#typescript #javascript #go #opensource #kafka #reactjs #metrics #prometheus #self_hosted #tracing #stream_processing #druid #gsoc #kafka_streams #observability #distributed_tracing #application_monitoring #jaegertracing #opentelemetry #open_telemetry

https://github.com/SigNoz/signoz

#java #database #grafana #hacktoberfest #influxdb #iot #low_latency #metrics #monitoring #postgres #postgresql #questdb #simd #sql #time_series #timeseries_database #tsdb

https://github.com/questdb/questdb

#java #api_management #apm #authentication #circuit_breaker #configuration_management #metrics #microservices #multi_runtime #proxyless #rate_limiter #router #service_discovery #service_mesh

https://github.com/polarismesh/femas

#go #metrics #prometheus #tsdb

https://github.com/grafana/mimir

#go #dashboard #database_monitoring #ebpf #kubernetes #log_analysis #metrics #microservice #monitoring #network_monitoring #observability #postgresql_monitoring #prometheus #service_map

https://github.com/coroot/coroot

#c_lang #c #cloudnative #data_collector #fluent_bit #fluentd #forwarder #log #logging #metrics #sql_queries #stream_processing #traces

https://github.com/fluent/fluent-bit

#python #instrumentation #metrics #prometheus

https://github.com/prometheus/client_python

#java #cpu #deep_learning #docker #gpu #kubernetes #machine_learning #metrics #mlops #optimization #pytorch #serving

https://github.com/pytorch/serve

#other #adblock #adguard #ads #blacklist #blocklist #coins #dns #domains #fake #filterlist #hosts #malware #metrics #phishing #pi_hole #privacy #scam #telemetry #threat_intelligence_feeds #tracking

https://github.com/hagezi/dns-blocklists

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

https://github.com/prometheus/node_exporter

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

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

#python #computer_science #computer_science_rankings #conference #dblp #faculty #metrics #ranking

https://github.com/emeryberger/CSrankings

#python #classification #coco #computer_vision #deep_learning #hacktoberfest #image_processing #instance_segmentation #low_code #machine_learning #metrics #object_detection #oriented_bounding_box #pascal_voc #python #pytorch #tensorflow #tracking #video_processing #yolo

Supervision is a powerful tool for building computer vision applications. It allows you to easily load datasets, draw detections on images or videos, and count detections in specific zones. You can use any classification, detection, or segmentation model with it, and it has connectors for popular libraries like Ultralytics and Transformers. Supervision also offers customizable annotators to visualize your data and utilities to manage datasets in various formats. By using Supervision, you can streamline your computer vision projects and make them more reliable and efficient. Additionally, there are extensive tutorials and documentation available to help you get started quickly.

https://github.com/roboflow/supervision

#c_lang #bigdata #cloud_native #cluster #connected_vehicles #database #distributed #financial_analysis #industrial_iot #iot #metrics #monitoring #scalability #sql #tdengine #time_series #time_series_database #tsdb

TDengine is a powerful, open-source time-series database designed for handling large amounts of data from IoT devices, connected cars, and industrial IoT. Here are the key benefits It can handle billions of data collection points efficiently, outperforming other time-series databases in data ingestion, querying, and compression.
- **Simplified Solution** Designed for cloud environments, it supports distributed design, sharding, partitioning, and Kubernetes deployment.
- **Ease of Use** Makes data exploration and access efficient through features like super tables and pre-computation.
- **Open Source**: Available under open source licenses with an active developer community.

Using TDengine helps you manage and analyze large-scale time-series data efficiently, making it ideal for various IoT and industrial applications.

https://github.com/taosdata/TDengine

#go #alerting #ccf #metrics #monitoring #nightingale #observability #open_falcon #time_series #tsdb

Nightingale is a free, open-source monitoring tool designed for cloud environments. It combines data collection, visualization, monitoring alerts, and data analysis into one platform. This tool supports multiple time-series databases like Prometheus and VictoriaMetrics, and it has advanced alert management features, including alert rules and notifications. It also offers high-performance visualization with various dashboard templates and supports different data collectors. Using Nightingale, you can manage alerts efficiently, reduce disturbances, and ensure seamless collaboration. This makes it a powerful tool for enterprises to monitor and analyze their systems effectively.

https://github.com/ccfos/nightingale

#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

#rust #events #forwarder #logs #metrics #observability #parser #pipeline #router #rust #stream_processing #vector

Vector is a powerful tool for managing your observability data, such as logs and metrics. It allows you to collect, transform, and route your data to any vendor you choose, giving you full control. Vector is reliable, fast (up to 10x faster than alternatives), and secure. It helps reduce costs, improve data quality, and consolidate agents, making your observability processes more efficient and reliable. With a strong community support and extensive documentation, Vector is used by many big companies and is downloaded over 100,000 times daily. This makes it a valuable tool for anyone looking to manage their data effectively.

https://github.com/vectordotdev/vector