cosmo VS prometheus

At the very beginning, I was a solo founder and put my project WunderGraph (https://github.com/wundergraph/cosmo) on GitHub.

After a while, a CTO contacted me and asked if I could "support" his team and add some features that he wanted. After a month of sweating, we agreed that they'd pay me a monthly support subscription of $2k.

I learned a lot from the use cases, improved the software, and got some more users, which ultimately was enough of a story for VCs to raise a $3M seed round, which I think is quite cool as a first-time founder from Germany with zero connections, no YC friends, etc...

I quickly realized that I could not pull this off alone, so I teamed up with 3 fantastic Co-Founders who are responsible for the business side, marketing, sales, and engineering.

Fast forward two years and we're growing our customer base at a great pace and are slowly looking towards a Series A. I can tell though that the way from our first customer to where we are now was extremely tough. We're in enterprise sales, we had to switch our strategy at some point. Lots of learning, lots of pain.

In retrospect, I wouldn't say that the first customer is the hardest. Building a repeatable sales motion is much harder. Building a product, marketing, and sales process that all aligns well for repeatable sales is a lot of work.

Whoever tries this, good luck and please connect if you need help as a founder or want some advice. I love to help others to start their own business. It's hard, but it's also a life that I don't want to miss.

👉 Cosmo on GitHub: The code

By leveraging the astjson package, we were able to speed up our GraphQL API Gateway (Cosmo Router) while reducing the memory footprint. At the macro level, we were able to increase requests per second by 23% and reduced p99 latency by 44% over the previous version of Cosmo Router. At the micro level, we reduced the memory usage of a benchmark by 60%.

To learn more, go check out their docs here. Also, the WunderGraph Discord can be found here, if you have questions or issues you want to discuss.

For the future, we're working hard on adding compatibility with Federation 2.x features, If you find any bugs or have feature requests, please open an issue on GitHub.

If you want to learn more about Cosmo, check out the documentation.

WriteRequest::timeseries is a vector (https://github.com/prometheus/prometheus/blob/main/prompb/re...) and

Developers widely use Prometheus as a system for operational monitoring and alerting for their projects. Here is a list of tools for monitoring frontend services with Prometheus.

Just to give an example of the power of Go for CLI builds, you may have already used or at least heard of Docker, Kubernetes, Prometheus, Terraform, but what do they all have in common? They all have a large part of their usability via CLI and are developed in Go 🐿.

Distributed system administrators need mechanisms and tools for monitoring individual nodes in order to analyze the system and promptly detect anomalies. Developers also need effective mechanisms for analyzing, diagnosing issues, and identifying bugs in protocol implementations. Logging, tracing, and collecting metrics are common observability techniques to allow monitoring and obtaining diagnostic information from the system; most of the explored code bases use these techniques. OpenTelemetry and Prometheus are popular open-source monitoring solutions, which are used in many of the explored code bases.

Setting up monitoring for a system, especially one involving GRPC communication, provides crucial visibility into its operations. In this guide, we walked through the steps to instrument both a GRPC server and client with Prometheus metrics, exposed those metrics via an HTTP endpoint, and visualized them using Grafana. The Docker-Compose setup simplified the deployment of both Prometheus and Grafana, ensuring a streamlined process.

Alerting and Notification: Select a tool with flexible alerting mechanisms to proactively detect anomalies or deviations from defined thresholds. Consider asking questions like "Does this tool offer customizable alerting options and support notification channels that suit our team's communication preferences?" A tool like Prometheus provides robust alerting capabilities.

Prometheus

Prometheus is an open-source monitoring and alerting toolkit. It is designed to monitor highly dynamic containerized systems, making it an excellent choice for monitoring Docker containers and Kubernetes clusters.

wget https://github.com/prometheus/prometheus/releases/download/v2.46.0/prometheus-2.46.0.linux-amd64.tar.gz

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