#python #instrumentation #metrics #prometheus

https://github.com/prometheus/client_python

#go #blackbox_exporter #icmp #prometheus #prometheus_exporter

https://github.com/prometheus/blackbox_exporter

#go #asynq #dtm #elasticsearcg #filebeat #gitlab #go_queue #go_stash #go_zero #goctl #golang #gozero #grafana #harbor #jaeger #jenkins #k8s #kafka #microservices #modd #prometheus

https://github.com/Mikaelemmmm/go-zero-looklook

#lua #cdn #grafana #load_balancer #luajit #nginx #openresty #prometheus #tutorial #wrk

https://github.com/leandromoreira/cdn-up-and-running

#go #argocd #bash_script #ci_cd #devops #docker #git #github_actions #gitops #grafana #helm #jenkins #kubernetes #linux #networking #portainer #prometheus #yaml

https://github.com/Pradumnasaraf/DevOps

#go #automated_failover #business_continuity #database #database_management #devops #disaster_recovery #failover #high_availability #json_logging #k8s #kubectl_plugin #kubernetes #operator #postgres #postgresql #prometheus_exporter #replication #self_healing #sql #switchover

https://github.com/cloudnative-pg/cloudnative-pg

#go #host_metrics #machine_metrics #metrics #node_metrics #procfs #prometheus #prometheus_exporter #system_information #system_metrics

https://github.com/prometheus/node_exporter

#java #alert #apm #collector #data_collection #data_collector #distributed #jdbc #jmx #linux #monitor #monitoring #prometheus #self_hosted #selfhosted #snmp #springboot #ssh #uptime #uptime_monitor #zabbix

https://github.com/dromara/hertzbeat

#go #kubernetes #kubernetes_exporter #kubernetes_monitoring #metrics #monitoring #observability #prometheus #prometheus_exporter

https://github.com/kubernetes/kube-state-metrics

#go #cloud_native #ebpf #energy_consumption #energy_efficiency #energy_monitor #kubernetes #machine_learning #prometheus #prometheus_exporter #sustainability

https://github.com/sustainable-computing-io/kepler

#cplusplus #audio #c #c_plus_plus #dash #hevc #hls #live #live_streaming #low_latency #media_server #multimedia #prometheus_exporter #rtmp #server_side #srt #streaming #video #video_conferencing #video_streaming #webrtc

SRS (Simple Realtime Server) is a powerful and efficient video server that supports multiple streaming protocols like RTMP, WebRTC, HLS, and more. It works on various operating systems (Linux, Windows, macOS) and hardware architectures. You can easily set it up using Docker and stream videos using tools like FFmpeg or OBS. SRS is free and open-source, licensed under MIT, making it a great choice for developers to build high-quality streaming platforms. It also offers extensive documentation and community support, making it easier to get started and troubleshoot issues.

https://github.com/ossrs/srs

#go #cluster #database #grafana #graphite #influxdb #k8s #kubernetes #monitoring #observability #opentsdb #prometheus #promql #scalability #thanos #tsdb

VictoriaMetrics is a fast, cost-saving, and scalable solution for managing time series data. It offers high performance and reliability, making it ideal for businesses of all sizes. Key benefits include long-term storage for Prometheus and Graphite, powerful stream aggregation, support for large amounts of data from various sources, and easy setup with a small binary. It also supports multiple protocols and has features like anomaly detection, backup automation, and downsampling in its Enterprise version. This tool reduces storage costs and outperforms other solutions in terms of memory footprint and data compression, making it highly efficient for handling large datasets.

https://github.com/VictoriaMetrics/VictoriaMetrics

#typescript #alerting #analytics #business_intelligence #dashboard #data_visualization #elasticsearch #go #grafana #hacktoberfest #influxdb #metrics #monitoring #mysql #postgres #prometheus

Grafana is a free tool that helps you monitor and understand your data. You can use it to create graphs, dashboards, and alerts for your metrics and logs. It allows you to mix data from different sources and explore your data in various ways. You can also share dashboards with your team and set up notifications for important changes. This helps you make better decisions based on your data and keeps your team informed. To get started, you can download Grafana and follow the installation guides.

https://github.com/grafana/grafana

#python #cloud_native #cncf #deep_learning #docker #fastapi #framework #generative_ai #grpc #jaeger #kubernetes #llmops #machine_learning #microservice #mlops #multimodal #neural_search #opentelemetry #orchestration #pipeline #prometheus

Jina-serve is a tool that helps you build and deploy AI services easily. It supports major machine learning frameworks and allows you to scale your services from local development to production quickly. You can use it to create AI services that communicate via gRPC, HTTP, and WebSockets. It has features like built-in Docker integration, one-click cloud deployment, and support for Kubernetes and Docker Compose, making it easy to manage and scale your AI applications. This makes it simpler for you to focus on the core logic of your AI projects without worrying about the technical details of deployment and scaling.

