Update headings

Author: madeline-underwood

content/learning-paths/servers-and-cloud-computing/spark-on-azure/background.md

@@ -1,12 +1,13 @@
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-title: "Overview of Azure Cobalt 100, Azure Linux 3.0, and Apache Spark"
+title: Overview of Microsoft Azure Cobalt 100, Azure Linux 3.0, and Apache Spark
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-# Overview of Azure Cobalt 100, Azure Linux 3.0, and Apache Spark
+## Learn about Azure Cobalt 100, Azure Linux 3.0, and Apache Spark
 
 This section introduces the key technologies you will use when running Spark applications on Microsoft Azure Cobalt 100 processors. You will learn about the Azure Cobalt 100 Arm-based processor, Azure Linux 3.0, and Apache Spark.
 
@@ -18,13 +19,13 @@ Typical workloads include web and application servers, data analytics, open-sour
 
 To learn more, see the blog [Announcing the preview of new Azure virtual machines based on the Azure Cobalt 100 processor](https://techcommunity.microsoft.com/blog/azurecompute/announcing-the-preview-of-new-azure-vms-based-on-the-azure-cobalt-100-processor/4146353).
 
-## Azure Linux 3.0 overview
+## Azure Linux 3.0 
 
 Azure Linux 3.0 is Microsoft’s lightweight Linux distribution optimized for cloud-native workloads on Azure. It is designed for performance, security, and reliability, and is supported by Microsoft. Azure Linux 3.0 is tailored for containers, microservices, and Kubernetes.
 
 With native support for Arm64 (AArch64) architecture, Azure Linux 3.0 enables efficient execution of workloads on Arm-based infrastructure, making it a scalable and cost-effective choice for cloud deployments.
 
-## Apache Spark overview
+## Apache Spark 
 
 Apache Spark is an open-source, distributed computing system for fast, general-purpose big data processing. It provides high-level APIs in Java, Scala, Python, and R, and supports in-memory computation for improved performance.
 

content/learning-paths/servers-and-cloud-computing/spark-on-azure/baseline.md

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-# Functional validation of Apache Spark on Azure Cobalt 100 Arm64
+## Functional validation of Apache Spark on Azure Cobalt 100 Arm64
 
 After installing Apache Spark on your Arm64 virtual machine, you can perform simple baseline testing to validate that Spark runs correctly and produces the expected output.
 

content/learning-paths/servers-and-cloud-computing/spark-on-azure/benchmarking.md

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-# Benchmark Apache Spark on Azure Cobalt 100 Arm64 and x86_64
+## Benchmark Apache Spark on Azure Cobalt 100 Arm64 and x86_64
 
 Apache Spark includes internal micro-benchmarks to evaluate the performance of core components such as SQL execution, aggregation, joins, and data source reads. These benchmarks are useful for comparing performance on Arm64 and x86_64 platforms in Azure.
 

content/learning-paths/servers-and-cloud-computing/spark-on-azure/container-setup.md

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-# Set up an Azure Linux 3.0 environment
+## Set up an Azure Linux 3.0 environment
 
 You can deploy your Spark workload either in an Azure Linux 3.0 Docker container or on a virtual machine created from a custom Azure Linux 3.0 image.
 

content/learning-paths/servers-and-cloud-computing/spark-on-azure/create-instance.md

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-# Create an Arm-based virtual machine using Azure Cobalt 100
+## Create an Arm-based virtual machine using Azure Cobalt 100
 
 You can create an Azure Cobalt 100 Arm-based virtual machine in several ways: using the Microsoft Azure console, the Azure CLI, or your preferred Infrastructure as Code (IaC) tool. In this Learning Path, you will use the Azure console to create a virtual machine with the Azure Cobalt 100 Arm-based processor.