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Evolution of Netflix Conductor:

The Netflix TechBlog

The Netflix Media Database (NMDB) is one such example. Instead, we use a wrapper that pulls in the latest version of Conductor and adds Netflix infrastructure components and libraries before deployment. Netflix Conductor is maintained by the Media Workflow Infrastructure team. As such, Conductor 2.x

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AWS serverless services: Exploring your options

Dynatrace

This means you no longer have to provision, scale, and maintain servers to run your applications, databases, and storage systems. Instead of worrying about infrastructure management functions, such as capacity provisioning and hardware maintenance, teams can focus on application design, deployment, and delivery. Reliability.

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Lerner?—?using RL agents for test case scheduling

The Netflix TechBlog

We needed a way to run agents and tie the runs to the internal infrastructure for analytics, reporting, and visualizations. To maintain the quality of Lerner APIs, we are using the server-less paradigm for Lerner’s own integration testing by utilizing AWS Lambda. Administrative user-interface to manage agents.

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Dynatrace SaaS release notes version 1.233

Dynatrace

DL/I segment name for DL/I databases. RUM linking timeouts adjusted in transaction storage. (APM-341299). The trace list now correctly supports sorting on the number of database calls. (APM-340223). Resolved an issue that was causing alerts for infrastructure (for example, Host CPU) to be generated even when disabled. (APM-348563).

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Seamless AI-powered observability for multicloud serverless applications

Dynatrace

Cloud vendors such as Amazon Web Services (AWS), Microsoft, and Google provide a wide spectrum of serverless services for compute and event-driven workloads, databases, storage, messaging, and other purposes. Dynatrace news. Engineers often choose best-of-breed services from multiple sources to create a single application.

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What is Google Cloud Functions?

Dynatrace

In a time when modern microservices are easier to deploy, GCF, like its counterparts AWS Lambda and Microsoft Azure Functions , gives development teams an agility boost for delivering value to their customers quickly with low overhead costs. These functions can connect with supported cloud databases, such as Cloud SQL and Bigtable.

Google 221
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Expanding the Cloud: Amazon Machine Learning Service, the Amazon Elastic Filesystem and more

All Things Distributed

Once the models are created, you can get predictions for your application by using the simple API, without having to implement custom prediction generation code or manage any infrastructure. AWS has been offering a range of storage solutions: objects, block storage, databases, archiving, etc. Amazon Lambda.

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