https://github.com/jina-ai/serve

#go #alerting #graphing #hacktoberfest #metrics #monitoring #prometheus #time_series

Prometheus is a powerful tool for monitoring systems and services. It collects data from different sources, lets you query and analyze this data using a special language called PromQL, and can alert you when something goes wrong. Here are the key benefits It stores data in a way that makes it easy to analyze different aspects of your system.
- **Flexible queries** You can install Prometheus using precompiled binaries, Docker images, or by building it from source code.
- **Service discovery** It supports creating graphs and dashboards to visualize your data and send alerts when necessary.

Using Prometheus helps you keep a close eye on your systems, making it easier to identify and fix problems quickly.

https://github.com/prometheus/prometheus

#typescript #apm #application_monitoring #distributed_tracing #go #good_first_issue #jaeger #log #logs #metrics #monitoring #nextjs #observability #open_source #opentelemetry #prometheus #react #reactjs #self_hosted #tracing #typescript

SigNoz is a tool that helps you monitor and troubleshoot your applications easily. It combines logs, metrics, and traces in one place, allowing you to spot issues before they happen and fix problems quickly. It's cost-effective and open-source, similar to Datadog and New Relic but without the high costs. With SigNoz, you can monitor application performance, manage logs efficiently, track user requests across services, create customized dashboards, and set alerts for unusual activities. This makes it easier to identify and solve problems quickly, ensuring your application runs smoothly.

https://github.com/SigNoz/signoz

#c_lang #alerting #cncf #data_visualization #database #devops #docker #grafana #influxdb #kubernetes #linux #machine_learning #mongodb #monitoring #mysql #netdata #observability #postgresql #prometheus #raspberry_pi #statsd

Netdata is a powerful monitoring tool that helps you keep an eye on your servers, containers, and applications in real-time. Here’s what you need to know Netdata collects data every second, giving you immediate insights into your system's behavior.
- **Zero-Configuration** Netdata uses ML to detect anomalies and patterns in your metrics, helping you identify issues before they become critical.
- **Scalability** Netdata monitors everything from system resources to application logs, providing a complete view of your infrastructure.
- **Energy Efficiency**: Studies have shown that Netdata is the most energy-efficient monitoring tool, consuming fewer resources than other solutions.

Using Netdata benefits you by providing real-time, high-resolution monitoring, automated anomaly detection, and advanced visualization tools, all while being highly scalable and energy-efficient. This makes it easier to manage and troubleshoot your systems effectively.

https://github.com/netdata/netdata

#python #ansible #aws #azure #coding #containers #devops #docker #git #interview #interview_questions #kubernetes #linux #openstack #production_engineer #prometheus #python #sql #sre #terraform

This repository contains a collection of exercises and questions on various technical topics, including DevOps and SRE. It offers 2624 exercises that can be useful for preparing for interviews or learning new concepts. The repository covers a wide range of subjects such as networking, operating systems, cloud computing, and more. By using these resources, you can improve your skills in areas like software development, infrastructure management, and system reliability engineering. This helps you become more proficient in handling complex IT environments and enhances your career prospects in related fields.

https://github.com/bregman-arie/devops-exercises

#go #cloudnative #grafana #hacktoberfest #logging #loki #prometheus

Loki is a log aggregation system inspired by Prometheus but designed specifically for logs instead of metrics. It is cost-effective and easy to operate because it only indexes metadata (labels) about logs, not the full log content, which reduces storage and complexity. Loki works well with Kubernetes by automatically indexing pod labels and integrates natively with Grafana for easy log visualization. Its stack includes an agent (Alloy) to collect logs, Loki to store and query them, and Grafana to display them. This setup helps you efficiently manage and analyze logs with less cost and simpler operation compared to traditional logging systems[2].

https://github.com/grafana/loki

#go #aws #azure #cncf #cost #cost_optimization #finops #gcp #k8s #kubernetes #monitoring #opencost #prometheus

OpenCost is a free, open-source tool that helps you see and understand the costs of running Kubernetes clusters and cloud services in real time. It breaks down costs by cluster, node, namespace, pod, and more, across multiple cloud providers like AWS, Azure, and GCP, and even supports on-premises setups. This lets you track where your money is going, spot expensive resources, and manage your cloud spending better. It integrates with Prometheus for metrics and offers a user-friendly web interface and APIs for easy cost monitoring and exporting. Using OpenCost helps you control and optimize your cloud and Kubernetes expenses efficiently[1][2][3][4].

https://github.com/opencost/opencost