Based on our record, Grafana seems to be a lot more popular than Amazon EMR. While we know about 197 links to Grafana, we've tracked only 10 mentions of Amazon EMR. 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.
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 1 year ago
I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago
This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: almost 2 years ago
Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
Check out https://aws.amazon.com/emr/. Source: about 2 years ago
Monitoring application logs is a crucial aspect of the software development and deployment lifecycle. In this post, we'll delve into the process of observing logs generated by Docker container applications operating within HashiCorp Nomad. With the aid of Grafana, Vector, and Loki, we'll explore effective strategies for log analysis and visualization, enhancing visibility and troubleshooting capabilities within... - Source: dev.to / about 2 months ago
To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along. - Source: dev.to / about 1 month ago
Visualization and Analysis: Choose a tool with intuitive and customizable dashboards, charts, and visualizations. A question to ask is, "Are the visualization features of this tool user-friendly and adaptable to our team's specific needs?" Tools like Grafana and Kibana provide powerful visualization capabilities. - Source: dev.to / about 1 month ago
Prometheus: Open-source monitoring system. Often used together with Grafana. - Source: dev.to / 2 months ago
In example above, we use 2 additional parameters: code (HTTP response code) and page (page identifier), which provide detailed statistics. For example, you can build such graphs in Grafana:. - Source: dev.to / 3 months ago
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Prometheus - An open-source systems monitoring and alerting toolkit.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
Zabbix - Track, record, alert and visualize performance and availability of IT resources