go-cache VS prometheus

Why I am creating this package? There is an already existing memory cache package which creates (One Janitor for One Cache) So I am running into issues where many go routines are running in our use cases causing the application to crash due to some memory leakage in the library itself or maybe multiple timers running at same time casuing the issue. Also this is a very popular github library but just doesn't fits when I am creating many cache instances. So thought about creating one package by myself.

I wrote a new library called VCache (https://github.com/microup/vcache). VCahce differs from go-cache (https://github.com/patrickmn/go-cache) by using a key of type "any" instead of a key of type "string". I compared the performance of both libraries on the main operations: Add, Get, and Delete.

https://github.com/patrickmn/go-cache is a well known one. My cache module is for it's fast full text search thus I recommend only using mine if u are using a pre-set cache.

github.com - patrickmn/go-cache

> when they went a year without a release.

Cause these libraries depend on other libraries that are probably extremely out of date at that point and have their own security vulnerabilities.

An example of a project that hasn't been dismissed as "abandoned", is https://github.com/patrickmn/go-cache because it explicitly doesnt have dependencies.

So yeah, if you have a semi-complex library, a year without a release is abandoned.

implementing runtime cache using map seems doable, i may just learn from github.com/patrickmn/go-cache but i dont understand what does it mean cache locally using text file. does it mean I have to:

Though pretty simple but have a look at https://github.com/patrickmn/go-cache

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.