Operations | Monitoring | ITSM | DevOps | Cloud

2020 was indeed challenging for Kovai.co still had great learning! One of them is what I am sharing with the community through this blog. For enterprises like us, worldwide work from anywhere became the new reality. We had to move towards a cloud-native world where secure data storage and effective remote management of IT infrastructure were of supreme importance.

Today’s applications are expected to be highly responsive and always online. Such circumstances excite the pressure on applications to respond in real-time to large changes in usage at peak hours, store ever-increasing volumes of data and make it available in milliseconds. Azure Database Services comes to rescue in such situations, and Azure supports many industry-standard databases and APIs.

Over the past few years, Microsoft Azure has seen tremendous growth, and many new enhancements have improved user productivity. To keep users well informed about their resource status and availability, Microsoft has also been actively working on various monitoring capabilities.

Data sources ingest data in different sizes and shapes across on-premises and in the cloud, including product data, historical customer behaviour data, and user data. Enterprise could store these data in data storage services like Azure Blob store, an on-premises SQL Server, Azure SQL Database, and many more. This blog will highlight how users can define pipelines to migrate the unstructured data from different data stores to structured data using the Azure ETL tool, Azure Data Factory.

There is no doubt that organizations have a difficult task to address the current requirements for building and managing APIs, especially if they don’t use tools like API Management. APIs require up-to-date and strong documentation, increased security levels, comprehensive testing, routine versioning, and high-reliability to be appropriately utilized.

There is no doubt that organizations have a difficult task to address the current requirements for building and managing APIs, especially if they don’t use tools like API Management. APIs require up-to-date and strong documentation, increased security levels, comprehensive testing, routine versioning, and high-reliability to be appropriately utilized.