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AWS observability: AWS monitoring best practices for resiliency

Dynatrace

These resources generate vast amounts of data in various locations, including containers, which can be virtual and ephemeral, thus more difficult to monitor. These challenges make AWS observability a key practice for building and monitoring cloud-native applications. AWS monitoring best practices. What is AWS observability?

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How platform engineering and IDP observability can accelerate developer velocity

Dynatrace

During a breakout session at the Dynatrace Perform 2024 conference, Dynatrace DevSecOps activist Andreas Grabner and staff engineer Adam Gardner demonstrated how to use observability to monitor an IDP for key performance indicators (KPIs). Intelligent monitoring is also crucial. “It makes them more productive.

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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. Logs are automatically produced and time-stamped documentation of events relevant to cloud architectures.

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Unlock the Power of DevSecOps with Newly Released Kubernetes Experience for Platform Engineering

Dynatrace

Platform engineering is on the rise. According to leading analyst firm Gartner, “80% of software engineering organizations will establish platform teams as internal providers of reusable services, components, and tools for application delivery…” by 2026. Monitoring-as-code can also be configured in GitOps fashion.

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OpenTelemetry observability and Dynatrace deliver actionable answers at scale

Dynatrace

If a microservice falls in the forest and all your monitoring solutions report it differently, can operators accurately trace what happened and automate a response? Different monitoring point solutions, such as Jaeger, Zipkin, Logstash, Fluentd, and StatsD, each have their own way of observing and recording such an event.

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Automating Success: Building a better developer experience with platform engineering

Dynatrace

Check out the following use cases to learn how to drive innovation from development to production efficiently and securely with platform engineering observability. Using Dynatrace, teams can directly access their synthetic monitors and drill down into locations where, for example, execution failed because of local or global outages.

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Dynatrace Perform 2024 Guide: Deriving business value from AI data analysis

Dynatrace

Check back here throughout the event for the latest news, insights, and announcements. Measuring the importance of data quality to causal AI success – blog Causal AI can accurately pinpoint why an event occurred, but the effectiveness of AI depends on high-quality data. Enter causal AI.