Azure FAQ

A real time pipeline starts with Azure Event Hubs ingesting high throughput streaming data from producers such as IoT devices, applications, or microser...

• How would you design a real-time data processing pipeline using Azure Event Hubs and Power BI?

  A real time pipeline starts with Azure Event Hubs ingesting high throughput streaming data from producers such as IoT devices, applications, or microservices. Azure Stream Analytics sits in the middle to perform windowed aggregations, filtering, and transformations on the live stream. The processed results are then pushed to Power BI as a streaming dataset for real time dashboards. Key design considerations include: Configure Event Hubs partitions to match expected throughput and parallelism nee

• Can you explain the differences between Azure Event Hubs, Azure Service Bus, and Azure Event Grid, and when to use each?

  These three services serve distinct messaging and eventing patterns in Azure. Azure Event Hubs is a big data streaming platform designed for high throughput ingestion (millions of events/sec). Use it for telemetry, logging, and analytics pipelines. Azure Service Bus is an enterprise message broker supporting queues (point to point) and topics (pub/sub) with features like transactions, dead lettering, and sessions. Use it for reliable command style messaging between services. Azure Event Grid is

• How would you implement a solution to handle duplicate events in Azure Event Hubs?

  Azure Event Hubs provides at least once delivery, so duplicates are possible and consumers must handle them. The primary strategy is idempotent processing designing your consumer so that processing the same event twice produces the same result. Include a unique event ID (e.g., UUID) in each event payload at the producer side Maintain a processed event store (e.g., a Redis set or database table) to track IDs you have already handled Use checkpoint based consumer groups so that after a restart, on

• Describe a scenario where you would use Azure Data Factory in conjunction with Azure Event Hubs.

  A common scenario is bridging batch and streaming worlds. Azure Data Factory (ADF) orchestrates scheduled data movement from on premises or SaaS sources, while Azure Event Hubs handles real time ingestion. For example, ADF can run a nightly pipeline that extracts reference data from an on premises SQL Server and lands it in Azure Blob Storage . Simultaneously, Event Hubs ingests real time clickstream events. A Stream Analytics job joins the live stream against the reference data to enrich events

• How can you secure data in transit when using Azure Event Hubs?

  Azure Event Hubs enforces encryption in transit by default using TLS 1.2 for all client to service communication. Beyond transport encryption, access control is critical. Use Shared Access Signatures (SAS) tokens to grant time limited, permission scoped access (Send, Listen, Manage) Prefer Azure Active Directory (AAD) RBAC roles such as Azure Event Hubs Data Sender and Azure Event Hubs Data Receiver for identity based access Restrict network exposure using Virtual Network service endpoints or Pr

• How would you implement a solution to monitor and alert on the performance of an Azure Event Hubs instance?

  Azure Monitor is the primary tool for observing Event Hubs health and performance. It collects platform metrics automatically and supports custom dashboards and alert rules. Track key metrics: Incoming/Outgoing Messages , Throttled Requests , Server Errors , and Capture Lag Create metric alert rules for thresholds like throttled requests 0 or incoming bytes dropping below a baseline Enable Diagnostic Settings to stream logs to a Log Analytics workspace for KQL based querying Build Azure Dashboar

• Can you explain how to implement partitioning in Azure Event Hubs and its impact on performance?

  Partitioning is the core scalability mechanism in Event Hubs. You choose the partition count (2 32, or up to 2000 in Dedicated tier) at namespace creation time, and it cannot be changed later. Assign a partition key when sending events so that related events (e.g., same device ID) land in the same partition, preserving ordering Each partition is an independent ordered log, enabling parallel consumers within a consumer group one consumer per partition More partitions mean higher aggregate through

• How would you design a disaster recovery strategy for Azure Event Hubs?

  Azure Event Hubs Geo Disaster Recovery pairs two namespaces in different Azure regions, replicating metadata (entity definitions, configuration) but not event data. Set up a primary and secondary namespace in separate regions using the Geo DR pairing feature On failover, the secondary namespace becomes the new primary and takes over the DNS alias Event data in flight is not replicated , so producers must re send any events lost during the failover window Regularly test failover in a non producti