Every cloud account grows the same way: a test instance nobody shut down, a storage bucket from a migration two years ago, a database whose owner left the company. Steward walks all four of your clouds, AWS, Alibaba Cloud, Google Cloud and Microsoft Azure, and writes down what is actually running in one inventory you can search instead of four consoles you half remember. The point is not the list, it is what the list connects to: open any resource and see its relationships, which services depend on it, what shares its network, what breaks if it disappears. Cleanup stops being a leap of faith, because every candidate deletion is reviewed against that dependency map first, showing the impact before execution and following the result of each action afterwards. Scheduled scans keep the picture honest without you remembering to look, reporting exactly which resources each scan added, removed or modified, and pinging Slack, Feishu, DingTalk or WeCom when a scan fails. Connect accounts, including through OIDC, run the first sweep, and the orphaned, idle and forgotten start standing out from the infrastructure you actually need. It runs as a single executable with the web console and database built in, under systemd on your server, behind your HTTPS proxy with token sign-in. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

ManageIQ gives operators one console for every cloud and hypervisor the organization runs, connecting to VMware, OpenStack, AWS, Azure, Google Cloud, Kubernetes, OpenShift, and Nutanix to continuously discover inventory, map relationships, and listen for changes without installing agents. Discovered estates become manageable: operators publish bundles of resources into a self-service catalog that end users order like apps, then govern the full life cycle through policy, compliance, delegated operations, and retirement. SmartState analysis scans the contents of VMs, hosts, and containers agentlessly, even foreign or uncooperative ones, feeding security and compliance policies that flag drift automatically. Utilization metrics reveal idle systems and right-sizing opportunities, with capacity planning and what-if scenarios before hardware purchases. Chargeback and showback assign rates to tenants, group VMs by tag or container images by label, and generate reports in multiple currencies. Embedded Ansible automation executes playbooks for provisioning and remediation, and the Spassky release adds Nutanix and Terraform Enterprise providers on a Rails 7.2 core. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Your racks of hypervisor hosts become one private cloud with Apache CloudStack, the open-source IaaS platform that deploys and manages large networks of virtual machines behind a single web interface and API. One cloud can mix hypervisors side by side, running KVM, XenServer or XCP-ng, and VMware vSphere clusters under the same control plane, each organized into regions, zones, pods, and clusters that mirror your physical datacenters and racks. Administrators provision instances from templates and ISO images, take volume and VM snapshots on schedules, and migrate running instances between hosts in a cluster without downtime. Built-in networking spans isolated and shared networks, VPCs with tiered virtual routers, load balancers with SSL offloading, VPNs, and firewall rules, all exposed both to admins and to end users through separate, customizable interfaces. Multi-tenancy is native: domains, accounts, usage metering, and resource quotas let providers bill departments or customers for what they consume. The 4.22 LTS release strengthens backup and disaster recovery, adds a CSI driver for CloudStack Kubernetes Service, and streamlines VMware-to-KVM migrations for teams consolidating onto open virtualization. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Anyone juggling several Oracle Cloud accounts knows the tab-switching ritual; OCI Core ends it by pulling every tenancy's instances into one self-hosted panel. The cross-account list shows state, shape, volumes, and public IPs for each machine, and you can start, stop, resize, rename, or terminate instances without opening Oracle's console. A creation wizard offers every shape in an availability domain, not just the free presets, while long operations such as IP swaps, resizes, and terminations run as background jobs with visible progress. Capacity hunting watches Oracle's read-only capacity reports and retries creation until a scarce shape appears, notifying you when it lands. Networking tools edit VCNs, subnets, and security rules visually, swap public IPs, enable IPv6, and manage extra network cards. Storage views resize boot and block volumes, and a rescue mode moves a broken system disk to a healthy machine for repair. Billing breaks spend down by service and region, tracks the monthly free egress allowance, and shows real usage for free-tier accounts. Accounts are checked for connectivity, quotas, and credential health, with emails, IPs, and OCIDs masked by default and revealed only on demand. Alerts reach Telegram, WeCom, DingTalk, email, or webhooks, and access is guarded by argon2id passwords, TOTP two-factor sign-in, session controls, and an audit log. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

