Listing Thumbnail

    Langfuse LLM Observability - Software Sushi

     Info
    Deployed on AWS
    Free Trial
    Langfuse is an open source LLM observability platform for tracing, evaluating and debugging LLM applications. This Ubuntu 24.04 AMI runs the full single-node stack with per-instance credentials created at first boot, and you reach the UI through AWS Systems Manager port forwarding.

    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

    Delivery method

    Delivery option
    64-bit (x86) Amazon Machine Image (AMI)

    Latest version

    Operating system
    Ubuntu 24.04

    Deployed on AWS
    New

    Introducing multi-product solutions

    You can now purchase comprehensive solutions tailored to use cases and industries.

    Multi-product solutions

    Features and programs

    Financing for AWS Marketplace purchases

    AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
    Financing for AWS Marketplace purchases

    Pricing

    Free trial

    Try this product free for 5 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.

    Langfuse LLM Observability - Software Sushi

     Info
    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Usage costs (1)

     Info
    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.

    How can we make this page better?

    Tell us how we can improve this page, or report an issue with this product.
    Tell us how we can improve this page, or report an issue with this product.

    Legal

    Vendor terms and conditions

    Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .

    Content disclaimer

    Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.

    Usage information

     Info

    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

    1. 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.
    2. 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).
    3. Read the admin password: sudo cat /etc/langfuse/admin.password (user admin@localhost.local ).
    4. 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.
    5. 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.
    6. 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.

    Similar products

    Customer reviews

    Ratings and reviews

     Info
    0 ratings
    5 star
    4 star
    3 star
    2 star
    1 star
    0%
    0%
    0%
    0%
    0%
    0 reviews
    No customer reviews yet
    Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.