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Dynatrace and Google Cloud: Intelligent Kubernetes observability and automation

Dynatrace

In the webinar “ Intelligent Kubernetes observability and automation ,” Dynatrace expert Henrik Rexed and GCP experts Gari Singh and Alisha Stull provide insights into leveraging AI-powered observability and automation to gain granular insights into Kubernetes environments on Google Cloud Platform at an enterprise scale.

Google 264
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The keys to selecting a platform for end-to-end observability

Dynatrace

This enables proactive changes such as resource autoscaling, traffic shifting, or preventative rollbacks of bad code deployment ahead of time. However, the drive to innovate faster and transition to cloud-native application architectures generates more than just complexity — it’s creating significant new risk.

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Google Analytics and Dynatrace – Why you need both

Dynatrace

In this post, I wanted to share how I use Google Analytics together with Dynatrace to give me a more complete picture of my customers, and their experience across our digital channels. Google Analytics. Almost all marketers will be familiar with Google Analytics. Dynatrace – understanding customer experience. Thanks, Davis!

Google 202
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Kubernetes vs Docker: What’s the difference?

Dynatrace

This opens the door to auto-scalable applications, which effortlessly matches the demands of rapidly growing and varying user traffic. Just as people use Xerox as shorthand for paper copies and say “Google” instead of internet search, Docker has become synonymous with containers. What is Docker? Networking.

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What is a service mesh?

Dynatrace

This becomes even more challenging when the application receives heavy traffic, because a single microservice might become overwhelmed if it receives too many requests too quickly. A service mesh enables DevOps teams to manage their networking and security policies through code. Why do you need a service mesh?

Traffic 279
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Build and operate multicloud FaaS with enhanced, intelligent end-to-end observability

Dynatrace

For example, to handle traffic spikes and pay only for what they use. 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. Scale automatically based on the demand and traffic patterns.

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9 key DevOps metrics for success

Dynatrace

Let’s start with the four most common metrics Google’s DevOps Research and Assessment (DORA) team established known as “ The Four Keys.” Let’s dive into how these metrics and DevOps KPIs can help your team perform better and deliver better code. Percentage of code covered by automated tests.

DevOps 246