The latest News and Information on Log Management, Log Analytics and related technologies.
Tracing is often the last thought in any observability strategy. While engineers prioritize logs and metrics, tracing is truly the hallmark of a mature observability platform, but it is also the most difficult to implement. Once tracing is in place, engineers typically discover something else – many tracing solutions aren’t particularly feature-rich.
If you’re using Solr, for sure there are times when you change the schema and need to reindex. Quite often the source of truth is a database, so you can use streaming expressions via the JDBC source to reindex. But sometimes that’s not possible or adds too much load to the DB. So how can we use Solr itself as a source?
You have more data coming at you than ever before. Over the next five years, the total amount of digital data is going to be more than twice the amount of data created since the advent of digital storage. With the success of your company often determined by how you anticipate and respond to threats – and leverage meaningful insights – you need the ability to quickly search and find insights in your data, despite this increasing deluge of information.
Grafana Loki 2.6 is here! In addition to improvements in query performance, we are excited to introduce two key features in Grafana Loki: cross-tenant query federation and targeted deletes.
When considering application source code, the way you maintain consistency throughout environments is mostly straightforward. You write application code, commit it to source control, and then build, test and deploy via a CI/CD pipeline. Since the application is defined by the source code living in source control, the build will be identical in all environments to which it’s deployed. But what about the infrastructure on which an application runs?
The Core Splunk platform is rightfully recognized as having sparked the log analytics revolution when viewed through the lenses of ingest, search speed, scale, and usability. Their original approach leveraged a MapReduce approach, and it still stores the ingested data on disk in a collection of flat files organized as “buckets.” These immutable buckets are not human-readable and largely consist of the original raw data, indexes (.tsidx files), and a bit of metadata.
Kubernetes, Prometheus, and Grafana are a trio of technologies that have transformed cloud native development. However, despite how powerful these three technologies are, developers still face gaps in the process of implementing a mature Kubernetes environment.