Remove Azure Remove Database Remove Metrics Remove Operating System
article thumbnail

Kubernetes in the wild report 2023

Dynatrace

As Kubernetes adoption increases and it continues to advance technologically, Kubernetes has emerged as the “operating system” of the cloud. Kubernetes is emerging as the “operating system” of the cloud. The strongest Kubernetes growth areas are security, databases, and CI/CD technologies.

article thumbnail

What is serverless computing? Driving efficiency without sacrificing observability

Dynatrace

Traditional computing models rely on virtual or physical machines, where each instance includes a complete operating system, CPU cycles, and memory. 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.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Lessons learned from enterprise service-level objective management

Dynatrace

Lastly, error budgets, as the difference between a current state and the target, represent the maximum amount of time a system can fail per the contractual agreement without repercussions. Organizations have multiple stakeholders and almost always have different teams that set up monitoring, operate systems, and develop new functionality.

article thumbnail

OpenShift vs. Kubernetes: Understanding the differences

Dynatrace

According to the Kubernetes in the Wild 2023 report, “Kubernetes is emerging as the operating system of the cloud.” ” In recent years, cloud service providers such as Amazon Web Services, Microsoft Azure, IBM, and Google began offering Kubernetes as part of their managed services. Ease of use.

article thumbnail

The road to observability demo part 3: Collect, instrument, and analyze telemetry data automatically with Dynatrace

Dynatrace

Making applications observable—relying on metrics, logs, and traces to understand what software is doing and how it’s performing—has become increasingly important as workloads are shifting to multicloud environments. We also introduced our demo app and explained how to define the metrics and traces it uses.

Metrics 173
article thumbnail

Weighing a microservices approach means covering all architecture bases

Dynatrace

Smaller teams can launch services much faster using flexible containerized environments, such as Kubernetes, or serverless functions, such as AWS Lambda, Google Cloud Functions, and Azure Functions. Additionally, typical SOA models use larger relational databases. VMs require their own operating system and take up additional resources.

article thumbnail

PREVIEW : SentryOne Plan Explorer Extension for Azure Data Studio

SQL Performance

Last year, I got together with one of my dev teams at SentryOne – they call themselves the SQL Injectors – to talk about the possibility of replicating Plan Explorer functionality inside of Azure Data Studio. First, ensure you meet our requirements: Azure Data Studio 1.9.0 or newer ( July announcement post ).NET or better).

Azure 90