#python #airflow #airflow_operators #aws #aws_ec2 #aws_s3 #aws_sdk #cassandra #cassandra_database #cloudformation #cluster #data #data_engineering #data_engineering_pipeline #data_lake #data_modeling #data_warehouse #etl_pipeline #infrastructure #postgres #postgresql_database

https://github.com/san089/Udacity-Data-Engineering-Projects

#cplusplus #cdn #cluster #hls #http_flv #http_streaming #live #live_streaming #media_server #rtmp #rtmp_server #srs

https://github.com/ossrs/srs

#go #cluster #cncf #containers #kubernetes #minikube

https://github.com/kubernetes/minikube

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

https://github.com/VictoriaMetrics/VictoriaMetrics

#go #cloud_native #cluster_management #distributed_cloud #edge_cloud #hybrid_cloud #kubernetes #multicloud #orchestration #out_of_the_box #public_cloud

https://github.com/clusternet/clusternet

#typescript #apache_kafka #big_data #cluster_management #event_streaming #hacktoberfest #kafka #kafka_brokers #kafka_client #kafka_cluster #kafka_connect #kafka_manager #kafka_producer #kafka_streams #kafka_ui #opensource #streaming_data #streams #web_ui

https://github.com/provectus/kafka-ui

#hcl #argocd #aws #aws_eks_cluster #bottlerocket #cluster_autoscaler #eks #eks_addons #eks_clusters #eks_fargate #fargate #fluentbit #fluxcd #helm_charts #ingress_controller #kubernetes #spark #spark_operator #terraform #traefik #yunikorn

https://github.com/aws-ia/terraform-aws-eks-blueprints

#go #alicloud #aws #azure #cluster #controller #equinixmetal #extensibility #gardener #gcp #golang #hetzner #k8s #kubernetes #kubevirt #metalstack #onmetal #openstack #vsphere

https://github.com/gardener/gardener

#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 #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