Looker is a business intelligence platform with an analytics-oriented application server that sits on top of relational data stores. The Looker platform includes an end-user interface for exploring data, a reusable development paradigm for creating data discovery experiences, and an extensible API set so the data can exist in other systems. Looker enables anyone to search and explore data, build dashboards and reports, and share everything easily and quickly.
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Based on our record, Open Telemetry seems to be a lot more popular than Looker. While we know about 162 links to Open Telemetry, we've tracked only 14 mentions of Looker. 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.
The open source projects Fastly uses and the foundations we partner with are vital to Fastly’s mission and success. Here's an unscientific list of projects and organizations supported by the Linux Foundation that we use and love include: The Linux Kernel, Kubernetes, containerd, eBPF, Falco, OpenAPI Initiative, ESLint, Express, Fastify, Lodash, Mocha, Node.js, Prometheus, Jenkins, OpenTelemetry, Envoy, etcd, Helm,... - Source: dev.to / 9 days ago
OpenTelemetry is an open-source observability framework for generating, capturing, and collecting telemetry data such as logs, metrics, and traces from software services and applications. For this article, we will focus on configuring traces in the system, so you can see the entire distributed operation of processing a payment. - Source: dev.to / 8 days ago
In addition, we now have a common standard for defining and correlating traces, metrics, and logs: OpenTelemetry. Most Observability vendors are all in on OpenTelemetry, which means that it has become the de-facto standard for instrumenting code (and also the second most popular CNCF project in terms of contributions 🎉). It also means that these vendors all ingest the same data, and it’s up to how those vendors... - Source: dev.to / 17 days ago
I contend there is using a worker runtime and OpenTelemetry. - Source: dev.to / 24 days ago
OpenTelemetry is an open-source observability framework that provides mechanisms for creating and sending traces, metrics, and logs. It consists of various elements such as protocols for transmission and SDKs for different programming languages. In this article, we will explore how OpenTelemetry achieves distributed tracing. - Source: dev.to / 28 days ago
Then in the "foldername" you can have 5 folders, each one for each of the groups. This means that when group1 enters looker.com, his default page will be the "foldername", which contains group1folder (he cannot see the rest of the folders if you have set the permissions correctly for each folder). Source: over 1 year ago
Even if you want to make Wide Tables, combining fact and dimensions is often the easiest way to create them, so why not make them available? Looker, for example, is well suited to dimensional models because it takes care of the joins that can make Kimball warehouses hard to navigate for business users. - Source: dev.to / over 1 year ago
We take daily snapshots of test results, aggregate them, and send Looker dashboards to the appropriate teams. - Source: dev.to / over 2 years ago
Dashboard: I like to use Datastudio because it's easy (just like using google sheets), but you can also try out Looker. Source: over 2 years ago
For Growth and larger, I would recommend Looker. The only reason I wouldn't recommend it for the smaller company stages is that the cost is much higher than alternatives such as Metabase. With Looker, you define your data model in LookML, which Looker then uses to provide a drag-and-drop interface for end-users that enables them to build their own visualizations without needing to write SQL. This lets your... - Source: dev.to / over 2 years ago
SigNoz - Open source alternative to Datadog
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Microsoft Power BI - BI visualization and reporting for desktop, web or mobile
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Sisense - The BI & Dashboard Software to handle multiple, large data sets.