DevOps is the union of people, processes, and products to enable the continuous delivery of value to end users. DevOps for machine learning is about bringing the lifecycle management of DevOps to Machine Learning. Utilizing Machine Learning, DevOps can easily manage, monitor, and version models while simplifying workflows and the collaboration process.
Effectively managing the Machine Learning lifecycle is critical for DevOps’ success. And the first piece to machine learning lifecycle management is building your machine learning pipeline(s).
What is a Machine Learning Pipeline?
DevOps for Machine Learning includes data preparation, experimentation, model training, model management, deployment, and monitoring while also enhancing governance, repeatability, and collaboration throughout the model development process. Pipelines allow for the modularization of phases into discrete steps and provide a mechanism for automating, sharing, and reproducing models and ML assets. They create and manage workflows that stitch together machine learning phases. Essentially, pipelines allow you to optimize your workflow with simplicity, speed, portability, and reusability.
There are four steps involved in deploying machine learning that data scientists, engineers and IT experts collaborate on:
Data Ingestion and Preparation Model Training and Retraining Model Evaluation Deployment
Together, these steps make up the Machine Learning pipeline. Below is
Azure Service Health helps you stay informed and take action when Azure service issues like outages and planned maintenance affect you. It provides you with a personalized dashboard that can help you understand issues that may be impacting resources in your Azure subscriptions.
For any event, you can get guidance and support, share details with your colleagues, and receive issue updates. Most importantly, you can configure customizable alerts to automatically notify you of service issues, planned maintenance, and health advisories.
We’ve posted a new video series to help you learn how to use Azure Service Health and ensure you stay on top of service issues. You’ll find out how to:
Set up your first Azure Service Health alert. Follow best practices in Azure Service Health alerting. Get alerted via mobile push notifications. Integrate Azure Service Health with your organization’s ticketing system, for example, ServiceNow. Understand the differences between Azure Service Health, Azure Resource Health, and the Azure Status page.
Watch the first video now:
Set up your Azure Service Health alerts today by visiting Azure Service Health in the Azure portal.
For more in-depth guidance, visit the Azure Service Health documentation. Let us know if you have a suggestion
In the late 1990s, the time and date features of computer systems became a topic of high interest for every business, as programmers realized that a simple abbreviation of four digit years to only the last two digits had a fatal flaw – the rollover to the year 2000. But early preparation and remediation ensured that the predicted Y2K disaster never occurred. In much the same way, Microsoft has completed preparations for the upcoming GPS Week Number Rollover to ensure that users of Microsoft time sources do not experience any impact.
In the financial services industry, coordinating and reporting time is critical. The same Global Positioning System (GPS) we rely upon daily to get from point A to point B, also provides precise and accurate Coordinated Universal Time (UTC) to financial markets. It transmits the correct date and time by supplying the receiver with the current week and the current number of seconds in the week. The week number is encoded into the data stream by a 10-bit field. A binary 10-bit word can represent a maximum of 1,024 weeks (roughly19.7 years or an epoch). At the end of each epoch, the receiver resets the week number to zero and
After you experience a Microsoft Azure service issue, you likely need to explain what happened to your customers, management, and other stakeholders. That’s why Azure Service Health provides official incident reports and root cause analyses (RCAs) from Microsoft.
Azure Service Health helps you stay informed and take action when Azure service issues like incidents and planned maintenance affect you by providing a personalized health dashboard, customizable alerts, and expert guidance. In this blog, we’ll cover how you can use Azure Service Health’s health history to review past health issues and get official root cause analyses (RCAs) to share with your internal and external stakeholders.
Review past health issues and get official root cause analyses (RCAs)
You can see 90 days of history about past incidents, maintenance, and health advisories in Azure Service Health’s “Health history” section. This is a tailored view of the Azure Activity Log provided by Azure Monitor.
If you experienced downtime, your internal or external stakeholders might expect an official report or RCA. As soon as they become available, RCAs can be found under any incident. Meanwhile, you can download and share Microsoft’s issue summary as a PDF.
Learn more about getting downloadable explanations in the
We are pleased to share the general availability of Azure Active Directory (AD) based access control for Azure Storage Blobs and Queues. Enterprises can now grant specific data access permissions to users and service identities from their Azure AD tenant using Azure’s Role-based access control (RBAC). Administrators can then track individual user and service access to data using Storage Analytics logs. Storage accounts can be configured to be more secure by removing the need for most users to have access to powerful storage account access keys.
