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The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.

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Are disconnected RDP sessions ticking time bombs in your network?

I think we’ve all been there before – you log on to a server remotely via RDP, and do the needful – but don’t immediately log off. But then you get distracted by a phone call, an email, a chat, or a good old-fashioned physical interaction with another human being. So when it comes time clock out for the night, you shut down your computer or log off. Or maybe you’ve been working on a laptop and your VPN got interrupted.

Monitor your Redis Enterprise clusters with Datadog

Redis is an in-memory key-value data store that offers fast performance, flexible data structures, and multi-model databases, allowing it to handle a variety of use cases. Redis Enterprise enhances open source Redis with features designed to run distributed applications at scale, such as multi-tenancy, tiered data storage, active-active cluster replication, and support for up to five 9s of availability.

Analyzing Cardinality in Grafana Cloud and Grafana Enterprise Metrics

Cardinality Analysis of metrics is an enabler to reducing costs and focusing observability on the necessary metrics to identify and investigate where issues are occurring in your services. Grafana has added cardinality management dashboards to Grafana Cloud and Grafana Enterprise Metrics to make this an easy and fast process. In this introductory session, we will provide an overview of the Grafana Cardinality features and offer a set of discovery questions to help you with the process.

The ins, outs, and benefits of using Grafana Loki as a backend logging solution

As organizations have moved from monolithic to microservice-based architectures, there has been an explosion in the volume of logs generated. Most logging solutions create a full index of the logs and use SSD drives, which results in costly compute and storage resources for logs that are mostly write once, read never. We created Grafana Loki to solve these problems. Loki only indexes the metadata of the log lines, relies on inexpensive object storage, and is architected for scalability. In addition, Loki takes advantage of parallelism and sharding that results in fast query performance. In this session, we will discuss the benefits of using Loki as a backend logging solution.

Video: Get started with Grafana Mimir in minutes

Since we launched Grafana Mimir — the most scalable, most performant open source time series database in the world — we have answered many of your questions about our latest open source project, including how to pronounce it. (All together now: /mɪ’mir/.) We have walked through how we scaled Grafana Mimir to 1 billion active series. And we will be hosting webinars to showcase cutting-edge features like query sharding and the two-stage compactor.

Ask Miss O11y: Logs vs. Traces

Ah, good question! TL;DR: Trace instead of log. Traces show connection, performance, concurrency, and causality. Logs are the original observability, right? Back in the day, I did all my debugging with `printf.` Sometimes I still write `console.log(“JESS WAS HERE”)` to see that my code ran. That’s instrumentation, technically. What if I emitted a “JESS WAS HERE” span instead? What’s so great about a span in a trace? Yeah, and so do logs in any decent framework.