The Kubernetes project's own answer to cluster management UIs: maintained under SIG UI governance, Headlamp's roadmap tracks Kubernetes releases and its design philosophy reflects community needs rather than a vendor's product strategy. The React interface provides full read-write capabilities adapted to each user's RBAC permissions — delete, scale, edit, and restart buttons appear only when the authenticated user holds the corresponding cluster role, preventing accidental unauthorized actions. Multi-cluster support surfaces workloads across development, staging, and production from a single view without context switching. The plugin architecture drives extensibility through a curated catalog: an AI Assistant plugin answers natural-language cluster queries and performs operations via configurable LLM keys, Flux handles GitOps, Karpenter manages nodes. Integrated terminals provide browser-based exec access to running pods, live log streaming follows container output with filtering, and the YAML editor displays inline Kubernetes API documentation alongside resource definitions. Deployment creation forms let you configure containers, environment variables, volumes, and replicas without writing manifests. Side-by-side cluster comparison views surface differences in workload distribution. Works with any distribution: EKS, GKE, AKS, Minikube, Docker Desktop. Helm chart installation via the Headlamp repository with images on GitHub Container Registry. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Managing Kubernetes shouldn't require every developer to become a Kubernetes expert — KubeSphere wraps cluster operations, CI/CD, service mesh, and observability into guided web workflows that operations teams configure once and developers consume without kubectl. The LuBan extensible architecture treats each capability as an independently installable extension plugging into a lightweight microkernel: enable DevOps without service mesh, add monitoring without the app store, compose exactly what your organization needs. Multi-cluster management provides a centralized control plane for provisioning and operating clusters across cloud providers, data centers, and edge locations with unified identity and resource quotas. The DevOps extension integrates Jenkins for graphical pipeline creation with S2I and B2I workflows, while Argo CD powers GitOps continuous deployment with real-time sync status. Istio-based service mesh provides traffic management, canary deployments, circuit breaking, and distributed tracing through the console without CLI knowledge. Prometheus monitoring with custom dashboards, Fluentd log collection with multi-tenant search, and alerting via Slack and email complete the observability stack. Multi-tenant workspace hierarchy enforces resource quotas and fine-grained RBAC roles across teams. A built-in Helm-based app store handles lifecycle management across clusters. KubeKey deploys production-grade clusters on bare metal or VMs with air-gapped support. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

The de facto dashboard of observability: Grafana is the open-source frontend that turns the data stores you already run into interactive graphs. It does not store metrics itself; it connects to the data stores you already run and turns their contents into interactive dashboards. Supported sources number over 150 via plugins: Prometheus, Loki, Tempo, InfluxDB, Elasticsearch, MySQL, PostgreSQL, Microsoft SQL Server, AWS CloudWatch, Azure Monitor, Google Cloud Monitoring, and many more. Dashboards are built from a large library of panel types (time series, heatmaps, tables, gauges, logs) with template variables for reusable, parameterized views. Unified alerting evaluates rules against any connected data source, not just Prometheus, and routes notifications to Slack, PagerDuty, email, and other channels with grouping and silencing - unlike Prometheus Alertmanager, a single rule can combine a Loki log pattern, a PostgreSQL query result, and a CloudWatch metric. Dashboards serialize to JSON and data sources configure via provisioning files, so the entire observability setup can live in Git and deploy repeatably across environments. Explore mode adds ad-hoc querying outside dashboards, with split view for correlating a metric spike against the matching log lines, and access control spans organizations, teams, folder permissions, and OAuth, LDAP, and SAML integration. Written in Go and TypeScript, AGPL-licensed. Self-hosting gives you unlimited users, dashboards, and queries at flat hosting cost, without Grafana Cloud's usage-based pricing.

With 20,500+ GitHub stars and over 6,000 organizations running it in production — including a Fortune 100 company ingesting more than 4 PB per day — OpenObserve is the open-source observability platform that replaces your entire Datadog, Splunk, or ELK stack with a single Rust binary deploying in under two minutes. Apache Parquet columnar storage with zstd compression on S3-compatible object storage delivers 140x lower storage costs than Elasticsearch while providing better query performance on a quarter of the hardware. Ingest logs, metrics, and distributed traces via native OpenTelemetry OTLP endpoints with no vendor lock-in. Query logs and traces with standard SQL, metrics with SQL or PromQL — no proprietary query language to learn. The built-in dashboard builder offers 19 chart types including time-series graphs, heatmaps, gauges, tables, and top-K lists with drag-and-drop layout combining data from all signal types. Data pipelines process, enrich, redact, or normalize ingestion streams using Vector Remap Language for real-time transformations including PII redaction and logs-to-metrics conversion. Real User Monitoring captures frontend performance with session replay. The Service Catalog provides topology-based trace analysis with side-panel drill-downs into database queries and error details. Alerting supports real-time and scheduled rules with SQL and PromQL conditions. Native multi-tenancy isolates organizations and streams with complete data separation. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPLv3 licensed.

Webhooks, cron schedules, and app events trigger chains of nodes that fetch, transform, and route data: n8n is a workflow automation platform built around a visual, node-based editor. It ships with 400+ built-in integrations covering databases like Postgres, SaaS tools like Slack and HubSpot, and every major AI provider. When a pre-built node does not exist, the HTTP Request node calls any REST API, and the Code node runs JavaScript or Python inline, so you are never blocked by a missing connector. Workflows execute as directed graphs with branching, loops, error handling, and sub-workflows, and every run is logged for inspection and replay during debugging. It also includes LangChain-based nodes for building AI agents with tool calling and memory. Self-hosting on RepoCloud gives you unlimited workflow executions with no per-task pricing, and all data stays on your instance. Runs on Node.js with SQLite by default; add Postgres and Redis queue mode when you need to scale workers horizontally.

