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Automate complex metric-related use cases with the Metrics API version 2

Dynatrace

Dynatrace collects a huge number of metrics for each OneAgent-monitored host in your environment. Depending on the types of technologies you’re running on individual hosts, the average number of metrics is about 500 per computational node. Running metric queries on a subset of entities for live monitoring and system overviews.

Metrics 228
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Enable full observability for Linux on IBM Z mainframe now with logs

Dynatrace

The challenge for hybrid cloud deployments is maintaining critical observability, which must include the full set of monitoring signals: logs, metrics, and traces. You can push a filtering change to filter out all unwanted logs from your central Dynatrace environment and apply the change automatically to all your monitored platforms.

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Auto-adaptive thresholds for AI-driven quality gating

Dynatrace

The training times and other quality metrics, such as the RMSE (Root Mean Squared Error), SMAPE (Scaled Mean Absolute Percentage Error), and coverage probability, are monitored using Dynatrace. Our data scientists utilize metrics and events to store these quality metrics. For full details, see Dynatrace Documentation.

Metrics 233
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Dynatrace innovates again with the release of topology-driven auto-adaptive metric baselines

Dynatrace

With the advent and ingestion of thousands of custom metrics into Dynatrace, we’ve once again pushed the boundaries of automatic, AI-based root cause analysis with the introduction of auto-adaptive baselines as a foundational concept for Dynatrace topology-driven timeseries measurements. In many cases, metric behavior changes over time.

Metrics 212
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PostgreSQL Checkpoints, Buffers, and WAL Usage with Percona Monitoring and Management

Percona

In this blog post, we will discuss how to extend Percona Monitoring and Management (PMM) to get PostgreSQL metrics on checkpointing activity, internal buffers, and WAL usage. With this data, we’ll be able to better understand and tune our Postgres servers. You can search the blog for more information on this if needed.

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Flexible, scalable, self-service Kubernetes native observability now in General Availability

Dynatrace

From a cost perspective, internal customers waste valuable time sending tickets to operations teams asking for metrics, logs, and traces to be enabled. A team looking for metrics, traces, and logs no longer needs to file a ticket to get their app monitored in their own environments. Monitoring such an application is easy.

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New Prometheus-based extensions enable intelligent observability for more than 200 additional technologies

Dynatrace

Building on its advanced analytics capabilities for Prometheus data , Dynatrace now enables you to create extensions based on Prometheus metrics. Many technologies expose their metrics in the Prometheus data format. Easily gain actionable insights with the Dynatrace Extension for Prometheus metrics. Prometheus in Kubernetes ?and