CloudBolt

Resource Plane
Self-service Cloud Platform Orchestrator
Source
Closed
What is CloudBolt?
CloudBolt is a self-service cloud management platform that automates resource delivery, enforces governance, and unifies control across hybrid and multi-cloud environments.

Profile

CloudBolt is an enterprise hybrid cloud management platform that provides unified visibility, governance, and cost optimization across heterogeneous infrastructure environments including public clouds, private virtualization, and Kubernetes clusters. Backed by Insight Partners and actively maintained with regular releases, the platform has established itself as a comprehensive solution for organizations managing complex multi-cloud architectures. CloudBolt addresses the persistent challenge of cloud fragmentation by functioning as an "orchestrator of orchestrators," integrating with existing infrastructure tools while providing centralized control. The platform combines cloud management, financial operations (FinOps), and automation capabilities to help enterprises reduce waste, accelerate provisioning, and demonstrate return on investment from cloud infrastructure spending.

Focus

CloudBolt solves the fundamental challenge of managing fragmented cloud operations across multiple infrastructure providers and deployment models. Organizations struggle with visibility gaps, uncontrolled spending, inconsistent governance, and manual provisioning processes that create operational bottlenecks. The platform addresses these issues by consolidating cloud management functions—provisioning, cost tracking, security enforcement, and optimization—into unified workflows accessible through a single interface. Primary users include enterprise IT operations teams managing heterogeneous environments, FinOps practitioners implementing cost accountability frameworks, platform engineers deploying containerized workloads, and managed service providers requiring automated billing capabilities. CloudBolt enables organizations to maintain centralized governance while providing developers with self-service infrastructure access, resolving the tension between operational control and business agility.

Background

CloudBolt was founded in 2011 by Alexandre Augusto da Rocha and Bernard Sanders, who developed the initial platform prototype called SmartCloud. The company rebranded to CloudBolt Software in 2012 and has evolved through consistent product releases tracking enterprise cloud technology adoption. Insight Partners became the primary investor through a Series A funding round in 2018 and subsequent Series B funding in 2020, providing approximately $61 million in total capital. The company acquired StormForge in 2025 to integrate machine learning-powered Kubernetes optimization capabilities. CloudBolt maintains active development with regular platform releases and has achieved recognition from industry analysts including Gartner and GigaOm. The platform is deployed across diverse organizations including federal agencies, data integration software companies, and IT services providers managing production workloads at scale.

Main features

Unified hybrid cloud orchestration and self-service provisioning

CloudBolt provides comprehensive infrastructure orchestration across twenty-five distinct cloud and virtualization environments including VMware vSphere, AWS, Azure, Google Cloud Platform, OpenStack, and Kubernetes. The platform performs continuous auto-discovery, synchronizing resource state information every thirty minutes to maintain accurate inventory across heterogeneous infrastructure. Users provision complex multi-tier applications through blueprint-based templates that abstract cloud-specific details, enabling identical infrastructure deployments across multiple providers without requiring specialized knowledge. The self-service catalog allows authorized users to order infrastructure through graphically-driven workflows, with provisioning completing in minutes rather than weeks typical of manual processes. CloudBolt integrates deeply with configuration management systems including Ansible, Chef, and Puppet, enabling complete application configuration within single provisioning workflows.

Financial operations and cloud cost optimization

CloudBolt implements comprehensive FinOps capabilities through unified cost visibility using the FOCUS standard, which normalizes billing data across different cloud providers into consistent formats. The platform enforces automated cost allocation through programmatic tagging policies that prevent deployment of untagged resources, ensuring accurate cost attribution to teams and projects. Advanced analytics identify spending patterns and optimization opportunities, with automated rightsizing recommendations eliminating waste from idle or underutilized resources. Budget management features define spending limits at group or resource levels with automated alerts when thresholds approach. Chargeback and showback capabilities attribute cloud costs to consuming departments, enabling financial accountability. Organizations achieve substantial waste reductions through continuous optimization that analyzes utilization patterns and implements corrective actions without manual intervention.

Kubernetes optimization and container cost management

CloudBolt integrates machine learning-powered Kubernetes optimization capabilities that automatically analyze container workload patterns and continuously adjust resource requests, limits, and horizontal pod autoscaler targets based on real-time demand observations. The platform addresses persistent overprovisioning challenges where container requests vastly exceed actual usage, resulting in wasted infrastructure spending. Bill-accurate cost allocation extends down to individual container levels, enabling precise understanding of which applications, teams, or projects drive Kubernetes spending. Machine learning models analyze container restart frequencies, resource contention patterns, and application startup performance to identify optimization opportunities beyond simple rightsizing. This continuous optimization eliminates manual trial-and-error resource estimation, automatically tuning allocations to match actual consumption patterns while minimizing performance degradation risk.

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