Superset is gaining popularity among users especially Business/Product Owners and people who would like to create Business Intelligence graphs. Unfortunately it does not support Prometheus protocol at the moment of writing, therefore can not be used for DevOps’ish or Telemetry BI. This can be resolved with a very popular in Data Scientists circles data aggregation framework— Trino. It allows us to gather and transform data from different sources. Let’s see how it can help us extract data from VM and pass it into Superset for plotting and visualisation.
We have used Grafana and Prometheus for our operational insights, which collects performance metrics for us to see how our systems are performing. However, when we wanted to determine specific request patterns, we ran into issues related to high cardinality labelling. After some testing, the most promising results for resolving the issue have been using VictoriaMetrics.
VictoriaMetrics is a fast, cost-effective, and scalable monitoring solution and time-series database. VictoriaMetrics can be used for long-term remote storage for Prometheus. VictoriaMetrics is written in the Go programming language, so it installs without any external dependencies.
prometheus-push-client: Push metrics from your periodic long-running jobs to the existing Prometheus/VictoriaMetrics monitoring system.
As a fintech organization, we move billions of dollars every month. Our customers and merchants have entrusted us with a paramount responsibility. To handle our ever-growing business, building a robust observability stack is not just “nice to have”, but absolutely essential. And all of this starts with better monitoring and metrics.
In this article, I will describe a simple setup of centralized monitoring based on VictoriaMetrics for a couple of OpenShift clusters.
I’ve written a number of times recently about TSDBs at $JOB. For the last few years, we’ve been using OpenTSDB. It’s been…a mixed bag. Let’s get into how much happier we are with VictoriaMetrics…
When you integrate your software with bank APIs, you open a range of possibilities. But how do you control all of this? How can you monitor the services that support these interactions? Are they working correctly? The answer to these questions is monitoring, which can be achieved using Prometheus, AlertManager, Grafana, and VictoriaMetrics.
In this follow-up blog to Compiling a Percona Monitoring and Management v2 Client in ARM Architecture, we will show what changes are needed to get the latest versions of PMM working on ARM architecture. The latest versions will need the vmagent for supporting the newly added VictoriaMetrics functionality.
There’s two reasons we’ve written this post. The first is just that we think this stuff is interesting, and that the world can always use another detailed case study. The second, though, is that the work we’re going to describe is now part of our public API, and you can piggyback your own application metrics on top of ours. Our hope is, the more we describe this stuff, the more likely you are to get value out of it.
Ground Control Is Here to Help With Support From The Core Team.
Ground Control is here to provide enhanced technical support, architectural and security guidance, help with adoption, integration and performance analytics.