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Prometheus vs Stackdriver: What are the differences?
Prometheus vs Stackdriver
Prometheus and Stackdriver are two popular monitoring and observability tools used to gain insights into the performance and health of applications and infrastructure. While they share some similarities, there are several key differences between the two.
Data Collection: Prometheus operates on a pull-based model where it scrapes metrics from various targets, such as applications and servers, at regular intervals. On the other hand, Stackdriver follows a push-based model where applications and services send their metrics to Stackdriver for processing.
Data Storage: Prometheus stores data in a time-series database, allowing for efficient querying and analysis. It provides a rich query language and retains data for a configurable period. In contrast, Stackdriver relies on Google Cloud storage and BigQuery for the storage and analysis of its data, making it more suitable for users already operating within the Google Cloud ecosystem.
Alerting and Notifications: Prometheus offers a flexible and powerful alerting system that allows users to define custom alerting rules and send notifications based on metric thresholds. Stackdriver also provides alerting capabilities but integrates more seamlessly with other Google Cloud services, such as Cloud Monitoring and Cloud Pub/Sub, for advanced alerting and notification mechanisms.
Integration and Ecosystem: Prometheus has a thriving open-source community, which has led to the creation of numerous integrations and exporters supporting various technologies and frameworks. Stackdriver, being a Google Cloud product, offers seamless integration with other Google Cloud services, including log management, tracing, and error reporting, providing a unified observability experience within the Google Cloud Platform.
Pricing: Prometheus is an open-source project, making it free to use and deploy. Users have full control over their infrastructure and incur only the costs associated with running and managing their Prometheus servers. Stackdriver, on the other hand, offers different pricing tiers based on the features and usage, with some basic functionality being available for free. Additional costs may be incurred for advanced features, increased storage, and usage beyond the free tier.
Scalability and Performance: Prometheus is known for its scalability, allowing users to scale horizontally by adding multiple instances. It can handle vast amounts of data and high ingestion rates efficiently. Stackdriver also offers scalability, leveraging the Google Cloud infrastructure, allowing users to handle large volumes of data. Stackdriver benefits from Google's extensive network and capacity for processing vast amounts of data in real-time.
In summary, the key differences between Prometheus and Stackdriver lie in their data collection models, storage mechanisms, alerting capabilities, integrations, pricing, and scalability. Prometheus provides users with greater flexibility and control, while Stackdriver offers tight integration with the Google Cloud Platform and advanced features suited for users already operating within that ecosystem.
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 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
Pros of Stackdriver
- Monitoring19
- Logging11
- Alerting8
- Tracing7
- Uptime Monitoring6
- Error Reporting5
- Multi-cloud4
- Production debugger3
- Many integrations2
- Backed by Google1
- Configured basically with GAE1
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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
Cons of Stackdriver
- Not free2
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What is Prometheus?
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