Operations | Monitoring | ITSM | DevOps | Cloud

There is more data available to us than ever. Storing this data is important — but deciding on the right type of data storage solution is not so clear. This article explores two primary types of big data storage: data lakes and data warehouses. We’ll examine the benefits of each, then discuss the key differences between a data lake and a data warehouse, so you can decide on the best approach for your business.

In this blog series, we’ll explore how Cribl Stream can leverage your existing cross-domain solution (CDS) to easily collect and send your log and metric data between disparate security domains or across air-gapped networks. The goal is to retain as much fidelity of the data as possible, deduplicating processes and simplifying management efforts.

Imagine this scenario: your platform appears to have an issue. Maybe it has gone down or maybe it has affected a large volume of users or perhaps just a few of those important ones; either way there is a significant problem with it. Users are complaining and are happy to shout about the platform not working on X (formally Twitter).

Have you ever wondered why some once-prominent companies now find themselves less popular, even overshadowed by smaller competitors? A prime example of this shift is Facebook. Although Facebook was the heartthrob of the 2000s, major issues like internet privacy and possible leaking of user records have made users more suspicious. Only 18% of American Facebook users think the platform protects their data and privacy.

While we built Grafana Loki as an open source log aggregation system that is cost effective and easy to operate, let’s face it: sometimes there is no time or bandwidth to mess around with self-managing and self-hosting. Luckily there’s the fully managed Grafana Cloud observability stack for log management. “Grafana Cloud is a no-BS platform. The engineering costs of hosting it ourselves would be much higher," says Jameel Al-Aziz, a software architect at Paradigm.

Circles X uses DORA DevOps best practices to build the first telco-as-a-service in Indonesia, helping partners to launch a digital telco.

In today’s hybrid cloud era, the volume and diversity of log data have exploded, which makes managing them ever so challenging. IT teams need to conquer the gush of logs by providing context whilst having an effective log management strategy. Without a powerful log management solution, it all becomes too cumbersome. And even if you do get your hand around a good log management platform, you’ll find yourself stuck with hefty licensing costs and impractical compliance issues.

Recently, I sat down with Adelaide O’Brien, research vice president at IDC Government Insights, to discuss the current and future state of generative AI in the public sector worldwide. The full conversation is available to view on demand, but I also wanted to highlight some of the takeaways from the discussion.

Nginx metrics and logs monitoring are important to ensure that Nginx is performing as expected and to identify and resolve problems quickly. In this tutorial, you will install OpenTelemetry Collector to collect Nginx metrics and logs and then send the collected data to SigNoz for monitoring and visualization. In this tutorial, we cover: If you want to jump straight into implementation, start with this pre-requisites section.