Monthly updates for July 2019
Protect applications and data from datacenter failures with redundancies across Availability Zones.
Azure Cosmos DB now offers a preview driver extension for Azure Cosmos DB Cassandra API for Java SDK.
Target availability: Q3 2019
Share data with other organizations using Azure Data Share, now in preview.
Target availability: Q4 2019
Enterprise BI systems need to support high user concurrency, which means there can be lots of queries submitted close to each other. We are pleased to announce that we are working on the query interleaving feature, which allows system configuration to improve the user experience in high-concurrency scenarios. Query interleaving allows configuration to improve the user experience in high-concurrency scenarios. Multiple queries can run concurrently so fast queries are not blocked behind slow ones. Query interleaving can be set up with short-query bias so if the system is under CPU pressure, short queries are allocated a higher proportion of CPU resources than long-running queries, allowing them to complete faster.
Understand the adoption of self-service password reset (SSPR) and Multi-Factor Authentication (MFA) in your organization with this Azure AD dashboard.
The latest release of the Text Analytics API's sentiment capability (v3) provides a significant improvement in detecting positive, neutral, and negative sentiment of text documents. It is available in public preview Central Canada, East Asia, and Central US.
We are excited to announce support for up to 16TB of storage and up to 20,000 IOPS in Azure Database for PostgreSQL is now in preview.
We are excited to announce support for up to 16TB of storage and up to 20,000 IOPS in Azure Database for MySQL is now in preview.
The Azure Sphere public preview 19.06 quality release is now available via the Retail feed.
Seamlessly collaborate with guests or partners whose IT managed identity solution supports the SAML or WS-Fed standards.
Azure Data Factory Mapping Data Flows provides a code-free design environment for building and operationalizing ETL data transformations at scale. Now, the ADF team has added parameter support for Data Flows, enabling flexible & reusable data flows that can be called dynamically from pipelines.