Overview
Langfuse 4.56.0 is an open source LLM engineering platform for tracing, evaluating and debugging LLM applications. This AMI runs it inside your own AWS account as a single-node stack, so trace data stays on an EBS volume you control and the UI stays off the public internet.
What you get: Langfuse web and worker plus Postgres, Redis, ClickHouse and MinIO in Docker Compose with pinned image digests, all bound to loopback. First boot generates private per-instance credentials and an admin password (/etc/langfuse/admin.password, readable only with sudo). The AMI contains no customer credentials or databases, and telemetry is disabled.
Getting started: launch t3.large (8 GiB RAM, 40 GiB encrypted gp3 or larger) with an instance profile that has AmazonSSMManagedInstanceCore, allow outbound HTTPS and keep the security group free of inbound rules. Connect with Session Manager, run sudo -iu ubuntu bash /opt/sushi/docs/demo.sh, then forward port 3000 with AWS-StartPortForwardingSession and sign in from your browser. Send traces with OpenTelemetry (OTLP) or a v4 Langfuse SDK and query them with the Observations API v2 (add fields=core,basic,io to include input and output). Upstream documentation: https://langfuse.com/docs .
The bundled ClickHouse is the stable 25.12 release. Its static binary embeds OpenSSL 3.5.0, which has a published CVE; ClickHouse is reachable only on loopback inside the instance. Updated AMIs will follow new stable ClickHouse releases.
This is a single-node deployment, not a clustered or managed service. Back up the Docker volumes and /etc/langfuse together before replacing an instance.
Software fee: USD 0.02 per running t3.large instance-hour with the first five days free for one concurrent instance; the same full software runs throughout and there is no product-imposed time, user or usage limit. EC2, EBS and data transfer are billed separately. No annual offer is configured.
This is a repackaged open source software product wherein additional charges apply for independent AWS packaging, validation, maintenance and setup documentation. Langfuse is MIT-licensed outside separately licensed ee/ paths; enterprise features are not included. Software Sushi supplies the AMI recipe, packaging and setup guide without claiming upstream endorsement.
Highlights
- Trace, evaluate and debug LLM applications with Langfuse 4.56.0, ingesting through OpenTelemetry or the v4 Langfuse SDKs.
- Trace data stays on your EBS volume, and each instance creates its own credentials and admin password on first boot.
- The UI and data services bind to localhost; you reach the UI through Session Manager port forwarding.
Details
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Dimension | Cost/hour |
|---|---|
t3.large Recommended | $0.02 |
Vendor refund policy
We offer a full refund of software charges for the first 48 hours billing starts if the product does not perform as described. To request a refund, email info@softwaresushi.com with your EC2 instance ID and a description of the issue. AWS infrastructure costs (EC2, EBS, data transfer) are billed by AWS and are not eligible for refund by us.
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Langfuse 4.56.0 (MIT, by Langfuse GmbH) on Ubuntu 24.04 LTS as a single-node Docker Compose stack: web, worker, Postgres, Redis, ClickHouse and MinIO, all with pinned image digests. The UI listens on 127.0.0.1:3000 and is reached through Session Manager port forwarding. Per-instance credentials are generated at first boot. Ingest traces with OTLP or a v4 Langfuse SDK and read them back with the Observations API v2. Telemetry is disabled.
Additional details
Usage instructions
- Launch t3.large (8 GiB RAM, 40 GiB or larger encrypted gp3, IMDSv2) with an instance profile that has AmazonSSMManagedInstanceCore and outbound HTTPS. No inbound rules are needed.
- Connect: aws ssm start-session --target <instance-id>. After cloud-init finishes, run: sudo -iu ubuntu bash /opt/sushi/docs/demo.sh (expect SUSHI_CUSTOMER_DEMO_PASSED).
- Read the admin password: sudo cat /etc/langfuse/admin.password (user admin@localhost.local ).
- From your workstation: aws ssm start-session --target <instance-id> --document-name AWS-StartPortForwardingSession --parameters '{"portNumber":["3000"],"localPortNumber":["3000"]}', then open port 3000 on your workstation in a browser and sign in.
- Send traces with OTLP to /api/public/otel/v1/traces or with a v4 Langfuse SDK using the project keys from the UI. Read them back with GET /api/public/v2/observations with fields=core,basic,io to include input and output (the default fields omit them). The legacy v2/v3 ingestion endpoint is not accepted in this v4 mode.
- ClickHouse: the bundled ClickHouse is the stable 25.12 release. Its static binary embeds OpenSSL 3.5.0, which has a published CVE; ClickHouse listens only on loopback and is not reachable from the network. Move to a newer AMI when one is released. Docs: https://langfuse.com/docs . Back up the Docker volumes and /etc/langfuse together.
Support
Vendor support
Software Sushi provides AMI packaging and setup guidance. Contact info@softwaresushi.com for installation questions. This offer does not include upstream Langfuse support.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.