Systems | Development | Analytics | API | Testing

snowflake

9 Best Practices for Transitioning From On-Premises to Cloud with Snowflake

Nov 19, 2024 By Yogesh Gupta In Snowflake
On a day-to-day basis, Snowflake teams identify opportunities and help customers implement recommended best practices that ease the migration process from on-premises to the cloud. They also monitor potential challenges and advise on proven patterns to help ensure a successful data migration. This article highlights nine key areas to watch out for and plan around in order to accelerate a smooth transition to the cloud.
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unravel

BigQuery Cost Management

Nov 6, 2024 By Unravel Data In Unravel
Effective cost management becomes crucial as organizations increasingly rely on Google BigQuery for their data warehousing and analytics needs. This checklist delves into the intricacies of cost management and FinOps for BigQuery, exploring strategies to inform, govern, and optimize usage while taking a holistic approach that considers queries, datasets, infrastructure, and more.
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speedscale

Simplifying AWS Testing: A Guide to AWS SDK Mock

Oct 17, 2024 By Shaun Duncan In Speedscale
Testing AWS services is an essential step in creating robust cloud applications. However, directly interacting with AWS during testing can be complicated, time-consuming, and expensive. The AWS SDK Mock is a JavaScript library designed to simplify this process by allowing developers to mock AWS SDK methods, making it easier to simulate AWS service interactions in a controlled environment. Primarily used with AWS SDK v2, AWS SDK Mock integrates with Sinon.js to mock AWS services like S3, SNS, and DynamoDB.
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kong

RAG Application with Kong AI Gateway, AWS Bedrock, Redis and LangChain

Oct 17, 2024 By Claudio Acquaviva In Kong
For the last couple of years, Retrieval-Augmented Generation (RAG) architectures have become a rising trend for AI-based applications. Generally speaking, RAG offers a solution to some of the limitations in traditional generative AI models, such as accuracy and hallucinations, allowing companies to create more contextually relevant AI applications.
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Episode 11: The future of data lakes: Open table formats, metadata and AI | AWS

Oct 17, 2024 By Fivetran In Fivetran
Paul Meighan, Director of Product Management at AWS, shares how enterprises are increasingly looking for ways to integrate more data sources in their environment — especially with data lakes. From turning S3 buckets into databases to establishing better metadata layers, Meighan explores the rapid evolution of data lakes alongside data warehouses. He also explains the pivotal role AI, ML and GenAI workloads and applications will play in large metadata environments, driving innovative analytics and business insights.
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moesif

Using Moesif with Middy and Serverless for AWS Apps

Oct 15, 2024 By Abu Sakib In Moesif
See the GitHub repository for the source code of this article’s example project. Serverless is a popular framework to build serverless apps using AWS Lambda on the Node.js runtime. Serverless automatically orchestrates necessary resources on AWS and can scaffold a basic project for you that you can build up on. You can solely focus on your application’s core logic, development, and your Lambda functions.
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chaossearch

Optimize Your AWS Data Lake with Streamsets Data Pipelines and ChaosSearch

Oct 11, 2024 By Sandro Lima In ChaosSearch
Many enterprises face significant challenges when it comes to building data pipelines in AWS, particularly around data ingestion. As data from diverse sources continues to grow exponentially, managing and processing it efficiently in AWS is critical. Without these capabilities, it’s harder to analyze and get any meaning from your data.
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integrate

Unleashing the Power of Amazon Redshift Analytics

Oct 5, 2024 By Donal Tobin In Integrate
Table of Contents Amazon Redshift has become one of the most popular data warehousing solutions due to its scalability, speed, and cost-effectiveness. As the data landscape continues to evolve, businesses are generating and data processing increasingly large datasets. Efficient analysis of these datasets is essential to making informed, data-driven decisions. Amazon Redshift allows companies to extract meaningful insights from vast amounts of structured and semi-structured data.
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ClearML

The Cloud Exit: Cost, Security, and Performance Driving the Move Back to On-Premises

Oct 1, 2024 By ClearML In ClearML
The last decade has seen a giant shift by organizations into the cloud for software, storage, and compute, resulting in business benefits ranging from flexibility and lower up-front costs to easier maintenance. But lately we have seen more and more companies re-evaluating their cloud strategies and opting to move their data back to on-premises infrastructure due to several key factors.
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