#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

#javascript #devops #monitoring #best_practices #incident_response #site_reliability_engineering #post_mortem #reliability #alerting #on_call #dev_ops #sre #observability #incident_management #chaos_engineering #sre_team #sre_teams #sre_culture #sre_classroom

https://github.com/upgundecha/howtheysre

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

https://github.com/VictoriaMetrics/VictoriaMetrics

#go #cloud_native #cncf #container_management #devops #hacktoberfest #istio #jenkins #k8s #kubernetes #kubernetes_platform_solution #kubesphere #multi_cluster #observability #servicemesh

https://github.com/kubesphere/kubesphere

#scala #akka #akka_http #declarative #documentation #functional_programming #http #http_client #http_requests #http_server #http4s #observability #openapi #play_framework #sttp #type_safe #zio

https://github.com/softwaremill/tapir

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

https://github.com/coroot/coroot

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

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

#go #continuous_profiling #developer_tools #devops #find_bottlenecks #golang #hacktoberfest #linux #monitoring #observability #performance #profiling #pyroscope #python #ruby

https://github.com/grafana/pyroscope

#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

#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

#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

#python #automation #data #data_engineering #data_ops #data_science #infrastructure #ml_ops #observability #orchestration #pipeline #prefect #python #workflow #workflow_engine

Prefect is a tool that helps you automate and manage data workflows in Python. It makes it easy to turn your scripts into reliable and flexible workflows that can handle unexpected changes. With Prefect, you can schedule tasks, retry failed operations, and monitor your workflows. You can install it using `pip install -U prefect` and start creating workflows with just a few lines of code. This helps data teams work more efficiently, reduce errors, and save time. You can also use Prefect Cloud for more advanced features and support.

https://github.com/PrefectHQ/prefect