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How to Configure Custom Metrics in AWS Elastic Beanstalk Using Memory Metrics Example

DZone

Recently, I encountered a task where a business was using AWS Elastic Beanstalk but was struggling to understand the system state due to the lack of comprehensive metrics in CloudWatch. By default, CloudWatch only provides a few basic metrics such as CPU and Networks.

Metrics 241
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Install Prometheus on Kubernetes: Tutorial and Examples

DZone

As one of the most popular open-source Kubernetes monitoring solutions, Prometheus leverages a multidimensional data model of time-stamped metric data and labels. The platform uses a pull-based architecture to collect metrics from various targets.

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Dynatrace simplifies OpenTelemetry metric collection for context-aware AI analytics

Dynatrace

The release candidate of OpenTelemetry metrics was announced earlier this year at Kubecon in Valencia, Spain. Since then, organizations have embraced OTLP as an all-in-one protocol for observability signals, including metrics, traces, and logs, which will also gain Dynatrace support in early 2023.

Analytics 293
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Support of OpenTelemetry metrics with enhanced AI capabilities

Dynatrace

With the most important components becoming release candidates , Dynatrace now supports the full OpenTelemetry specification on all runtimes and automatically adds intelligence to metrics at enterprise scale. So these metrics are immensely valuable to SRE and DevOps teams. Automation and intelligence for metrics at enterprise scale.

Metrics 237
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Unified Observability Exporters: Metrics, Logs, and Tracing

DZone

This second blog will take a deeper dive into the Metrics, Logs, and Tracing exporters (which can be found at [link] ), describing them and showing how to configure them, Grafana, alerts, etc. This is the second in a series of blogs discussing unified observability with microservices and the Oracle database.

Metrics 246
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Create compelling insights into business and operational KPIs through metric calculations in the Data explorer

Dynatrace

Metrics matter. But without complex analytics to make sense of them in context, metrics are often too raw to be useful on their own. To achieve relevant insights, raw metrics typically need to be processed through filtering, aggregation, or arithmetic operations. Examples of metric calculations. Dynatrace news.

Metrics 246
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Transform log data into actionable metrics and have Davis AI do the work for you

Dynatrace

Now, Dynatrace has the ability to turn numerical values from logs into metrics, which unlocks AI-powered answers, context, and automation for your apps and infrastructure, at scale. Whatever your use case, when log data reflects changes in your infrastructure or business metrics, you need to extract the metrics and monitor them.

Metrics 226