Open Source Go Distributed Tracing Tools

As on-the-ground microservice practitioners are quickly realizing, the majority of operational problems that arise when moving to a distributed architecture are ultimately grounded in two areas: networking and observability. It is simply an orders of magnitude larger problem to network and debug a set of intertwined distributed services versus a single monolithic application. Jaeger, inspired by Dapper and OpenZipkin, is a distributed tracing system released as open source by Uber Technologies. It is used for monitoring and troubleshooting microservices-based distributed systems. OpenTracing compatible data model and instrumentation libraries include Go, Java, Node, Python, C++ and C#. Jaeger uses consistent upfront sampling with individual per service/endpoint probabilities and it has multiple storage backends: Cassandra, Elasticsearch, memory.

Uptrace is an open-source APM tool that supports distributed tracing, metrics, and logs. You can use it to monitor applications and set up automatic alerts to receive notifications via email, Slack, Telegram, and more. Uptrace is an open-source APM that supports OpenTelemetry tracing, metrics, and logs. You can use it to monitor applications and set up alerts to receive notifications via email, Slack, Telegram, and more. Uptrace collects and analyzes data from a variety of sources, including servers, databases, cloud providers, monitoring tools, and custom applications. It provides a unified view of the entire technology stack, enabling you to monitor the performance, availability, and health of your systems in real-time. Uptrace allows to monitor your whole application stack on a compact and informative dashboard. You get a quick overview for all your services, hosts, and systems.

BFE (Beyond Front End) is a modern layer 7 load balancer from baidu. BFE has a builtin plugin framework that makes it possible to develop new features rapidly by writing plugins. BFE is designed to provide every tenant a dedicated share of the instance. Each tenant’s configuration is isolated and remains invisible to other tenants. BFE supports HTTP, HTTPS, SPDY, HTTP2, gRPC, WebSocket, TLS, FastCGI, etc. Future support is planned for HTTP/3. BFE provides an advanced domain-specific language to describe routing rules which are easy to understand and maintain. BFE supports global load balancing and distributed load balancing for zone aware balancing, zone level failure resilience, overload protection etc. BFE provides a rich set of plugins for traffic management, security, observability, etc. BFE includes detailed built-in metrics for all subsystems. BFE writes various logs for trouble shooting, data analysis and visualization. BFE also supports distributed tracing.

Bun's goal is to help you write SQL, not to hide it behind awkward constructs. Bun uses database/sql and extends it in a compatible and idiomatic way. Out-of-the-box works with PostgreSQL, MySQL 5.7+, MSSQL, and SQLite. Keep your database schema updated with Go and SQL-based migrations. Provide initial data for your application with YAML fixtures. Modern app skeleton puts everything together and helps you get started. Bun is brought to you by uptrace/uptrace. Uptrace is an open-source APM tool that supports distributed tracing, metrics, and logs. You can use it to monitor applications and set up automatic alerts to receive notifications via email, Slack, Telegram, and others.

DeepFlow provides a universal map with Zero Code by eBPF for production environments, including your services in any language, third-party services without code and all cloud-native infrastructure services. In addition to analyzing common protocols, Wasm plugins are supported for your private protocols. Full-stack golden signals of applications and infrastructures are calculated, pinpointing performance bottlenecks at ease. Zero Code distributed tracing powered by eBPF supports applications in any language and infrastructures including gateways, service meshes, databases, message queues, DNS, and NICs, leaving no blind spots. Full-stack network performance metrics and file I/O events are automatically collected for each Span. Distributed tracing enters a new era, Zero Instrumentation. DeepFlow collects profiling data at a cost of below 1% with Zero Code, plots OnCPU/OffCPU function call stack flame graphs, and locates Full Stack performance bottleneck in the application.

This is a lightweight API Gateway and Management Platform that enables you to control who accesses your API, when they access it and how they access it. API Gateway will also record detailed analytics on how your users are interacting with your API and when things go wrong. An API Gateway sits in front of your application(s) and/or services and manages the heavy lifting of authorization, access control, and throughput limiting to your services. Ideally, it should mean that you can focus on creating services instead of implementing management infrastructure. For example, if you have written a really awesome web service that provides geolocation data for all the cats in NYC, and you want to make it public, integrating an API gateway is a faster, more secure route than writing your own authorization middleware. You can install Janus using docker or manually deploying the binary.

Event Horizon is a CQRS/ES toolkit for Go. Event Horizon is used in production systems but the API is not final! CQRS stands for Command Query Responsibility Segregation and is a technique where object access (the Query part) and modification (the Command part) are separated from each other. This helps in designing complex data models where the actions can be totally independent from the data output. ES stands for Event Sourcing and is a technique where all events that have happened in a system are recorded, and all future actions are based on the events instead of a single data model. The main benefit of adding Event Sourcing is traceability of changes which can be used for example in audit logging. Additionally, "incorrect" events that happened in the past (for example due to a bug) can be compensated for with an event that will make the current data "correct", as that is based on the events.