, and POA&M generation for vulnerability management. Combined with VPC deployment, organizations retain complete data sovereignty while meeting stringent compliance requirements.

Data Governance: Enterprise Control Over Observability Data

Security and compliance extend beyond cryptography to how observability data is managed, accessed, and audited.

Data Scrubbing Across All Streams: Kloudfuse 3.5 expands data scrubbing capabilities across all telemetry streams: Metrics, Logs, APM traces, Events, and RUM. Preview data before deletion, apply sophisticated filters and regex patterns, and maintain comprehensive audit trails for GDPR's right to deletion, HIPAA's data minimization requirements, and internal data retention policies.
Stream-Specific RBAC: Stream-specific RBAC policies enable granular access control based on labels, tags, or custom attributes. Development teams see only their services' data while security teams maintain comprehensive access and finance teams query only aggregated metrics. This implements principle of least privilege for observability data.
Identity Provider Synchronization: Kloudfuse 3.5 automatically synchronizes groups and roles with SAML and OAuth 2.0 identity providers including Okta and Google. As organizational structure evolves, access controls stay current without manual updates. Engineers joining teams, role changes, and account deactivations update permissions automatically.
Hierarchical Organization: Organize dashboards, alerts, and objects in hierarchical folder structures that mirror organizational complexity. RBAC policies apply at the folder level and inherit downward, enabling delegation without chaos. Private folders ensure sensitive investigations remain confidential.
Self-Ingested Audit Logging: Audit logging captures every configuration change and can be self-ingested into Kloudfuse itself, creating a queryable trail using FuseQL. Search audit logs, build dashboards showing configuration changes over time, and alert on suspicious access patterns, simplifying regulatory audits by making compliance data observable.

Platform Engineering: Control That Scales

Kloudfuse 3.5 delivers capabilities purpose-built for teams managing observability at enterprise scale.

Stream-Specific Rate Control: Kloudfuse 3.5 introduces granular rate control at the stream level, enabling independent ingestion limits for metrics, logs, traces, events, and RUM. Within each stream, filters prioritize business-critical data over noise, preventing runaway ingestion from misbehaving services and ensuring observability infrastructure capacity remains predictable.
Multi-Zone High Availability and Disaster Recovery: Kloudfuse 3.5 offers flexible availability options to match organizational requirements. Multi-zone High Availability provides automatic failover with zero downtime and no manual intervention across availability zones. For cost-conscious deployments, the platform supports quick disaster recovery configurations with manual failover triggers, reducing resource requirements while enabling rapid recovery across regions.
Service Accounts and Automation: Kloudfuse 3.5 introduces enterprise-grade service accounts with bearer token authentication, enabling secure machine-to-machine interactions. Assign RBAC policies to both users and service accounts, enabling GitOps approaches to observability configuration and programmatic management of dashboards, alerts, and policies.
Consumption Tracking and Cost Visibility: Real-time consumption tracking dashboards provide granular breakdowns of data volumes and costs by stream, by team, and by custom tracking labels. Enable chargeback and showback models that attribute observability costs to the teams generating them, creating accountability and enabling informed capacity planning.
Custom Metrics SLOs: Kloudfuse 3.5 extends beyond basic latency and availability SLOs with custom metrics SLOs using PromQL queries. Define service level objectives based on any metric, enabling business-driven observability that tracks what matters: conversion rates, data pipeline lag, cache hit ratios, or custom business KPIs.

FuseQL: Query Capabilities That Compete with Specialized Vendors

Kloudfuse's proprietary FuseQL query language continues expanding capabilities that compete with specialized log analytics platforms while maintaining unified query syntax across all telemetry types.

Scheduled Views and Scheduled Search: Kloudfuse 3.5 introduces scheduled views, pre-aggregated datasets that update at specified intervals, enabling dramatically improved query performance by querying precomputed results instantly instead of scanning raw data repeatedly. Cron-based scheduled searches automate routine investigations like daily security audits, weekly capacity reports, or hourly compliance checks.
Advanced Operators for Complex Analysis: Version 3.5 expands FuseQL's operator library with sophisticated analysis capabilities including time range comparisons to identify changes between releases or incidents, efficient pattern matching and membership testing, native handling of complex structured data, and on-the-fly data enrichment without modifying ingestion pipelines.

OpenTelemetry Native: No Proprietary Agents, No Vendor Lock-In

Kloudfuse doubles down on open standards as architecture, not marketing. Kloudfuse 3.5 demonstrates that standardization enables innovation rather than constraining it.

Kloudfuse 3.5 visualizes Kubernetes infrastructure topology using pure OpenTelemetry instrumentation through OTel Events support, automatically discovering pods, nodes, services, and their relationships, no proprietary agents required. The platform implements both Prometheus native histograms and OTLP exponential histograms with complete function libraries for accurate metric distributions. Expanded cloud integration adds AWS CloudFront metrics enrichment and GCP Stackdriver metrics ingestion through standard cloud APIs, plus GeoIP support for location-based analysis. When you evaluate alternatives or evolve your observability strategy, your instrumentation remains portable.

Proven at Scale

"Kloudfuse continues to deliver the scale, flexibility, and cost efficiency we need as Automation Anywhere grows globally," said Raghu Sethuraman, Vice President of Engineering at Automation Anywhere. "The enhanced FuseQL capabilities give our engineering teams powerful new ways to analyze trends and troubleshoot issues faster. We're particularly excited about the MCP Server, which will enable our developers to interact with observability data in entirely new ways. Longer data retention and complete ownership through Self-SaaS deployment are exactly what we need to confidently build and operate the next generation of AI-powered automation at global scale."

Trusted by enterprises including Zscaler, GE Healthcare, Tata 1mg, and Automation Anywhere, Kloudfuse processes millions of events per second while delivering 60-80% cost savings compared to competitors. With over 700 integrations, Kloudfuse has proven that observability doesn't require choosing between capability and control.

The Self-SaaS architecture underlying every capability in Kloudfuse 3.5 fundamentally differentiates the platform. Deploy Kloudfuse in your own VPC on AWS, Azure, or GCP. Your data never leaves your infrastructure. You control retention, storage costs, and eliminate data egress fees, yet you get SaaS-like simplicity with managed control plane, automatic updates, and expert support.

Learn more about Kloudfuse 3.5 capabilities
Sign up for a demo
Read the technical documentation

Kloudfuse will be demonstrating version 3.5 capabilities at Gartner IT Infrastructure, Operations & Cloud Strategies Conference, taking place in Las Vegas, Nevada, from December 9-11, 2025. Visit booth 646 to see the Model Context Protocol Server in action and learn how Kloudfuse is building enterprise-ready observability for modern infrastructure.

About Kloudfuse

Kloudfuse is a unified observability platform integrating with over 700 diverse infrastructures, cloud services, and applications. By harnessing open standards like OpenTelemetry and Prometheus, Kloudfuse eliminates vendor lock-in while providing advanced capabilities across metrics, logs, traces, events, and real user monitoring. Deployed within customer VPCs, Kloudfuse ensures scalability, cost-efficiency, and enterprise security. Trusted by leading organizations like Zscaler, GE Healthcare, Tata 1mg, and Innovacer, Kloudfuse delivers observability that enterprises can operate with confidence.

Learn more at www.kloudfuse.com or follow us on LinkedIn.

Contact:
Neha Smriti
Kloudfuse
neha.smriti@kloudfuse.com

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