Terraform Pull Request Automation
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Updated
Nov 1, 2025 - Go
Site reliability engineering (SRE) is a set of principles and practices that incorporates aspects of software engineering and applies them to infrastructure and operations problems. The main goals are to create scalable and highly reliable software systems. Site reliability engineering is closely related to DevOps, a set of practices that combine software development and IT operations, and SRE has also been described as a specific implementation of DevOps.
Terraform Pull Request Automation
Coroot is an open-source observability and APM tool with AI-powered Root Cause Analysis. It combines metrics, logs, traces, continuous profiling, and SLO-based alerting with predefined dashboards and inspections.
[Moved to cloudprober/cloudprober] An active monitoring software to detect failures before your customers do.
Layerform helps engineers create reusable environment stacks using plain .tf files. Ideal for multiple "staging" environments.
Kubernetes utility for exposing image versions in use, compared to latest available upstream, as metrics.
An active monitoring software to detect failures before your customers do.
Squzy - is a high-performance open-source monitoring, incident and alert system written in Golang with Bazel and love. Welcome to free SRE
A blazing fast tool for building data pipelines: read, process and output events. Our community: https://t.me/file_d_community
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Automatic SRE Superpowers within your Kubernetes cluster
Modern TCP tool and service for network performance observability.
Infrastructure-as-Code Platform Built for the Future
preq is the community-driven problem detector for Common Reliability Enumerations (CREs)⚡️
Slo-exporter computes standardized SLI and SLO metrics based on events coming from various data sources.
Marmot workflow execution engine
🚀🚀A high-performance and high-concurrency ssh tool written in Go. It is 10 times faster than Ansible. If you need much more performance and better ease of use, you will love it.
Better Living Through Statistics: Monitoring Doesn't Have To Suck