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Prometheus vs Stackdriver: What are the differences?
Prometheus: An open-source service monitoring system and time series database, developed by SoundCloud. Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true; Stackdriver: Monitoring, logging, and diagnostics for applications on Google Cloud Platform and AWS. Google Stackdriver provides powerful monitoring, logging, and diagnostics. It equips you with insight into the health, performance, and availability of cloud-powered applications, enabling you to find and fix issues faster.
Prometheus belongs to "Monitoring Tools" category of the tech stack, while Stackdriver can be primarily classified under "Cloud Monitoring".
Some of the features offered by Prometheus are:
- a multi-dimensional data model (timeseries defined by metric name and set of key/value dimensions)
- a flexible query language to leverage this dimensionality
- no dependency on distributed storage
On the other hand, Stackdriver provides the following key features:
- Monitoring
- Logging
- Diagnostics
"Powerful easy to use monitoring" is the primary reason why developers consider Prometheus over the competitors, whereas "Monitoring" was stated as the key factor in picking Stackdriver.
Prometheus is an open source tool with 25K GitHub stars and 3.56K GitHub forks. Here's a link to Prometheus's open source repository on GitHub.
Uber Technologies, Slack, and DigitalOcean are some of the popular companies that use Prometheus, whereas Stackdriver is used by Kalibrr, Nuuvem, and Verba. Prometheus has a broader approval, being mentioned in 243 company stacks & 85 developers stacks; compared to Stackdriver, which is listed in 58 company stacks and 18 developer stacks.
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.
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.
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/
Pros of Prometheus
- Powerful easy to use monitoring42
- Flexible query language38
- Dimensional data model31
- Alerts25
- Active and responsive community21
- Extensive integrations20
- Easy to setup18
- Beautiful Model and Query language11
- Easy to extend7
- Nice6
- Written in Go3
- Easy for monitoring1
- Good for experimentation1
Pros of Stackdriver
- Monitoring18
- Logging11
- Alerting8
- Tracing7
- Uptime Monitoring6
- Error Reporting5
- Multi-cloud4
- Production debugger3
- Many integrations2
- Configured basically with GAE1
- Backed by Google1
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Cons of Prometheus
- Just for metrics10
- Needs monitoring to access metrics endpoints5
- Bad UI4
- Supports only active agents2
- Written in Go2
- Not easy to configure and use2
- Requires multiple applications and tools1
- TLS is quite difficult to understand1
Cons of Stackdriver
- Not free2
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We primarily use Prometheus to gather metrics and statistics to display them in Grafana. Aside from that we poll Prometheus for our orchestration-solution "JCOverseer" to determine, which host is least occupied at the moment.
Gather metrics from systems and applications. Evaluate alerting rules. Alerts are pushed to OpsGenie and Slack.
We primarily use Prometheus to gather metrics and statistics to display them in Grafana.