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AWS serverless services: Exploring your options

Dynatrace

Amazon Web Services (AWS), offers a wide range of serverless solutions. To get a better understanding of AWS serverless, we’ll first explore the basics of serverless architectures, review AWS serverless offerings, and explore common use cases. AWS serverless offerings. Common use cases for AWS serverless services.

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Consistent caching mechanism in Titus Gateway

The Netflix TechBlog

We introduce a caching mechanism in the API gateway layer, allowing us to offload processing from singleton leader elected controllers without giving up strict data consistency and guarantees clients observe. The cache is kept in sync with the current leader process. How do I know that my cache is up to date? of the data.

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Implementing AWS well-architected pillars with automated workflows

Dynatrace

If you use AWS cloud services to build and run your applications, you may be familiar with the AWS Well-Architected framework. But this workflow can also help you implement your applications according to each of the AWS Well-Architected pillars.  Beyond efficiency, validating performance thresholds is also crucial for revenues.

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Dynatrace Support for AWS Lambda Functions Powered by x86 and AWS Graviton2

Dynatrace

Dynatrace is proud to partner with AWS to support AWS Lambda functions powered by x86-based processors and Graviton2 Arm-based processors announced earlier this year. According to the official AWS announcement, Graviton2-based Lambda functions offer up to 34% better price-performance improvement. Dynatrace Data explorer.

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Dynatrace supports SnapStart for Lambda as an AWS launch partner

Dynatrace

Dynatrace is proud to be an AWS launch partner in support of Amazon Lambda SnapStart. For AWS Lambda, the largest contributor to startup latency is the time spent initializing an execution environment, which includes loading function code and initializing dependencies. Users can take advantage of the platform features immediately.

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Seeing through hardware counters: a journey to threefold performance increase

The Netflix TechBlog

to a larger AWS instance size, from m5.4xl (16 vCPUs) to m5.12xl (48 vCPUs). As GS2 relies on AWS EC2 Auto Scaling to target-track CPU utilization, we thought we just had to redeploy the service on the larger instance type and wait for the ASG (Auto Scaling Group) to settle on the CPU target. Thread 0’s cache in this example.

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AWS EKS Monitoring as a Self-Service with Dynatrace

Dynatrace

REDIS for caching. AWS EKS for Integration and Production. When focusing on the LanguageController service we learn that it’s currently deployed in three pods across three EKS nodes across two AWS Availability Zones (AZ). 4 AWS EFS monitoring. Their technology stack looks like this: Spring Boot-based Microservices.

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