NSQ Reviews

Datadog Reviews

NSQ mentions (7)

• Any thoughts on using Redis to extend Go's channels across application / machine boundaries?

  (G)NATS can do millions of messages per second and is the right tool for the job (either that or NSQ). Redis isn't even the fastest Redis protocol implementation, KeyDB significantly outperforms it. Source: over 1 year ago

• FileWave: Why we moved from ZeroMQ to NATS

  Bit.ly's NSQ is also an excellent message queue option. Source: over 1 year ago

• Infinite loop pattern to poll for a queue in a REST server app

  Queue consumers are interesting because there are many solutions for them, from using Redis and persisting the data in a data store - but for fast and scalable the approach I would take is something like SQS (as I advocate AWS even free tier) or NSQ for managing your own distributed producers and consumers. Source: over 1 year ago

• What are pros and cons of Go?

  Distrubition server engine ( for example websocket server multi ws gateway and worker pool,nsq.io realtime message queue and so on). Source: almost 2 years ago

• Distributed IM Service in Golang

  NSQ is a message queue implemented by Golang, and all messages are routed through NSQ. Reasons for choosing NSQ compared to other MQs: decentralized distribution (direct connection between production and consumption), low latency, No ordering, high performance, simple binary protocol. - Source: dev.to / about 2 years ago

Datadog mentions (5)

• Send the logs of your Shuttle-powered backend to Datadog

  Ideally, if we had access to the underlying infrastructure, we could probably install the Datadog Agent and configure it to send our logs directly to Datadog, or even use AWS Lambda functions or Azure Event Hub + Azure Functions in case we were facing some specific cloud scenarios. - Source: dev.to / 9 months ago

• I wanted a self hosted alternative to Atlassian status page so I build my own application !

  Currently supported : Datadog, Jenkins, DNS, HTTP. Source: over 1 year ago

• Datadog on Kubernetes: Avoiding Common Pitfalls

  Datadog is a powerful monitoring and security platform that gives you visibility into end-to-end traces, application metrics, logs, and infrastructure. While Datadog has great documentation on their Kubernetes integration, we've observed that there's some missed nuance that leads to common pitfalls. - Source: dev.to / almost 3 years ago

• Post-DockerCon spam

  .. Is to see you email address being silently distributed to every single company that I've watched a talk from. And now suddenly get several promotional spam emails per day from some 4-5 different domains like instana.com, datadoghq.com, snyk.io, cockroachlabs.com (some of them send even multiple emails per day!). Source: about 3 years ago

• Never write a UserService again

  We're commonly doing this with logging, using services such as Loggly or DataDog. We're using managed databases, be it on AWS, Heroku or database-vendor-specific solutions. We're storing binaries on S3. Externalising user authentication and authorization might be a good candidate as well. - Source: dev.to / about 3 years ago