Microsoft continued to roll out the updates and new features to its Azure cloud platform in August.
Leading the way is the addition of a public preview for archive blob storage, a low-cost, long-term storage tier feature. It is ideal for data that companies must keep for regulatory purposes, but have no need to access on a regular basis. Blob tiers can be changed easily by the administrator, as data needs change. Using the preview requires registering, but once up and running will help businesses further reduce their cloud storage costs.
Related to this leading news is the addition of default encryption for blobs and files to improve security. All data written or copied to Azure services for all types of accounts will be encrypted to 256-bit AES standards. This feature will be rolled out over September to all regions.
Third-party and big data features
Continuing Microsoft's efforts to allow users to work with third-party products, the company also has updates on its stack and working with the increasingly popular Kubernetes.
With deploy to Kubernetes and ACS plug-ins, users can continuously deploy to their choice of container orchestrator. This includes a Jenkins to Kubernetes plugin, for which there was no obvious tool in existence, one of the growing signs of Microsoft helping out the communities. With lots of big data projects using Kubernetes, in concert with Apache Spark, Azure can fit in with these efforts.
Continuing the drive to big data, Microsoft has also added an Azure Data Lake Store Capture as part of the now generally available Event Hubs Capture. This provides hugely scalable massive data stores for incoming big data flows. Using it can help businesses with their unstructured, semi-structured or structured data, extracting value using parallel analytics and other types of tools. Ideal for capturing long-term streams where future analysis or batch processing can be carried out, adding it to your Azure system is a simple step through the Event Hubs Capture menu.
For those looking to truly exploit big data, Microsoft is also introducing machine learning-based anomaly detection for Azure Stream Analytics. Available as a private preview, it enables customers to monitor their data through SQL in real time to detect unexpected events. This will be ideal for those working with large, live, data streams from IoT or industrial devices. The machine learning element will help it understand over time which are genuine events, and what are the standard patterns of your data flow to minimise false positives.
Along those lines, Microsoft also offers improved ways to integrate the Azure Stack into your company's data centre. The stack provides a simpler way to install and import all the features required for an organisation’s business needs, running through a simplified administrative system, rather than installing and managing each component individually. Integrating into IT system management and network services, with backup and security features as part of the stack, this is a logical way for most businesses to deploy Azure.