ITOps vs. DevOps: where does one end and the other begin? These two terms are commonly confused even within the IT industry, which is understandable since neither is set in stone and they often overlap, especially when talking about infrastructure. What does each role encompass and how can you tell the difference between them?
As Stephen Marsland once said, “if data had mass, the earth would be a black hole.” A vast part of the immense amount of structured and unstructured data that we call “Big Data” is nothing but machine-originated log data. Logs are generated for a lot of different purposes – from security to debugging and troubleshooting. They constitute a gold mine of useful information and actionable insights if properly stored, managed, and analyzed.
Today we are releasing Graylog v3.0.1 with a few bug fixes. Many thanks to our community for reporting issues and contributing fixes!
Windows logs can be very informative, providing a perfect picture of the activities happening on an endpoint. Unfortunately, the logs can also be hard to decipher when you first start examining them. Graylog uses Pipelines and Data Adapters to enrich logs to make them more functional and easier for you to read.
In order to analyze logs efficiently, they must be structured effectively. Often, logs from different sources label data fields differently and/or provide data that’s completely unstructured. The problem is that both types of data need to be structured appropriately in order to key in on particular elements within the log data, such as: Monitoring on source address, Applying rules associated with user names, and Creating alerts for destination addresses.
It’s Sunday afternoon, and you’re having a nice relaxing weekend, sitting down watching your favorite sporting event. While enjoying the game, you get a high alert email on your phone, noting something’s going on and you need to jump into action. What do you do in these high stress times? Every second counts, and everyone is waiting on you to tell them what’s happening.
Over the past several months, our team has been hard at work building the best log management solution out there. Introducing new features like Views, reporting, and script alerts, alongside updates to content packs, the Sidecar, and pipeline rules, Version 3.0 will knock your socks off. Read on for the nitty-gritty details.
If you maintain a regular practice of keeping log data, you probably have an established way of observing event logs in real time or you do it by using batch processing. There are two ways you can monitor event logs: manually and automatically. By monitoring event logs, you can gain deeper insight into system metrics, localize process bottlenecks, and detect security vulnerabilities. What are some other advantages of event log monitoring, and how can you get the most out of it?
Today we are releasing the first release candidate of Graylog v3.0. This release brings a whole new content pack system, an overhauled collector sidecar, reporting capabilities, improved alerting with greater flexibility, a new script alert notification plugin, support for Elasticsearch 6.x, a preview version of an awesome new search page called Views, and tons of other improvements and bug fixes.
An immeasurable amount of data, in its raw, unfiltered form, exists all around us. For most of us, to be able to properly categorize and “read” that data, we first must convert it into a format that we can understand – which is where the log viewer comes in.
