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Cortex Project might be a bit more popular than Google Cloud Dataproc. We know about 4 links to it since March 2021 and only 3 links to Google Cloud Dataproc. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Now if its more metric data you are using and want to do APM, prometheus is your man https://prometheus.io/, want to make prometheus your full time job? Deploy cortex https://cortexmetrics.io/, honorable mention in the metrics space, Zabbix, https://www.zabbix.com/ I've seen use cases of zabbix going way beyond its intended use its a fantastic tool. Source: 12 months ago
Yes, but also no. The Prometheus ecosystem already has two FOSS time-series databases that are complementary to Prometheus itself. Thanos and Mimir. Not to mention M3db, developed at Uber, and Cortex, then ancestor of Mimir. There's a bunch of others I won't mention as it would take too long. Source: 12 months ago
You can use the Remote write feature to send to a centralized location. It would have to be scalable like Cortex https://cortexmetrics.io/. Source: over 1 year ago
For a homelab I think prometheus + grafana is easy to get started and scales well. There are lots of ways to set up the architecture. Prometheus can write to a directory on a filesystem, it can be set to write to a remote server, and there are other projects to integrate object storage (s3, minio, etc) or influxdb for long term storage and downsampling. Source: almost 2 years ago
I have also a spark cluster created with google cloud dataproc. Source: about 1 year ago
Specifically, we heavily rely on managed services from our cloud provider, Google Cloud Platform (GCP), for hosting our data in managed databases like BigTable and Spanner. For data transformations, we initially heavily relied on DataProc - a managed service from Google to manage a Spark cluster. - Source: dev.to / about 2 years ago
With that, the best way to maximize processing and minimize time is to use Dataflow or Dataproc depending on your needs. These systems are highly parallel and clustered, which allows for much larger processing pipelines that execute quickly. Source: over 2 years ago
Thanos.io - Open source, highly available Prometheus setup with long term storage capabilities.
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
Prometheus - An open-source systems monitoring and alerting toolkit.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
IRONdb - Circonus delivers Machine Data Intelligence for the most demanding use cases. Collect, store, manage, and analyze IoT and monitoring data at unprecedented volume and frequency.
HortonWorks Data Platform - The Hortonworks Data Platform is a 100% open source distribution of Apache Hadoop that is truly...