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gobetween is a self-hosted Layer 4 load balancer and reverse proxy for TCP, TLS, and UDP traffic. Its central use case is routing traffic to backend services whose addresses or membership change over time: it can discover backends through sources such as DNS SRV, Docker or Swarm, Consul, HTTP responses, and custom scripts, then apply health checks and a selected balancing strategy.

It is not a general-purpose Layer 7 HTTP proxy: the project materials emphasize transport-level TCP, TLS, and UDP load balancing. That distinction matters if you need application-aware routing based on HTTP paths, headers, or cookies.

What gobetween does

The project describes gobetween as free and open-source software distributed as a single binary for multiple platforms. Alongside load balancing, its documented capabilities include backend discovery, health checks, and a REST API for server configuration, statistics, and management. The project documentation frames it as a response to a common microservice problem: service instances can appear, disappear, or change addresses, so a manually maintained backend list can become stale.

Project materials list TCP, TLS, and UDP support. The repository summary also names features such as TLS termination and proxying, ACME, PROXY Protocol, and optional UDP virtual sessions and transparent mode. These implementation-specific options can depend on the build and its configuration, so check the documentation for the exact version you plan to run rather than assuming every option is available or configured identically.

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The project documentation describes gobetween as aiming to provide a “fast, flexible and full-featured load balancing solution for modern microservice architectures.” “Fast” is the project’s characterization, not a performance result established by an independent benchmark here.

How gobetween discovers backends

Discovery determines where gobetween sends traffic. The documented choices cover both fixed backend lists and dynamic sources:

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Discovery source What it is for
Static configuration A known, manually specified set of backend addresses.
DNS SRV Backends published through DNS SRV records, including the service and port information those records provide.
Docker or Swarm Discovering service instances in Docker-based environments.
Consul Using Consul as a service-discovery source.
HTTP text or JSON Reading backend information from an HTTP endpoint that returns the supported text or JSON format.
Custom scripts Generating or retrieving a backend list through a script.

These options address different operating models. Static configuration is straightforward when membership changes rarely; an orchestrator or service registry is more suitable when instances are frequently replaced. HTTP and script-based discovery can bridge systems without a built-in integration, but they make the endpoint format, script behavior, execution permissions, and failure handling part of the deployment you must validate.

Documented example use cases include simple load balancing, SRV balancing, Docker/Swarm balancing, Elasticsearch with exec discovery, and Consul discovery used with Docker Registrator. Those examples show possible integration patterns; they do not guarantee that a particular cluster or current version will work without environment-specific configuration.

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Health checks: what they tell you

The project site describes built-in TCP ping checks and support for custom scripts. The repository summary also describes probes that send bytes and evaluate a response. A successful TCP connection only establishes that a connection could be made to the checked address and port at that moment. It does not prove that the application can serve valid requests, reach its dependencies, or meet your service’s readiness criteria.

Choose a check that matches the failure you need to detect. A TCP check can identify an unreachable listener; a probe that evaluates a response or a custom script can test a more specific condition if it is implemented appropriately. Before relying on a check, verify its timing, thresholds, behavior during discovery changes, and effect on traffic when it fails. The available sources do not establish universal defaults or guarantee application-level health checking for every protocol and deployment.

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Which load-balancing strategy should you use?

Project materials list weighted selection, round robin, IP hashing, least connections, and least bandwidth. The right choice depends on backend capacity, client-affinity needs, and whether maintaining connection or bandwidth state is meaningful for your traffic.

Strategy Routing behavior Affinity and weighting State or measurement When membership changes
Weighted selection Uses configured weights to influence how often backends are selected. Weights are central; it does not inherently promise client affinity. Requires configured backend weights; additional requirements are not stated in the cited project summaries. New or removed backends change the pool of weighted choices; verify how the chosen version applies updated weights.
Round robin Distributes selections in rotation across backends. No client affinity is implied; weights are not established for this strategy in the cited summaries. Tracks the rotation order, rather than choosing by observed connection load. The rotation pool changes as backends are added or removed; verify update behavior for the configured discovery source.
IP hashing Uses the client IP in backend selection. Can provide a degree of client-IP-based affinity; it is not equivalent to application-session persistence. Uses the client IP as the selection input; other required measurements are not stated. Changes to the backend set can alter the mapping, so affinity may not survive membership changes.
Least connections Selects according to the number of active connections. Does not inherently provide client affinity; weighting behavior is not stated in the cited summaries. Requires connection counts for backend selection. New backends join the selection pool; confirm how counts and eligibility are updated when discovery or health status changes.
Least bandwidth Selects according to bandwidth use. Does not inherently provide client affinity; weighting behavior is not stated in the cited summaries. Requires bandwidth measurements or accounting. New backends affect the candidate pool; verify the version’s measurement and update behavior.

Use round robin when straightforward distribution is sufficient, IP hashing when client-IP affinity is useful and its limitations are acceptable, or a least-load option when the relevant connection or bandwidth measurements reflect the workload. Consider weighted selection when backends have intentionally different capacities. The project materials list these strategies but do not establish a universally best option or provide an independently verified current performance comparison.

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Configuration and operational checks

The documentation covers protocol selection, balancing, discovery, health checks, access control, PROXY Protocol, TLS proxying, and SNI, and lists a REST API. The repository summary identifies an MIT license and single-binary distribution. Those are useful deployment characteristics, but they do not substitute for validating the details of a specific build.

  • Confirm the version and syntax: check the configuration reference and examples that match the binary you intend to deploy. The repository summary lists TOML and JSON configuration, but keys and feature availability may vary by version.
  • Validate TLS behavior: establish whether your design requires TLS termination, TLS proxying, SNI handling, or certificates obtained through ACME, then confirm certificate requirements and supported options for that build.
  • Protect management access: determine whether the REST API is enabled, which interfaces it listens on, and how access control and network restrictions prevent unauthorized configuration or statistics access.
  • Limit discovery permissions: grant only the Docker, Swarm, Consul, or other source permissions the deployment needs, and decide what should happen if a discovery source becomes unavailable or returns stale data.
  • Test failure behavior: verify how unhealthy backends are removed or restored, how existing connections behave, and what happens if no eligible backend remains.

Project status and fit

The newer surfaced repository README wording describes gobetween as being in maintenance mode and accepting pull requests. An older package-index snapshot says “Under active development” and reports a module publication date of May 6, 2019; that older wording conflicts with the newer status signal. Neither establishes an exact latest release, support SLA, or current commit activity. Treat the maintenance-mode description as the status stated by that newer README, and independently confirm upstream release and support information before adopting gobetween for a production service.

gobetween is worth evaluating when you need a self-hosted Layer 4 proxy with multiple backend-discovery options and control over balancing and health checks. It is a poor fit if your requirement is specifically a general Layer 7 HTTP proxy with documented path-, header-, or cookie-based routing. In either case, assess the version-specific configuration and failure modes against your own protocols, network, and operational requirements.

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