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Grafana Alternatives
Similar projects and alternatives to Grafana
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Home Assistant
:house_with_garden: Open source home automation that puts local control and privacy first.
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Puter.js
Puter.js - The Backend for AI-Generated Apps. One-shot full-stack apps with your existing AI coding tool. Puter.js gives you Auth, Storage, DB, AI & more, with up to 90% fewer AI tokens than other backend platforms.
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terraform
Terraform enables you to safely and predictably create, change, and improve infrastructure. It is a source-available tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned.
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PostgreSQL
Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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signoz
SigNoz is an open-source, OpenTelemetry-native observability platform for your team and their AI agents. Get logs, metrics, and traces in one tool with features like APM, distributed tracing, log management, infra monitoring, etc. Combined with SigNoz MCP and a native AI teammate (in SigNoz Cloud) it helps you build more resilient apps.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better Grafana alternative or higher similarity.
Grafana discussion
Grafana reviews and mentions
Posts with mentions or reviews of Grafana.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2026-06-26.
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How To Learn Go Fast: A Practical Roadmap For Senior Backend Developers
grafana/grafana — Go backend with rich frontend,
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OpenTelemetry: The Foundation of Modern Cloud-Native Observability — Traces, Metrics, Logs, and the Future of Observability
Grafana Labs ecosystem Datadog New Relic Dynatrace Splunk Elastic Custom data lakes and analytics systems
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Grafana Labs internal source code accessed
Their whole repo had been made public !!!!
https://github.com/grafana/grafana
/s
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The Performance Battle the hardening of Vault and OWASP: What Matters
A common mistake we see is teams rejecting Vault hardening because they assume it will add 400ms+ p99 latency, a myth perpetuated by outdated blog posts from 2020. Our benchmarks of Vault 1.15 show that OWASP-compliant TLS 1.3 and rate limiting add only 12ms p99 latency, not 400ms. Before deciding against hardening, run the first code example (vault_owasp_benchmark.py) against your own Vault deployment to get real numbers for your workload. Use tools like https://github.com/influxdata/telegraf to collect latency metrics from production, and https://github.com/grafana/grafana to visualize percentiles over time. For read-heavy workloads (10k+ requests per second), the latency overhead is even lower (under 8ms p99) because TLS 1.3 has lower handshake overhead than TLS 1.2. We worked with a SaaS company that rejected hardening for 6 months due to latency fears, only to find after benchmarking that the overhead was 9ms p99, well within their 100ms SLA. They implemented hardening in 2 weeks, cut breach risk by 89%, and saw no customer impact. Always benchmark with your own traffic patterns, not generic numbers from the internet. Use the Go benchmark tool or Python script provided to test with your secret sizes, request patterns, and auth methods. If you see unexpected latency spikes, check for misconfigured cipher suites or rate limits that are too strict, not the hardening itself.
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Load Test
The JSON output file can be analyzed using various tools. One popular option is to use Grafana along with k6 Cloud. You can also use the built-in summary report that k6 provides at the end of the test run.
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Infrastructure as Code Toolbox - Final Thoughts and Future Work
Enable Application Logging, Monitoring and Alerting using services like CloudWatch or Grafana.
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The Real Cost of Silent Data Pipeline Failures
For monitoring infrastructure, Prometheus and Grafana are widely used for pipeline metrics collection and alerting. For orchestration that includes built-in run observability, Apache Airflow tracks run history, task durations, and failure states in a web UI. Python with SQLAlchemy is the standard stack for custom pipeline implementation with relational state management.
- 25 Trending Self-Hosted Projects on GitHub
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AI Is for DevOps: How a Neural Network Debugs Failed Pipelines
Grafana
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LLM Inference Optimization: Techniques That Actually Reduce Latency and Cost
Prometheus lets you see this in real time. The vLLM metrics endpoint exposes vllm:gpu_cache_usage_perc and vllm:num_requests_waiting via a /metrics endpoint. Wire those up to Grafana, and you’ll immediately see when you’re cache-bound versus compute-bound, which tells you exactly which optimization to reach for first.
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A note from our sponsor - SaaSHub
www.saashub.com | 21 Jul 2026
Stats
Basic Grafana repo stats
478
75,655
10.0
5 days ago
grafana/grafana is an open source project licensed under GNU Affero General Public License v3.0 which is an OSI approved license.
Grafana is marked as "self-hosted". This means that it can be used as a standalone application on its own.
The primary programming language of Grafana is TypeScript.
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developer.puter.com
Review ★★★★★ 9/10