AWX transforms Ansible from a command-line tool into a centralized automation hub with a web UI, REST API, and distributed task engine for managing playbooks, inventories, and credentials at enterprise scale. The React-based dashboard provides real-time visibility into job status, inventory health, and execution history while Django REST Framework powers programmatic control over every automation resource. Job templates combine Ansible playbooks, inventories, and credentials into reusable units that chain together in workflow templates using directed acyclic graph orchestration with conditional branching on success, failure, or always-run logic and configurable convergence gates. The RBAC system built on django-ansible-base provides granular permission control over organizations, teams, projects, inventories, and credentials at object-level granularity. Dynamic inventory sources pull host data from AWS EC2, Google Cloud, Microsoft Azure, VMware vCenter, and Red Hat Satellite, while credential management securely stores SSH keys, cloud tokens, and vault passwords with HashiCorp Vault and CyberArk integration for external secret retrieval. Notifications deliver alerts via Slack, email, PagerDuty, Mattermost, IRC, and webhooks, while activity streams log every action for compliance auditing. The Receptor mesh network distributes job execution across isolated container-based execution environments with capacity-aware scheduling and hop-node routing for network-segmented infrastructures. Upstream of Red Hat Ansible Automation Platform. Deploys via Docker Compose with PostgreSQL and Redis or via the AWX Operator on Kubernetes. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Flowctl turns repetitive ops work, such as granting SSH access, restarting a service, or provisioning a server, into self-service forms that anyone on the team can run without holding credentials. Each workflow is a YAML or HUML file with typed inputs, validation rules, and a list of actions. Actions run in order or as a dependency graph, so independent branches execute in parallel. Every action runs in a Docker container, as a shell script, or as another flow, and scripts can target remote servers over SSH, several at once. Sensitive steps pause until a reviewer approves or rejects them. Output from one action feeds the next, files pass along as artifacts, and failed actions can be retried. Cron schedules with time zones and labels run flows unattended, while logs stream live in the browser. Email, Slack, Mattermost, and webhook notifications announce success, failure, waiting, or cancellation. Teams get isolated namespaces with user, operator, reviewer, and admin roles, OIDC single sign-on, and encrypted storage for SSH keys and secrets. A built-in flow editor means nobody has to hand-write files, and custom executors can be added as Go plugins. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

With over 3,700 GitHub stars and growing adoption among teams tired of managing complex orchestration platforms, Dagu delivers a complete workflow engine as a single Go binary that requires no external database, message broker, or framework installation. Define directed acyclic graphs in declarative YAML — specifying dependencies, schedules, retries, timeouts, approvals, and notifications — while keeping existing shell scripts, containers, and tools completely unchanged. The built-in Web UI provides live pipeline visualization, per-step log streaming, run history browsing, artifact previewing, manual retry controls, and workflow YAML editing without SSHing into servers. Execute steps as shell commands, Docker containers, Kubernetes Jobs, SSH remote commands, SQL queries, or HTTP requests, with conditional branching and parallel execution handled natively. The integrated Model Context Protocol server exposes dagu_read, dagu_change, and dagu_execute tools, enabling AI agents like Claude, Codex, and Cursor to inspect workflow state, preview YAML modifications, and control runs through authenticated endpoints. The harness.run executor lets external coding-agent CLIs operate inside DAG steps with full scheduling and approval gate support. Scale beyond a single machine with the distributed worker mode, which dispatches tasks to remote nodes via gRPC with automatic label-based routing and worker selection. Deploy with Docker, the official Helm chart for Kubernetes, or a simple binary download requiring only a Linux, macOS, or Windows host. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPLv3 licensed.

With over 27,000 GitHub stars and an ecosystem of 1,900+ plugins covering every major cloud provider, database, and SaaS platform, Kestra is the orchestration engine that brings Infrastructure as Code principles to workflow automation — defining complex multi-step pipelines in readable YAML that execute across any language, runtime, or infrastructure boundary. The built-in VS Code-style editor provides syntax highlighting, auto-completion, real-time validation, and an AI Copilot that generates workflow YAML from natural language descriptions. Tasks execute in Python, Node.js, Go, R, Shell, SQL, or any Docker container, with event-driven triggers listening for file arrivals on SFTP and cloud storage, messages from Kafka, Redis, Pulsar, AMQP, MQTT, NATS, AWS SQS, Google Pub/Sub, and Azure Event Hubs in real time. The topology view visualizes workflow DAGs with execution state, duration, and output artifacts for each task node. Namespaces organize workflows into isolated environments with configurable secrets, while subflows enable modular composition with inputs, outputs, and conditional branching. Retry policies, timeouts, error handlers, and automatic backfills for missed schedules ensure reliability across production workloads. Git integration pushes workflows directly to branches from the UI with CI/CD pipeline support for automated deployment. The REST API enables programmatic workflow management, execution triggering, and resource provisioning. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.