
Grafana Labs delivers the leading AI-powered observability platform, built around Grafana—the most widely adopted open source technology for dashboards and visualization. Recognized as a Leader in the 2025 Gartner® Magic Quadrant™ for Observability Platforms, Grafana Labs supports more than 25 million users and thousands of organizations worldwide, from startups to Fortune 500 enterprises.
Grafana Cloud is the open observability cloud, designed to help engineering teams observe everything and solve anything. Built on open source, open standards, and open ecosystems, it unifies metrics, logs, traces, and profiles in a single platform for full-stack visibility across applications, infrastructure, and digital experiences.
At the core is the open-source LGTM stack: Grafana for dashboards and visualization, Mimir for metrics, Loki for logs, and Tempo for distributed tracing. Native OpenTelemetry and Prometheus support allow teams to ingest telemetry from virtually any environment, while hundreds of integrations connect existing tools and data sources without costly rip-and-replace migrations.
Grafana Cloud combines powerful analytics with AI-driven observability. Grafana Assistant helps engineers investigate issues, explore telemetry, and troubleshoot faster. Adaptive Telemetry identifies the data that matters most and aggregates the rest, helping organizations reduce telemetry costs while preserving valuable insights
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With solutions for Kubernetes monitoring, application observability, digital experience monitoring, incident response, synthetic monitoring, and performance testing, Grafana Cloud delivers a complete observability platform that scales with your business.
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Accelerate your data journey with AnalyticsCreator—a metadata-driven data warehouse automation solution purpose-built for the Microsoft data ecosystem. AnalyticsCreator simplifies the design, development, and deployment of modern data architectures, including dimensional models, data marts, data vaults, or blended modeling approaches tailored to your business needs.
Seamlessly integrate with Microsoft SQL Server, Azure Synapse Analytics, Microsoft Fabric (including OneLake and SQL Endpoint Lakehouse environments), and Power BI. AnalyticsCreator automates ELT pipeline creation, data modeling, historization, and semantic layer generation—helping reduce tool sprawl and minimizing manual SQL coding.
Designed to support CI/CD pipelines, AnalyticsCreator connects easily with Azure DevOps and GitHub for version-controlled deployments across development, test, and production environments. This ensures faster, error-free releases while maintaining governance and control across your entire data engineering workflow.
Key features include automated documentation, end-to-end data lineage tracking, and adaptive schema evolution—enabling teams to manage change, reduce risk, and maintain auditability at scale. AnalyticsCreator empowers agile data engineering by enabling rapid prototyping and production-grade deployments for Microsoft-centric data initiatives.
By eliminating repetitive manual tasks and deployment risks, AnalyticsCreator allows your team to focus on delivering actionable business insights—accelerating time-to-value for your data products and analytics initiatives.
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VictoriaMetrics Cloud
VictoriaMetrics Cloud allows you to run VictoriaMetrics Enterprise on AWS without having to perform typical DevOps activities such as proper configuration and monitoring, log collection, security, software updates, software protection, or backups.
We run VictoriaMetrics Cloud in our environment using AWS, and provide easy to use endpoints for data ingestion. VictoriaMetrics takes care of software maintenance and optimal configuration.
It has the following features:
It can be used to manage Prometheus. Configure Prometheus, Vmagent or VictoriaMetrics to write data into Managed VictoriaMetrics. Then use the endpoint provided as a Prometheus source in Grafana.
Each VictoriaMetrics Cloud instance runs in a separate environment so that instances cannot interfere with one another;
VictoriaMetrics Cloud can be scaled-up or scaled-down in just a few clicks.
Automated backups.
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NudgeBee
NudgeBee is an enterprise-grade AI Agents and Agentic Workflow platform purpose-built for SRE, CloudOps, DevOps, and platform engineering teams running complex cloud-native environments.
The platform ships pre-built AI Assistants that work on day one, no model training, no prompt engineering. The AI SRE Agent handles incident triage, alert enrichment, root cause analysis, and remediation guidance.
The AI FinOps Assistant delivers continuous Kubernetes and cloud cost optimization with right-sizing, spot instance, and abandoned resource recommendations.
The AI K8sOps Agent provides natural-language interaction with clusters for workload checks, upgrade guidance, and maintenance operations.
Alongside these, NudgeBee's visual no-code Workflow Builder lets teams automate any custom operational process. It supports 20+ action categories including native AWS, Azure, and GCP CLI nodes, kubectl execution, database queries, LLM-powered nodes, Agent-to-Agent (A2A) calls, and MCP server integration, all with built-in approval gates and audit logging.
Key technical differentiators: NudgeBee uses a live semantic Knowledge Graph to ground AI answers in real infrastructure topology. It queries observability data in place, zero data ingestion, zero egress cost. A single workflow can span multiple clouds, Kubernetes clusters, ticketing tools, and communication channels.
49+ integrations across Kubernetes, AWS, Azure, GCP, Prometheus, Datadog, Dynatrace, Jira, ServiceNow, Slack, GitHub, ArgoCD, and more. Enterprise-ready: RBAC, MFA, immutable audit trails, BYOM (GPT, Claude, Gemini, Bedrock, Ollama), self-hosted deployment, SOC-2 Type II, and ISO 27001 certified.
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