Category Azure News

Securely monitoring your Azure Database for PostgreSQL Query Store

A few months ago, I shared best practices for alerting on metrics with Azure Database for PostgreSQL. Though I was able to cover how to monitor certain key metrics on Azure Database for PostgreSQL, I did not cover how to monitor and alert on the performance of queries that your application is heavily relying on. As a PostgreSQL database, from time to time you will need to investigate if there are any queries running indefinitely on a PostgreSQL database. These long running queries may interfere with the overall database performance and likely get stuck on some background process. This blog post covers how you can set up alerting on query performance related metrics using Azure Functions and Azure Key Vault.

What is Query Store?

Query Store was a feature in Azure Database for PostgreSQL ann...

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Reducing security alert fatigue using machine learning in Azure Sentinel

Last week we launched Azure Sentinel, a cloud native SIEM tool. Machine learning (ML) in Azure Sentinel is built-in right from the beginning. We have thoughtfully designed the system with ML innovations aimed to make security analysts, security data scientists, and engineers productive. The focus is to reduce alert fatigue and offer ML toolkits tailored to the security community. The three ML pillars in Azure Sentinel include Fusion, built-in ML, build your own ML.


Alert fatigue is real. Security analysts face a huge burden of triage as they not only have to sift through a sea of alerts, but also correlate alerts from different products manually or using a traditional correlation engine.

Our Fusion technology, currently in public preview, uses state of the art scalable learning algo...

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Microsoft and NVIDIA extend video analytics to the intelligent edge

Artificial Intelligence (AI) algorithms are becoming more intelligent and sophisticated every day, allowing IoT devices like cameras to bridge the physical and digital worlds. The algorithms can trigger alerts and take actions automatically — from finding available parking spots and missing items in a retail store to detecting anomalies on solar panels or workers approaching hazardous zones.

Processing these state-of-the-art AI algorithms in a datacenter requires a stable high-bandwidth connection to deliver videos feeds to the cloud. However, these cameras are often located in remote areas with unreliable connectivity or it may not be sensible given bandwidth, security, and regulatory needs.

Microsoft and NVIDIA are partnering on a new approach for intelligent video analytics at the edg...

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Azure Machine Learning service now supports NVIDIA’s RAPIDS

Azure Machine Learning service is the first major cloud ML service to support NVIDIA’s RAPIDS, a suite of software libraries for accelerating traditional machine learning pipelines with NVIDIA GPUs.

Just as GPUs revolutionized deep learning through unprecedented training and inferencing performance, RAPIDS enables traditional machine learning practitioners to unlock game-changing performance with GPUs. With RAPIDS on Azure Machine Learning service, users can accelerate the entire machine learning pipeline, including data processing, training and inferencing, with GPUs from the NC_v3NC_v2, ND or ND_v2 families. Users can unlock performance gains of more than 20X (with 4 GPUs), slashing training times from hours to minutes and dramatically reducing time-to-insight.

The following figure co...

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