Operations | Monitoring | ITSM | DevOps | Cloud

So you have been adding more and more logs to your Graylog instance, gathering up your server, network, application logs and throwing in anything else you can think of. This is exactly what Graylog is designed for, to collect all the logs and have them ready for you to search through in one place. Unfortunately, during your administration of Graylog you go the System -> Overview screen and see the big bad red box, saying you are having indexing failures.

Continuous integration and continuous deployment (CI/CD) has enabled teams to build and deploy software at a much faster pace. DevOps teams can build, test, and deploy changes to production in a matter of minutes, allowing for extremely rapid release cycles. However, a CI/CD pipeline has a lot of moving parts and steps where problems to occur. In order to ensure a successful deployment, it’s important to monitor each step in this process.

I have been super fortunate to work with incredibly innovative, talented teams that create powerful technology to help manage the world's data. When I met with Thomas Hazel, CHAOSSEARCH founder and CTO, and Les Yetton, CHAOSSEARCH co-founder and CEO to talk about CHAOSSEARCH — scalable, performant text search to your object storage without having to move any data — I knew it was special and was eager to join.

The next major version of the LogDNA agent is right around the corner, and we’re introducing some significant improvements. Most notably, we’ve completely rewritten the agent using Rust instead of Node.js. As we gear up for the release, we wanted to explain why we chose Rust for the LogDNA agent, the benefits that it offers over other languages, and how it can help you log faster. Rust is a systems programming language that aims to offer both performance and safety.

One of the benefits of using Logstash in your data pipelines is the ability to transform the data into the desired format according to the needs of your system and organization. There are many ways of transforming data in Logstash, one of them is using the mutate filter plugin. This Logstash filter plugin allows you to force fields into specific data types and add, copy, and update specific fields to make them compatible across the environment.