Why enterprises are adopting Fivetran's Managed Data Lake Service
Fivetran Managed Data Lake Service brings automation, governance and reliability to data lakes.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Why Do You Need to Test Your MVP?
More often in today’s society of growing ‘entrepreneurs’, almost all are developing Minimum Viable Products MVPs that breathe life into their concepts. A shocking but true statistic reveals that 90% of startups fail. One big reason for this is the poor execution of a key tool in the startup world: the minimum viable product (MVP). One of the reasons for this failure is the lack of tests conducted appropriately.
Govern an Open Lakehouse with Snowflake Open Catalog, a Managed Service for Apache Polaris
To enhance security and ease operational burden, many organizations with data lakes or lakehouses want flexibility to securely integrate their tools of choice on a single copy of data. An open standard for storage format and catalog API has helped, but there’s still a need for open standards for the catalog, including a consistent way to apply security access controls to data.
A Quick Guide to Embedded Dashboards
Understanding embedded analytics dashboards starts with knowing what the term itself means—so let’s break it down. Dashboards are screens or pages that display information in a unified view that makes data easily digestible for end users.
Kubernetes Load Testing: How JMeter and Speedscale Compare
At some point, your development team may be considering implementing load testing (also known as stress testing) as part of your software testing process. Load testing validates that your web app is able to withstand a large number of simultaneous users, decreasing the chance that any traffic spikes will bring down your services once deployed. These stress tests can be highly granular, giving you the opportunity to test run virtually unlimited strategies before they are set into the wild.
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Simplifying AWS Testing: A Guide to AWS SDK Mock
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.
Ways to Use Mock Services in Software Development
Mocking APIs is a popular practice in software development. An increasing number of developers are reaping the benefits and no longer using their valuable time to spin up duplicate resources. Many mock services do not require account creation, making them easy to use and privacy-friendly. In the rest of this article, we explain what mock APIs are, when you should think about using them, and what solutions are available within the open-source and proprietary markets.
Top 5 Tools For Performance Testing: Boost Your Application'S Speed
Performance testing t is a major part of software testing and involves understanding how the software handles expected errors, which is integral to quality assurance. There are multiple free and open-source tools we can discuss in the blog, but let’s start with why we even need performance testing.
Shift Left: Headless Data Architecture, Part 1
The headless data architecture is an organic emergence of the separation of data storage, management, optimization, and access from the services that write, process, and query it. With this architecture, you can manage your data from a single logical location, including permissions, schema evolution, and table optimizations. And, to top it off, it makes regulatory compliance a lot simpler, because your data resides in one place, instead of being copied around to every processing engine that needs it.
AWS on the future of data lakes, metadata and AI innovation
The Director of Product Management at AWS sat down with Fivetran to unpack how Iceberg and metadata are reshaping the future of data lakes, data warehouses and AI.