OpenObserve on Cloudron - Lightweight, petabyte-scale observability
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- Main Page: https://openobserve.ai
- Git: https://github.com/openobserve/openobserve
- Licence: AGPL-3.0
- Docker: Yes
Demo
Summary: OpenObserve (O2 for short) is a cloud-native observability platform built specifically for logs, metrics, traces, analytics, RUM (Real User Monitoring - Performance, Errors, Session Replay) designed to work at petabyte scale.
Notes: Looks like a nice, lightweight logging solution built in rust.
I was able to get a working package going pretty easily (subject to more testing).
OpenObserve serves as a seamless replacement for Elasticsearch for users who ingest data using APIs and perform searches. OpenObserve comes with its own user interface, eliminating the need for separate installation.
You can reduce your log storage costs by ~140x compared to Elasticsearch by using OpenObserve. Below, we present the results from pushing logs from our production Kubernetes cluster to both Elasticsearch and OpenObserve using Fluent Bit.
Introduction Video
Features:
- Logs, Metrics, Traces: Comprehensive support for various data types.
- OpenTelemetry Support: Full compatibility with OTLP for logs, metrics, and traces.
- Real User Monitoring (RUM): Includes performance tracking, error logging, and session replay.
- Dashboards, Reports, Alerts: Features over 18 different chart types for comprehensive data visualization for on-the-fly analysis and reporting along with alerting.
- Pipelines: Enrich, redact, reduce, normalize data on the fly. Stream processing for logs to metrics and more.
- Advanced Embedded GUI: Intuitive and user-friendly interface.
- SQL and PromQL Support: Query logs and traces with SQL, and metrics with SQL and PromQL.
- Single Binary or HA Installation: Install using a single binary for small deployments or in HA mode for large deployments.
- Versatile Storage Options: Supports local disk, S3, MinIO, GCS, Azure Blob Storage.
- High Availability and Clustering: Ensures reliable and scalable performance.
- Dynamic Schema: Adapts to your data structure seamlessly.
- Built-in Authentication: Secure and ready to use.
- Ease of Operation: Designed for simplicity and efficiency.
- Seamless Upgrades: Hassle-free updates.
- Multilingual UI: Supports 11 languages, including English, Spanish, German, French, Chinese, and more.
For a full list of features, check the documentation.
Screenshots
Home
Logs
Traces (OpenTelemetry)
Trace details page
Golden metrics based on traces
Visualizations and Dashboards
Front end monitoring
Performance analytics
Session replay
Error tracking
Alerts
Streams
Ingestion
Pipeline
Pipeline
Function
IAM
SSO (Single Sign On)
RBAC (Role Based Access Control)
-
- Main Page: https://openobserve.ai
- Git: https://github.com/openobserve/openobserve
- Licence: AGPL-3.0
- Docker: Yes
Demo
Summary: OpenObserve (O2 for short) is a cloud-native observability platform built specifically for logs, metrics, traces, analytics, RUM (Real User Monitoring - Performance, Errors, Session Replay) designed to work at petabyte scale.
Notes: Looks like a nice, lightweight logging solution built in rust.
I was able to get a working package going pretty easily (subject to more testing).
OpenObserve serves as a seamless replacement for Elasticsearch for users who ingest data using APIs and perform searches. OpenObserve comes with its own user interface, eliminating the need for separate installation.
You can reduce your log storage costs by ~140x compared to Elasticsearch by using OpenObserve. Below, we present the results from pushing logs from our production Kubernetes cluster to both Elasticsearch and OpenObserve using Fluent Bit.
Introduction Video
Features:
- Logs, Metrics, Traces: Comprehensive support for various data types.
- OpenTelemetry Support: Full compatibility with OTLP for logs, metrics, and traces.
- Real User Monitoring (RUM): Includes performance tracking, error logging, and session replay.
- Dashboards, Reports, Alerts: Features over 18 different chart types for comprehensive data visualization for on-the-fly analysis and reporting along with alerting.
- Pipelines: Enrich, redact, reduce, normalize data on the fly. Stream processing for logs to metrics and more.
- Advanced Embedded GUI: Intuitive and user-friendly interface.
- SQL and PromQL Support: Query logs and traces with SQL, and metrics with SQL and PromQL.
- Single Binary or HA Installation: Install using a single binary for small deployments or in HA mode for large deployments.
- Versatile Storage Options: Supports local disk, S3, MinIO, GCS, Azure Blob Storage.
- High Availability and Clustering: Ensures reliable and scalable performance.
- Dynamic Schema: Adapts to your data structure seamlessly.
- Built-in Authentication: Secure and ready to use.
- Ease of Operation: Designed for simplicity and efficiency.
- Seamless Upgrades: Hassle-free updates.
- Multilingual UI: Supports 11 languages, including English, Spanish, German, French, Chinese, and more.
For a full list of features, check the documentation.
Screenshots
Home
Logs
Traces (OpenTelemetry)
Trace details page
Golden metrics based on traces
Visualizations and Dashboards
Front end monitoring
Performance analytics
Session replay
Error tracking
Alerts
Streams
Ingestion
Pipeline
Pipeline
Function
IAM
SSO (Single Sign On)
RBAC (Role Based Access Control)
@andreasdueren Wow, that would make me feel really clever
(goes to buy 10 more monitors for the sys admin flight deck
)
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@andreasdueren Wow, that would make me feel really clever
(goes to buy 10 more monitors for the sys admin flight deck
)
@marcusquinn haha
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@marcusquinn I would build a new room with floor to ceiling monitors on one wall. Reclining theatre seating and a kegerator. And a Hirsh keypad to prevent anyone except me from entering:)
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@marcusquinn I would build a new room with floor to ceiling monitors on one wall. Reclining theatre seating and a kegerator. And a Hirsh keypad to prevent anyone except me from entering:)
@crazybrad Ahah, the stuff of movies