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New web performance insights with additional metrics and enhanced Visually complete for synthetic monitors

Dynatrace

Dynatrace Synthetic Monitoring allows you to proactively monitor the availability of your public as well as your internal web applications and API endpoints from locations around the globe or important internal locations such as branch offices. Synthetic monitors help you find issues before they affect your customers.

Metrics 203
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Ensure great customer experience on your mobile app by monitoring key user actions

Dynatrace

Overall statistics like the number of users, user sessions, or the crash rate definitely are a good starting point. Define and monitor up to 500 key user actions and track historic trends. You can use this feature to monitor key actions with a dedicated dashboard tile and track historic trends.

Mobile 178
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Monitoring-as-code through Dynatrace’s Open-Source Initiative

Dynatrace

Configurations such as dashboards, alerting rules and Service Level Objective definitions are left to be created separately, and often manually. Configuring monitoring and observability is no stranger to that paradigm and it was also highlighted in the latest State of DevOps 2020 report. Monitoring-as-code requirements at Dynatrace.

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

Dynatrace

Our monitoring coverage already includes ? This extension enables you to monitor RabbitMQ outside of Kubernetes with data obtained either from a Prometheus server or directly from a RabbitMQ Prometheus exporter. By monitoring specific RabbitMQ nodes, you can easily identify and mitigate performance issues. documentation.

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A three-step implementation guide to answer-driven SLO-based release validation

Dynatrace

Many of our users are performance engineers using Cloud Automation Quality Gates to automate the analysis of their performance and load tests – saving hours of analysis time for each test they run. You run load tests monitored with Dynatrace and you want to automatically validate to eliminate the manual analysis effort.

DevOps 241
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Automated observability, security, and reliability at scale

Dynatrace

While infrastructure has historically been treated as a bottleneck where proper scaling and compute power are applied to improve performance, these aspects are now typically addressed by hyperscalers that offer cloud-based infrastructure and infrastructure as a service. The screenshot below displays such a configuration.

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Conducting log analysis with an observability platform and full data context

Dynatrace

With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. Business leaders can decide which logs they want to use and tune storage to their data needs.

Analytics 177