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Build and operate multicloud FaaS with enhanced, intelligent end-to-end observability

Dynatrace

These functions are executed by a serverless platform or provider (such as AWS Lambda, Azure Functions or Google Cloud Functions) that manages the underlying infrastructure, scaling and billing. Enable faster development and deployment cycles by abstracting away the infrastructure complexity.

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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 207
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Dynatrace extends automatic and intelligent observability to cloud and Kubernetes logs for smarter automation at scale

Dynatrace

Leveraging cloud-native technologies like Kubernetes or Red Hat OpenShift in multicloud ecosystems across Amazon Web Services (AWS) , Microsoft Azure, and Google Cloud Platform (GCP) for faster digital transformation introduces a whole host of challenges. Dynatrace news. Collecting data requires massive and ongoing configuration efforts.

Cloud 258
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What is serverless computing? Driving efficiency without sacrificing observability

Dynatrace

VMware commercialized the idea of virtual machines, and cloud providers embraced the same concept with services like Amazon EC2, Google Compute, and Azure virtual machines. Cloud-hosted managed services eliminate the minute day-to-day tasks associated with hosting IT infrastructure on-premises.

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Dynatrace SaaS release notes version 1.239

Dynatrace

To stay tuned, keep an eye on our release notes. You can create custom log metrics for smarter and faster troubleshooting, and you will be able to understand log data in the context of your full stack, including real user impacts. Configuration API for AWS and Azure supporting services. New features and enhancements. Dashboards.

Azure 212
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Why log monitoring and log analytics matter in a hyperscale world

Dynatrace

Driving this growth is the increasing adoption of hyperscale cloud providers (AWS, Azure, and GCP) and containerized microservices running on Kubernetes. Log analytics also help identify ways to make infrastructure environments more predictable, efficient, and resilient. billion in 2020 to $4.1 More automation.

Analytics 205
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Easy SLA and SLO reporting for all your API endpoints with public synthetic HTTP monitors

Dynatrace

Here is the first batch of 15 public locations for HTTP monitoring: Chicago (Azure) ?, Virginia (Azure), N. California (AWS), San Jose (Azure), Texas (Azure), Ohio (AWS), Toronto (Azure) ?, London (AWS), London (Azure), Frankfurt (AWS) ?, Hong Kong (Azure), Tokyo (Azure), Sao Paulo (AWS).