Dynatrace native log support for Kubernetes and multi-cloud
Dynatrace has now enhanced its infrastructure monitoring capabilities to analyse logs from Kubernetes and multi-cloud environments, plus, also, the most widely used open source log data frameworks.
These enhancements are intended to allow DevOps and Site Reliability Engineering teams (SREs) to search, segment and analyse real-time and historical logs from any source in a centralised location.
To simplify cloud complexity at scale, Dynatrace combines this log data with observability and user experience data and maintains a real-time entity map and causation-based AI engine to deliver even smarter answers.
“It’s not just collecting data, but what you do with it once it’s collected that simplifies cloud complexity,” said Steve Tack, SVP of Product Management at Dynatrace.
Tacks says that his firm’s AI engine, Davis, continuously and automatically processes observability data and delivers precise answers with root-cause and impact analysis.
Dynatrace’s AI engine Davis provides real-time answers, detecting anomalies based on log events and other data and automatically identifies the root-cause of infrastructure problems such as Kubernetes service degradations, saving DevOps and SREs more time for innovation.
“Expanding this with native log support for Kubernetes, all major public clouds, and open-source frameworks, broadens this observability even further, making Davis even smarter, delivering better answers, and enabling DevOps and SRE teams to automate tedious work that is stealing time from innovation,” added Tack.
Automatic log ingestion
Legacy monitoring, observability-only and do-it-yourself approaches leave it up to digital teams to make sense of their data. Dynatrace addresses these challenges with: automatic log ingest and storage includes logs from Kubernetes and multi-cloud environments, Amazon Web Services, Google Cloud Platform, Microsoft Azure and Red Hat OpenShift and the most widely used open source log data frameworks, such as Fluentd and Logstash.
Also here we find the new Dynatrace Log Viewer, which provides powerful filtering capabilities to empower teams to search, analyse and segment real-time and historical log data from any source, again… in a centralized location.
Teams can explore logs across multi-cloud environments and analyse them in the context of their architecture.
Finally here, there is also Dynatrace Smartscape to continuously map cloud log data with the extensive observability data it already collects, reflecting the technologies and dependencies in multi-cloud environments as well as users’ experiences with these technologies.
