We have been busy adding new features to our growing list of abilities. Logz.io Cloud SIEM is no exception. Throughout 2020 we have been enriching our security incident and event management tool, refining threat intelligence, adding new dashboards, and improving the user experience to ensure there’s an eagle’s-eye view of the security challenges that organizations face. Here are a few of those updates that we have recently put to production.

It is tempting to consider logging as a simple, solved problem. We write a log, check our file and, boom, we’ve cracked it. Yet those of us who have sat up at three in the morning, trawling through log files over an unreliable SSH connection, know that this is simply not enough. As your system scales, so too must the sophistication of your tooling. Your logging best practices must be scalable and ready to support your efforts.

Log files, which are the records of everything that has happened in your server, application, or framework, are generally unfiltered and huge. Going on for pages, these plain text files are packed with tons of information and are the initial go-to place for any troubleshooting. However, the challenge lies in reading, understanding, and interpreting log files, and ultimately pulling out the right piece of information required for analysis.

We’ve heard from customers about how important it is to be able to reliably operate your applications and infrastructure running on Google Cloud. In particular, observability is critical to reliable operations. To help you quickly gain insight into your Google Cloud environment, we’ve added 21 new features to Cloud Operations, the observability suite we launched earlier this year, which gives you access to all our operations capabilities directly from the Google Cloud Console.

The CSV file format is widely used across the business and engineering world as a common file for data exchange. The basic concepts of it are fairly simple, but unlike JSON which is more standardized, you’re likely to encounter various flavors of CSV data. This lesson will prepare you to understand how to import and parse CSV using Logstash before being indexed into Elasticsearch.

ChaosSearch is excited to announce its new integration with Opsgenie — Atlassian’s alerting and incident management platform. Using this integration, your teams can leverage the industry’s most powerful and comprehensive data monitoring and analytics capabilities channeled into a unified workflow through Opsgenie’s easy-to-use interface.

CIOs see data costs as their greatest logging challenge to overcome, according to this survey we collaborated on with IDC. If you’re running significant production operations, you’re almost certainly generating 100’s of GB of log data every day. Naturally, you’re also monitoring those logs and querying for incident investigations. However, most log data is never queried or analyzed, yet makes up the majority of logging costs.

Isn’t all logging pretty much the same? Logs appear by default, like magic, without any further intervention by teams other than simply starting a system… right?

In the field of open-source metrics and time series monitoring, it is quite clear today that Grafana is the most popular tool of choice. One of Grafana’s main advantages is its storage backend flexibility. It can support almost all the major time series datastores (Prometheus, InfluxDB, Elasticsearch, Graphite etc.), when each datastore has its own query language syntax, and slight differences in the actual Grafana UI and capabilities resulting from these differences.