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Librato vs Prometheus: What are the differences?
Librato vs Prometheus: Key Differences
Librato and Prometheus are both monitoring and metrics collection tools, but they have key differences that make them suitable for different use cases.
Data Models: Librato uses a time-based data model, where metrics are sent at regular intervals and aggregated over time. Prometheus, on the other hand, uses a pull model where metrics are scraped from configured targets on demand. This allows Prometheus to provide a more real-time view of the system.
Query Language: Librato uses a proprietary query language called LQL, which allows users to perform complex queries and calculations on their metrics. Prometheus, on the other hand, uses a powerful query language called PromQL, which is specifically designed for working with time series data. PromQL offers a wide range of functionalities and allows for advanced data aggregation and manipulation.
Data Storage: Librato uses a cloud-based storage system to store metric data, making it easy to scale and manage. Prometheus, on the other hand, uses a local on-disk storage system, which is optimized for high performance and supports long-term data retention. This makes Prometheus more suitable for environments where data security and privacy are concerns.
Alerting and Notification: Librato has built-in alerting and notification features, allowing users to set up custom alerts based on their metrics. Prometheus, on the other hand, uses an external alert manager to handle alerting and notification. This provides more flexibility and allows users to use their preferred notification channels and integrations.
Service Discovery: Librato requires users to manually configure the targets they want to monitor. Prometheus, on the other hand, has built-in service discovery mechanisms that allow it to automatically discover and monitor new services as they come online. This makes Prometheus more suitable for dynamic environments where new services are constantly being added or removed.
In summary, Librato and Prometheus differ in their data models, query languages, data storage, alerting/notification capabilities, and service discovery mechanisms. Librato offers a cloud-based solution with powerful query capabilities and built-in alerting, while Prometheus provides a real-time view of the system with high-performance local storage and extensive service discovery capabilities.
Looking for a tool which can be used for mainly dashboard purposes, but here are the main requirements:
- Must be able to get custom data from AS400,
- Able to display automation test results,
- System monitoring / Nginx API,
- Able to get data from 3rd parties DB.
Grafana is almost solving all the problems, except AS400 and no database to get automation test results.
You can look out for Prometheus Instrumentation (https://prometheus.io/docs/practices/instrumentation/) Client Library available in various languages https://prometheus.io/docs/instrumenting/clientlibs/ to create the custom metric you need for AS4000 and then Grafana can query the newly instrumented metric to show on the dashboard.
Hi, We have a situation, where we are using Prometheus to get system metrics from PCF (Pivotal Cloud Foundry) platform. We send that as time-series data to Cortex via a Prometheus server and built a dashboard using Grafana. There is another pipeline where we need to read metrics from a Linux server using Metricbeat, CPU, memory, and Disk. That will be sent to Elasticsearch and Grafana will pull and show the data in a dashboard.
Is it OK to use Metricbeat for Linux server or can we use Prometheus?
What is the difference in system metrics sent by Metricbeat and Prometheus node exporters?
Regards, Sunil.
If you're already using Prometheus for your system metrics, then it seems like standing up Elasticsearch just for Linux host monitoring is excessive. The node_exporter is probably sufficient if you'e looking for standard system metrics.
Another thing to consider is that Metricbeat / ELK use a push model for metrics delivery, whereas Prometheus pulls metrics from each node it is monitoring. Depending on how you manage your network security, opting for one solution over two may make things simpler.
Hi Sunil! Unfortunately, I don´t have much experience with Metricbeat so I can´t advise on the diffs with Prometheus...for Linux server, I encourage you to use Prometheus node exporter and for PCF, I would recommend using the instana tile (https://www.instana.com/supported-technologies/pivotal-cloud-foundry/). Let me know if you have further questions! Regards Jose
We're looking for a Monitoring and Logging tool. It has to support AWS (mostly 100% serverless, Lambdas, SNS, SQS, API GW, CloudFront, Autora, etc.), as well as Azure and GCP (for now mostly used as pure IaaS, with a lot of cognitive services, and mostly managed DB). Hopefully, something not as expensive as Datadog or New relic, as our SRE team could support the tool inhouse. At the moment, we primarily use CloudWatch for AWS and Pandora for most on-prem.
this is quite affordable and provides what you seem to be looking for. you can see a whole thing about the APM space here https://www.apmexperts.com/observability/ranking-the-observability-offerings/
I worked with Datadog at least one year and my position is that commercial tools like Datadog are the best option to consolidate and analyze your metrics. Obviously, if you can't pay the tool, the best free options are the mix of Prometheus with their Alert Manager and Grafana to visualize (that are complementary not substitutable). But I think that no use a good tool it's finally more expensive that use a not really good implementation of free tools and you will pay also to maintain its.
Pros of Librato
- Easy setup14
- Great visualization8
- Heroku integration4
- Free tier3
- Alerting2
Pros of Prometheus
- Powerful easy to use monitoring47
- Flexible query language38
- Dimensional data model32
- Alerts27
- Active and responsive community23
- Extensive integrations22
- Easy to setup19
- Beautiful Model and Query language12
- Easy to extend7
- Nice6
- Written in Go3
- Good for experimentation2
- Easy for monitoring1
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Cons of Librato
Cons of Prometheus
- Just for metrics12
- Bad UI6
- Needs monitoring to access metrics endpoints6
- Not easy to configure and use4
- Supports only active agents3
- Written in Go2
- TLS is quite difficult to understand2
- Requires multiple applications and tools2
- Single point of failure1
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