Stream-Framework VS Grafana

I have looked into a getstream.io integration, however it seems that the Ruby SDK is really treated as a second class citizen. There's bugs with the documented API (I'm having issues even creating users and querying users), the usage of the gem is low and there is an open issue since May that no one has even looked at, which doesn't give me hope for long term support.

An ultralight social media app with no dependencies that can run on shared web hosting. It's an API like Getstream, so F/E is up to you. I've had a fork of it in production for 2.5 years on a subscription site that generates a small income.

Now, I'm seeking your advice and opinions. If you have experience using Stream or MirrorFly for chat implementation, I'd greatly appreciate any insights you can provide. Here are some questions I have:

Think about the edge that you can have over thousands other people looking for a job like you. One of the ways to do it – tailor your (even small) experience to the company you are applying to. E.g. Let's take a company like Stream that have an open-source Swift SDK, try to contribute to their SDK, maybe close some `good-first-issue`s here and there, do some documentation improvements, enrich their example app. So that when you feel like you are ready to knock their door – you already have an edge over others – you don't need onboarding (because you already know most of their codebase, you even completed your first few tasks while yet not being employed!)

This is absolutely absurd. I mean I 100% believe it happens, it's just absurd that the Tier 1 admin bot is this bad.

I too firmly believe the tier 1 admins are just this program - https://getstream.io/ And reddit doesn't want to admit that humans are not actually reviewing things

Really depends on so many variables, and comes down to knowing the audience. I built a lightweight social network api platform to do a lot of what getstream.io and OSSN does, but the way users engaged with it was nothing like what I expected. One use case, for example, would have been mostly satisfied with WordPress and Mailchimp. Forums are very familiar to people and still used by a lot of "I don't do social media" types. At the risk of making a sweeping generalization, if you have an older target audience they will be happy with a forum. If you have a younger target audience they will prefer the sequential post / react style of interacting, like Discord or Instagram.

Monitoring application logs is a crucial aspect of the software development and deployment lifecycle. In this post, we'll delve into the process of observing logs generated by Docker container applications operating within HashiCorp Nomad. With the aid of Grafana, Vector, and Loki, we'll explore effective strategies for log analysis and visualization, enhancing visibility and troubleshooting capabilities within your Nomad environment.

To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along.

Visualization and Analysis: Choose a tool with intuitive and customizable dashboards, charts, and visualizations. A question to ask is, "Are the visualization features of this tool user-friendly and adaptable to our team's specific needs?" Tools like Grafana and Kibana provide powerful visualization capabilities.

Prometheus: Open-source monitoring system. Often used together with Grafana.

Grafana

Yes I'm aware that Grafana is open source but the method I used to find the API endpoints is far quicker than digging through hundreds of files in a codebase I'm not familiar with.

So, you will add one last container to allow us to visualize this data: Grafana, an open-source analytics and visualization platform that allows us to see traces and metrics simply. You can set Grafana to read data from both Tempo and Prometheus by setting them as datastores with the following grafana.datasource.yaml config file:

In example above, we use 2 additional parameters: code (HTTP response code) and page (page identifier), which provide detailed statistics. For example, you can build such graphs in Grafana:

Robin switched to the Grafana dashboard tab, and sure enough, the 5xx volume on web service was rising. It had not hit the critical alert thresholds yet, but customers had already started noticing.