--- title: 'Announcement: Logfire Cloud & Self-Hosted Versions' description: >- We are excited to officially announce Enterprise Cloud and Enterprise Self-Hosted versions of our observability platform Pydantic Logfire date: '2025-03-21' authors: - Samuel Colvin categories: - Pydantic Logfire - Company canonical: 'https://pydantic.dev/articles/logfire-self-hosting-announcement' --- > Markdown version of [Announcement: Logfire Cloud & Self-Hosted Versions](https://pydantic.dev/articles/logfire-self-hosting-announcement) — the canonical HTML page. > > By [Samuel Colvin](https://pydantic.dev/authors/samuel-colvin.md) · 2025-03-21 · Pydantic Logfire, Company > > Related: [You've built this agent before](https://pydantic.dev/articles/harness-week.md) · [Your traces already know how to fix your prompt](https://pydantic.dev/articles/logfire-prompt-optimization.md) > > All articles: [/articles.md](https://pydantic.dev/articles.md) · Site index: [/llms.txt](https://pydantic.dev/llms.txt) --- After working closely with early adopter enterprise customers, we're pleased to officially announce **Enterprise Cloud** and **Enterprise Self-Hosted** versions of our observability platform. Both editions deliver the open, flexible foundation you need to gain actionable insights from logs, metrics, and distributed traces. As part of this we're open sourcing the [helm chart](https://github.com/pydantic/logfire-helm-chart) for Pydantic Logfire. ## Enterprise Cloud #### Who It's For If your organization needs support Service Level Agreements (SLAs), custom Data Processing Agreements (DPAs), or HIPAA Business Associate Agreements (BAAs), our managed cloud option provides a dedicated, contract-backed environment. #### Key Capabilities * **Full-Service Hosting**: All operational complexity is offloaded to our engineering team. * **Enhanced Support**: Our Enterprise Cloud plan includes priority support with guaranteed SLAs - ensuring timely responses and dedicated escalation paths if issues arise. Whether you need help with onboarding, integration, or scaling, we’re here to back you up 24/7. * **Compliance & Custom Billing**: Tailored billing, enterprise support packages, and industry-specific compliance options to match your regulatory requirements. * **Custom Retention Time Period**: Custom retention periods beyond our SaaS 30-day standard. --- ## Enterprise Self-Hosted #### Who It’s For Ideal for teams handling highly sensitive data, such as LLM workloads or regulated pipelines where data must remain on-prem. If your team is comfortable with Kubernetes, this solution gives you total control over your infrastructure and data. #### Key Capabilities * **Hassle-Free Deployment**: Our [newly open-sourced Helm chart](https://github.com/pydantic/logfire-helm-chart) lets you deploy quickly on any Kubernetes cluster, giving you full control with minimal operational headaches. * **Flexible Storage & Retention**: Store data in Parquet across any S3-compatible object storage system, allowing for fine-grained retention policies that suit your compliance or performance needs. * **Scalability**: Cloud native scaling via Kubernetes, enabling you to use your existing knowledge and infrastructure to scale up or down to match your workload and cost requirements. #### Support Services Enterprise Self-Hosted customers also gain access to advanced technical support. We provide: * **Installation & Configuration Guidance**: Best practices for production deployments, with personalized recommendations for your environment. * **Ongoing Troubleshooting**: Direct access to our support engineers for assistance with any operational or performance issues. * **Periodic Health Checks**: Optional assessments to ensure your cluster remains optimized and up-to-date with the latest features and security patches. --- ## Same Core Technology Stack Both offerings rely on the Pydantic Logfire core platform, which is built on **open standards** including: * OpenTelemetry for data ingestion * Highly efficient Parquet storage at rest * Powerful SQL-based queries backed by [Apache DataFusion](https://datafusion.apache.org/) Our [**open source Helm chart**](https://github.com/pydantic/logfire-helm-chart) ensures easy customization and deployment, minimizing the risk of vendor lock-in. This commitment to open technology also means **proven performance** at scale in real-world settings. By building on well-established protocols and open formats, our platform can integrate seamlessly with your existing tooling while offering the flexibility to evolve with your requirements. Our OTel compatibility means the migration path from other systems is considerably simpler (e.g. using an [OTel Collector](https://pydantic.dev/docs/logfire/instrument/opentelemetry-collector/otel-collector-overview/)). #### AI-Ready Architecture Our SQL-based query layer provides a familiar interface for AI assistants and tools, enabling seamless integration with modern LLM-powered workflows and automated analysis agents. This makes your observability data immediately accessible to the AI tools in your engineering stack, for example via our [Pydantic Logfire MCP server](https://pydantic.dev/articles/mcp-launch). --- ## High-Performance Queries with Apache DataFusion One of the standout features of our observability platform is its performance. Powered by a customized version of Apache DataFusion, an open source SQL query engine recognized as the fastest single node engine for querying Parquet files in [recent benchmarks](https://datafusion.apache.org/blog/2024/11/18/datafusion-fastest-single-node-parquet-clickbench/). --- ## Get Started Whether you want a fully managed environment for stringent compliance or total control over your data on-prem, our Enterprise Observability solutions have you covered. If you would like to learn more, [please get in touch](https://pydantic.dev/contact).