LogDNA today updated its log management tool for Kubernetes to include support for Webhooks that can be employed to provide tighter integration with external applications and tools such as the project management software and collaboration platforms that are crucial to implementing best DevOps practices.
In addition, the latest edition of LogDNA adds updated agent software that can tap into the Linux kernel to monitor log files and directories for changes. That capability reduces CPU utilization while also improving stability and accuracy. It also removes duplicate lines with symbolic linked log files.
LogDNA is also making it possible to process archived logs faster by unzipping just a portion of your logs instead of an entire day’s worth. A new hourly archiving format also enables easier data analysis with new Hive partition folder formats.
Finally, IT teams can now also extract, aggregate and export fields from log lines that have already been indexed. Unlike the custom log parser, the extract and aggregate feature allows users to parse out additional fields ad hoc from historical logs without having to re-ingest them.
Minh Dao, director of product management for LogDNA, says as Kubernetes instances continue to multiply, the IT environment is becoming more complex to manage. IT teams that have adopted Kubernetes will require a log management tool optimized for that platform to be able to pinpoint the root cause of a problem, he says, adding that capability should reduce the number of “war room” meetings every time there is an issue.
Support for Webhooks, meanwhile, will make it easier for IT teams to include LogDNA within a larger DevOps workflow for managing the building and deployment of microservices-based applications on Kubernetes clusters.
As IT teams increasingly operationalize Kubernetes, many of them are acquiring new tools to manage what soon will become hundreds and thousands of Kubernetes clusters. In theory, IT teams could opt to deploy only a handful of Kubernetes clusters. However, thus far each application team appears to prefer to have its own dedicated Kubernetes cluster.
Of course, many IT organizations already have a log management platform they will attempt to extend to Kubernetes. However, there also will be greenfield IT environments that are going to prefer to have a log management tool that runs natively on Kubernetes. Regardless of the approach, as Kubernetes becomes the foundation on which hybrid cloud computing strategies are built the challenges associated with managing Kubernetes clusters will only intensify. IT teams will need to pull together a range of tools to address Kubernetes lifecycle management from cradle to grave.
In the meantime, IT teams should also remember that log data will soon be playing a crucial role in the adoption of artificial intelligence (AI) with modern IT environments. Those AI platforms are only going to be useful if they have access to reliable data. As such, the logs being generated by Kubernetes clusters are about to become a lot more valuable than they might ever have been before.