In the beginning, there was the Log – or to be a bit more precise, there were application logs. At least that's how it was in the early days of application development, when raw log data itself was more often than not the point where troubleshooting began. Now, of course, the starting point for troubleshooting with cloud-based applications is much more likely to be an automatically-generated alert, or an indication on a monitoring dashboard that something isn't quite right.

Ivanti Device Control is all about securing your endpoints while also providing a detailed overview to quickly identify weak links in your environment. The latter has now become much simpler and quicker to perform! Our new Splunk connector enables you to connect directly to your Ivanti Device Control environment, feeding in all reported events and showing you the most important data in a single dashboard.

Customers need scale and flexibility from their cloud and this extends into supporting services such as monitoring and logging. Google Cloud’s Monitoring and Logging observability services are built on the same platforms used by all of Google that handle over 16 million metrics queries per second, 2.5 exabytes of logs per month, and over 14 quadrillion metric points on disk, as of 2020.

Monitoring is crucial if you want to see what happens in your system and JVM-based applications are not different. Well, some metrics, like memory and garbage collection, require special attention because they play a major role in your application performance. In this blog post, we will look into the key Java Virtual Machine (JVM) metrics that you should monitor if you care about performance and stability. Those are the memory, the garbage collection, and the JVM threads.

In a previous blog post, "Monitoring Kafka Performance with Splunk," we discussed key performance metrics to monitor different components in Kafka. This blog is focused on how to collect and monitor Kafka performance metrics with Splunk Infrastructure Monitoring using OpenTelemetry, a vendor-neutral and open framework to export telemetry data. In this step-by-step getting-started blog, we will.

Today’s business is powered by data. Success in the digital world depends on how quickly data can be collected, analyzed and acted upon. The faster the speed of data-driven insights, the more agile and responsive a business can become. Apache Kafka has emerged as a popular open-source stream-processing solution for collecting, storing, processing and analyzing data at scale.

You can add an action to log messages to Papertrail, a cloud-based logging service. You can send logs from Kiwi Syslog Server, or other servers or applications that can connect to the Internet. Then monitor, search, react to, and archive your messages on Papertrail.

The classic event viewer, introduced in June 2011, has been the heart of SolarWinds® Papertrail™. It’s where we spend most of our time, searching, tailing, and sharing event data. Over the last 10 years, Papertrail fans across the globe have shared their ideas with our development team and helped us improve and refine the event viewer.

Today, we’re excited to announce a new completely free pricing tier for observIQ: the 3-day free plan. With the observIQ free plan, you can ingest and index up to 3 gigabytes of logs per day with a 3 day rolling retention period.

In January 2021, we announced that starting with version 7.11, we would be changing the Apache 2.0 portions of Elasticsearch and Kibana source code to be dual licensed under Elastic License and SSPL, at the users’ discretion. As part of that change, we created Elastic License 2.0 (ELv2) as a permissive, fair-code license, which allows free use, redistribution, modification, and derivative works, with only three simple limitations, outlined in our original announcement.