By leveraging Azure AD to authenticate users and services, enterprises gain access to the full array of capabilities that Azure AD provides, including features like two-factor authentication, conditional access, identity protection, and more. Azure AD Privileged Identity Management (PIM) can also be used to assign roles “just-in-time” and reduce the security risk of standing administrative access.
When Azure AD authentication is combined with the new Azure Data Lake Storage Gen 2 capabilities, users can also take advantage of granular file and folder access control using POSIX-style access permissions and access control lists
Self-service is core to Infrastructure-as-a-Service (IaaS). Back in the virtualization days, you had to wait for someone to create a VLAN for you, carve out a LUN, and find space on a host. If Microsoft Azure ran that way, we would have needed to hire more and more admins as our cloud business grew.
Do it yourself
A different approach was required, which is why IaaS is important. Azure’s IaaS gives the owner of the subscription everything they need to create virtual machines (VMs) and other resources on their own, without involving an administrator. To learn more visit our documentation, “Introduction to Azure Virtual Machines” and “Introduction to Azure Stack virtual machines.”
Let me give you a few examples that show Azure and Azure Stack self-service management of VMs.
Creating a VM is as simple as going through a wizard. You can create the VM by specifying everything needed for the VM in the “Create virtual machine” blade. You can include the operating system image or marketplace template, the size (memory, CPUs, number of disks, and NICs), high availability, storage, networking, monitoring, and even in guest configuration.
Learn more by visiting the following resources:
Developers can now access the latest Cognitive Services Speech SDK which now supports:
Selection of the input microphone through the AudioConfig class Expanded support for Debian 9 Unity in C# (beta) Additional sample code
Read the updated Speech Services documentation to get started today.
The Speech SDK now also supports Unity in a beta version. Since this is new functionality, please provide feedback through the issue section in the GitHub sample repository. This release supports Unity on Windows x86 and x64 (desktop or Universal Windows Platform applications), and Android (ARM32/64, x86). More information is available in our Unity quickstart.
The following new content is available in our sample repository.
Samples for AudioConfig.FromMicrophoneInput. Python samples for intent recognition and translation. Samples for using the Connection object in iOS. Java samples for translation with audio output. New sample for use of the Batch
This blog post was co-authored by David Armour, Principal Program Manager, Azure Stack.
Start with what you already have
Every organization has a unique journey to the cloud. This journey is based on the organization’s history, business specifics, culture, and maybe most importantly, their starting point. While it can be hard for some to say goodbye to their current virtualization environment and way of doing things, the journey to the cloud provides many options, features, functionalities, and opportunities to improve existing governance, operations, and implement new ones. The journey to the cloud can also provide the opportunity to redesign applications and take advantage of the cloud architecture. Additionally, Microsoft Azure gives you the option to host your virtual machines (VMs) in the public cloud or in your own facility with Azure Stack.
In most cases, this journey starts with a lift and shift of the existing servers, either virtual machines or physical servers. Because Azure Stack at its core is an infrastructure-as-a-service (IaaS) platform, the right way to think about this first phase of the journey is as a lift and optimize process. Moving the servers should be the first step towards enabling modern operations across your workloads. That could
Classroom labs in Azure Lab Services make it easy to set up labs by handling the creation and management of virtual machines and enabling the infrastructure to scale. Through our continuous enhancements to Azure Lab Services, we are proud share that the latest deployment now includes added support for class schedules.
Schedules management is one of the key features requested by our customers. This feature helps teachers easily create, edit, and delete schedules for their classes. A teacher can set up a recurring or a one-time schedule and provide a start, end date, and time for the class in the time zone of choice. Schedules can be viewed and managed through a simple, easy to use calendar view.
Students virtual machines are turned on and ready to use when a class schedule starts and will be turned off at the end of the schedule. This feature helps limit the usage of virtual machines to class times only, thereby helping IT admins and teachers manage costs efficiently.
Schedule hours are not counted against quota allotted to a student. Quota is the time limit outside of schedule hours when a student can use the virtual machine.
With schedules, we are also