Agile Azure Scalability Serverless 
CIO
DECEMBER 22, 2023
Skills: Knowledge and skills for this role include an understanding of implementation and integration, security, configuration, and knowledge of popular cloud software tools such as Azure, AWS, GCP, Exchange, and Office 365. Role growth: 27% of companies have added cloud systems admin roles as part of their cloud investments.
Cloudera
SEPTEMBER 30, 2022
With DFF, users now have the choice of deploying NiFi flows not only as long-running auto scaling Kubernetes clusters but also as functions on cloud providers’ serverless compute services including AWS Lambda, Azure Functions, and Google Cloud Functions. build high performant, scalable web applications across multiple data centers).
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Apiumhub
MARCH 12, 2024
Implementation: Using edge computing frameworks like AWS IoT Greengrass or Azure IoT Edge to deploy machine learning models directly on edge devices for real-time data analysis. This event-driven model enhances efficiency, scalability, and cost-effectiveness.
Perficient
NOVEMBER 28, 2023
At Perficient we extract the best of each language to shape an agile and efficient ecosystem. This results in scalable and flexible software , able to adapt to changing demands and decoupled to offer flexibility in services as the challenge arises.
Cloudera
MARCH 14, 2023
When a draft is ready to be deployed in production, it is published to the Catalog, and can be productionalized with serverless DataFlow Functions for event-driven, micro-bursty use cases or auto-scaling DataFlow Deployments for low latency, high throughput use cases. This results in a rapid and agile flow development process.
CIO
NOVEMBER 29, 2023
And while Kubernetes is an industry standard, implementations of it, such as Azure Communication Services and Google Kubernetes Engine, don’t work identically. Transferring large amounts of data can also lead to downtime and potential data loss, and ensuring consistent performance and scalability during the transition is crucial.
Perficient
JUNE 15, 2023
From architectural shifts like the move from Mongo to SQL for xDB, the addition of additional services like Identity Server or the move from Azure Search back to SOLR all add complexity to the upgrade process. also support Serverless architectures leading to even greater scalability. You can even scale them independently.
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