This article is based on reporting originally published at virtualizationreview.com, authored by Paul Schnackenburg (MCSE, MCT, MCTS, MCITP), who runs IT consultancy Expert IT Solutions.
Overview
Microsoft Build 2019 moved well beyond the traditional major-release cadence and instead delivered a broad set of incremental but meaningful improvements across Azure. For DevOps engineers, the announcements touched on Kubernetes orchestration, relational and NoSQL databases, serverless computing, blockchain infrastructure, and machine learning tooling. This article organises those announcements into actionable categories.
Containers and Kubernetes (AKS)
Containers and Kubernetes remain central to cloud-native DevOps, and Microsoft used Build 2019 to shore up rough edges in Azure Kubernetes Service (AKS).
Azure Dev Spaces
Dev Spaces creates a shared development cluster where team members can iterate on individual microservices without affecting other components of the application. It is intentionally scoped to development clusters rather than production environments, reducing the risk of accidental interference between developers working on the same distributed system.
Azure Pipelines Integration with AKS
A tighter integration between Azure Pipelines and AKS was announced to streamline deployments from a Git repository directly to a Kubernetes cluster. The goal is to lower the barrier for teams adopting CI/CD pipelines with containerised workloads.
Azure Policy for AKS
Azure Policy — a governance tool for enforcing organisational standards across cloud resources — was extended to cover AKS deployments. This enables platform teams to apply consistent compliance rules to Kubernetes clusters alongside other Azure resources, something that had previously required separate tooling.
KEDA: Kubernetes-Based Event-Driven Autoscaling
KEDA (Kubernetes-based Event-Driven Autoscaling) is an open-source project co-developed by Microsoft and Red Hat. It brings Functions-as-a-Service-style event-driven scaling to any Kubernetes cluster, including AKS. Rather than triggering scale-out based solely on CPU or memory thresholds, KEDA scales workloads in response to events from sources such as:
- Apache Kafka streams
- Azure Storage Queues
- Azure Service Bus
- RabbitMQ
- HTTP requests
- Azure Event Grid
This makes KEDA well-suited to batch processing, message-driven architectures, and any workload with bursty, unpredictable demand patterns.
AKS Virtual Nodes: Generally Available
Virtual nodes — built on the Virtual Kubelet technology that Microsoft donated to the Cloud Native Computing Foundation (CNCF) — reached general availability. Virtual nodes allow AKS clusters to burst container workloads onto Azure Container Instances almost instantaneously, rather than waiting for new VM-backed nodes to provision. Billing is per-second. At the time of the announcement, virtual nodes supported Linux containers only.
Database Announcements
Build 2019 featured a significant number of database-related announcements, reflecting both the volume of data organisations are managing and the variety of workloads they need to support.
Azure SQL Database Edge
Azure SQL Database Edge is a lightweight relational engine designed for edge computing scenarios. Key characteristics announced at the time included:
- Support for both ARM and Intel processors
- Optimisation for data streaming and time-series workloads
- Built-in machine learning for local inference before optionally uploading data to the cloud
- Cloud-managed updates via Azure
- Linux-only at the time of announcement; in private preview
Azure SQL Database Hyperscale
The Hyperscale tier for Azure SQL Database is designed to remove the traditional ceiling on relational database size and performance. It distributes data across multiple nodes and handles sharding automatically, while still presenting a single connection endpoint to application developers. Announced capabilities included:
- Storage up to 100 TB (with larger limits planned)
- Near-instant backups and restores
- Optimisation for OLTP workloads
A Hyperscale tier for PostgreSQL (via Azure Database for PostgreSQL) was also referenced as part of the broader announcement.
Azure SQL Database Serverless
The serverless compute tier for Azure SQL Database automatically pauses compute resources when a database is idle and resumes them on the next request. During inactive periods, customers pay only for storage. This model suits intermittent or unpredictable workloads where keeping compute running continuously would be wasteful.
