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zipkin
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Creative Commons Attribution 4.0 | Apache License 2.0 |
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docs
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.NET Aspire is the best way to experiment with Dapr during local development
Dapr documentation
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Picking an architecture
I agree with the general sentiment here that you should try to keep things simple as long as possible. In addition to that, try to use frameworks such as Dapr, that allow you to postpone certain architectural decisions. Since Dapr runs everywhere where Kubernetes runs, it doesn't really matter which cloud provider you pick. Also, when it comes to pub/sub brokers, state stores, or secret stores, when using Dapr components you can easily swap those out.
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Mechanism for managing faulty consumer in asynchronous event broadcast in microservices / modular monolith
I'm mostly familiar with orchestration type sagas, and there I usually include retries when calling services and compensation actions in case calls completely fail. It really helps if you're using a framework, such as Dapr, to do most of the heavy lifting. You can apply resiliency policies to service calls and with the latest version, there's now a Workflow API to orchestrate your services.
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Service Mesh Considerations
One other option that is worth mentioning is Dapr. Dapr is a microservices building block that developers can use to develop microservices. There is a bit of overlap between Dapr and service meshes and the Dapr team has done a good job of comparing the two here. The biggest takeaway when comparing the two is that Dapr does not provide traffic routing/splitting. So if you need these capabilities, then yes, you will need a service mesh.
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Virtual Actors : Dapr vs Orleans
There was a similar issue with the code examples to get/set state, so I created a GitHub issue for them.
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Image Recognition App using GoLang | Tensorflow | WasmEdge | Dapr | Docker
It is an Image Recognition Application made using Go Language, works on a Tensorflow model and it requires Dapr and WasmEdge runtime for execution.
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Tech Talks: Building Event-Driven Apps with Dapr in Kubernetes
Dapr Docs
zipkin
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Enhancing API Observability Series (Part 3): Tracing
When choosing distributed tracing tools, considerations include your technology stack, business requirements, and monitoring complexity. Zipkin, SkyWalking, and OpenTelemetry are popular distributed tracing solutions, each with its unique features.
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The Road to GraphQL At Enterprise Scale
From the perspective of the realization of GraphQL infrastructure, the interesting direction is "Finding". How to find the problem? How to find the bottleneck of the system? Distributed Tracing System (DTS) will help answer this question. Distributed tracing is a method of observing requests as they propagate through distributed environments. In our scenario, we have dozens of subgraphs, gateway, and transport layer through which the request goes. We have several tools that can be used to detect the whole lifecycle of the request through the system, e.g. Jaeger, Zipkin or solutions that provided DTS as a part of the solution NewRelic.
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OpenTelemetry Exporters - Types and Configuration Steps
Zipkin is a distributed tracing system used for tracking and analyzing how requests move through complex systems, especially in setups with many interconnected services, known as microservices.
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The Complete Microservices Guide
Distributed Tracing: Middleware for distributed tracing like Jaeger and Zipkin helps monitor and trace requests as they flow through multiple microservices, aiding in debugging, performance optimization, and understanding the system's behavior.
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zipkin VS openobserve - a user suggested alternative
2 projects | 8 Sep 2023
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The Unreasonable Effectiveness of Sequence Diagrams in MermaidJS
For microservice tracing, you might want to look at Zipkin [0], or OpenTelemetry [1]
[0] https://zipkin.io/
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Analytics for aspnet core apis?
I’ve not used a self-hosted solution before, but here’s one I found. https://zipkin.io/
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Show HN: Uptrace – open-source APM (alternative to Datadog, NewRelic)
> IMO the reason these vendors can and do charge so much is not because telemetry software is hard.
I always saw it as "they are charging for their polished UI/experience"
The UI of https://zipkin.io/ versus DataDog is kind of... not really in the same ballpark?
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Is there a beginners guide to adding observability to your applications?
There are the zipkin https://zipkin.io/ and jaeger https://www.jaegertracing.io/ packages/components you can use both have quickstarts if you consider that to be a beginner's guide.
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How to monitor Python application performance
Zipkin, which was developed by Twitter, is an open source tool for distributed tracing that can also be used to troubleshoot latency issues in your application. While Zipkin is Java-based, py_zipkin is an implementation for Python.
What are some alternatives?
dapr-wasm - A template project to demonstrate how to run WebAssembly functions as sidecar microservices in dapr
skywalking - APM, Application Performance Monitoring System
CAP - Distributed transaction solution in micro-service base on eventually consistency, also an eventbus with Outbox pattern
sentry-java - A Sentry SDK for Java, Android and other JVM languages.
Orleans.CosmosDB - Orleans providers for Azure Cosmos DB
Fluentd - Fluentd: Unified Logging Layer (project under CNCF)
jaeger - CNCF Jaeger, a Distributed Tracing Platform
opentelemetry-specification - Specifications for OpenTelemetry
dapr - Dapr is a portable, event-driven, runtime for building distributed applications across cloud and edge.
brave - Java distributed tracing implementation compatible with Zipkin backend services.
cloud-dapr-demo - Demo of Dapr runtime and seamless integration of cloud providers
signoz - SigNoz is an open-source observability platform native to OpenTelemetry with logs, traces and metrics in a single application. An open-source alternative to DataDog, NewRelic, etc. 🔥 🖥. 👉 Open source Application Performance Monitoring (APM) & Observability tool