Operations | Monitoring | ITSM | DevOps | Cloud

Note 8.3.0 has an issue that could cause creating and accessing snapshots against Azure snapshot repositories to fail authenticating when using SAS tokens. This impacts self-managed customers who have deployed 8.3.0. Elastic Cloud Azure deployments are not currently being upgraded to 8.3.0 and are not impacted as a result. Visibility is crucial for ensuring application performance but it can be difficult to efficiently scale monitoring across all your critical infrastructures, platforms, and services.

Frontend monitoring is a process of tracking and maintaining the health of an application’s client-side. It involves monitoring the availability, functionality, and performance of the client-side of an application. We can segment a web application into two parts. I.e., client-side and server-side.

So here we are…the final chapter. In Part 2 of this series, we started to drill down into some of the concepts that make Kafka great. We concluded that although terminology between MQTT and Kafka was similar (for example topics), they behaved quite differently under the hood. We also took a brief overview of Kafka Connect and how we can use some of the enterprise connectors to stream our data to other platforms. Yet we did learn that Kafka does have some shortfalls.

In a world where the customer’s digital experience is critical to business outcomes, it is crucial to understand how our applications are behaving. As businesses increasingly rely on the performance and availability of revenue-generating applications, the tolerance for downtime and slow response times has plummeted – so the response to production issues must be quick and effective.

Monitoring performance in front-end applications is vital. It focuses on the areas of the application users experience. These areas are slow rendering or frame rate, network request errors, and unresponsive user experience. Your application’s users expect the experience of using the application to be fast, responsive, and smooth. In the first article of this series, we discussed some tips for optimizing your React Native application performance.

Let’s check out together the new features and improvements included in the newest Pandora FMS release: Pandora FMS 763.

Honeycomb uses AWS Lambda as a core part of our query execution architecture; Lambda’s ability to quickly allocate lots of resources and charge us only for use is invaluable to keeping Honeycomb fast and affordable. Our total Lambda bill is easily accessible in the AWS Console, but how do we know which customers or application areas dominate this bill? How do we judge the cost of changes we make to our own software?

In the early days of log analysis, application developers would use their logging libraries to write logs to files stored on a disk. After years of relying on those libraries, they found that they were unable to monitor the performance of their applications anymore because they didn’t understand the way their logging libraries worked. This led to a shift from using log files stored on a disk to using Syslog.

This week we released v5.0 of StackState’s observability and AIOps platform, which introduces a rich set of new capabilities. Our latest release contains a little something for everyone responsible for reliably running business critical workloads in dynamic environments – SREs, DevOps, central platform teams, even business teams – and for new and existing users alike.