Cosmos DB: Apache Spark, Jupyter Notebooks, and etcd API
Azure Cosmos DB received several additions targeting analytics and operational intelligence:
- Apache Spark integration: Enables running operational analytics and AI workloads directly against globally distributed Cosmos DB data, using Spark alongside existing protocol connectors (Cassandra, MongoDB, Gremlin).
- Jupyter Notebooks: Integrated directly into the Cosmos DB portal, allowing data exploration and ML query development without leaving the database environment.
- etcd API: Allows Kubernetes clusters to use Cosmos DB as the backing store for etcd configuration data, enabling globally distributed Kubernetes control planes.
Azure Blockchain Service
Azure Blockchain Service entered public preview at Build 2019. It is a fully managed service for provisioning and operating consortium blockchain networks, handling the underlying infrastructure so that teams can focus on writing smart contracts and business logic rather than configuring nodes and networking.
Complementing the managed service, Microsoft also announced:
- Azure Blockchain Development Kit: Includes connectors for Microsoft Flow and Logic Apps, enabling non-expert developers to integrate blockchain workflows into existing business processes.
- Visual Studio Code plug-in: Aimed at simplifying smart contract development within a familiar IDE.
Artificial Intelligence and Machine Learning
Azure Form Recognizer
Form Recognizer is a cognitive service that extracts text, key-value pairs, and table data from forms using a small set of sample documents (approximately five examples). This removes the need to build a bespoke ML model for every form type, which has practical implications for automating document processing at scale across industries such as healthcare, finance, and logistics.
Visual Interface for Azure Machine Learning
A new drag-and-drop visual interface for Azure Machine Learning was introduced, making it possible to build, train, and deploy models without writing code. This lowers the entry barrier for developers who work with data but are not dedicated ML practitioners.
MLOps and Azure DevOps Integration
Microsoft formalised the concept of MLOps — treating ML model development with the same lifecycle management practices applied to application code. Integration with Azure DevOps means that model training runs, versioning, and deployments can participate in standard CI/CD pipelines.
ML.NET
ML.NET brings machine learning capabilities to .NET developers using familiar C# or F# workflows, without requiring Python expertise or external ML frameworks. Build 2019 featured improvements to the library, though the specific version details in the original source material were not fully enumerated here.
Azure Active Directory for GitHub Enterprise
Following Microsoft’s acquisition of GitHub, Build 2019 included the announcement that Azure Active Directory authentication is now supported for GitHub Enterprise, enabling organisations to enforce existing identity and access management policies across their source control environment.
Summary of Key Announcements
| Category | Announcement | Status at Build 2019 |
|---|---|---|
| Kubernetes | AKS Virtual Nodes | Generally Available |
| Kubernetes | KEDA (event-driven autoscaling) | Announced / Open Source |
| Kubernetes | Azure Policy for AKS | Preview |
| Kubernetes | Azure Dev Spaces improvements | Available |
| Database | Azure SQL Database Edge | Private Preview |
| Database | Azure SQL Database Hyperscale | Available |
| Database | Azure SQL Database Serverless | Preview |
| Database | Cosmos DB Apache Spark integration | Preview |
| Database | Cosmos DB Jupyter Notebooks | Preview |
| Database | Cosmos DB etcd API | Preview |
| Blockchain | Azure Blockchain Service | Preview |
| AI / ML | Azure Form Recognizer | Preview |
| AI / ML | ML.NET improvements | Released |
| AI / ML | Azure ML visual interface | Preview |
| Identity | Azure AD for GitHub Enterprise | Available |
What to Watch Next
Build 2019 represented only a portion of Microsoft’s Azure roadmap at the time. Services announced shortly after the conference — including Azure Lighthouse (multi-tenant management) and Azure Bastion (managed jump-host service) — continued the theme of reducing operational complexity for platform and DevOps teams. Many of the preview features listed above have since reached general availability; always verify current status in the official Azure documentation before adopting them for production workloads.
Original reporting by Paul Schnackenburg for virtualizationreview.com. Paul is an IT consultant specialising in Windows, Hyper-V, and Exchange Server solutions.