M365.FM - Modern work, security, and productivity with Microsoft 365

The Monorepo Myth: Why Your Architecture Is Fragmented

1 h 22 min · Gisteren
aflevering The Monorepo Myth: Why Your Architecture Is Fragmented artwork

Beschrijving

Welcome to another episode of Knowledge Nuggets with Mirko Peters. In this episode, we're tackling one of the biggest misconceptions in software architecture: the Monorepo Myth. For years, engineering teams have debated whether a monorepo or a multirepo is the "correct" repository strategy. Discussions usually focus on Git performance, build speed, repository size, or tooling. But these technical arguments miss the real issue. Your repository strategy isn't primarily a Git decision—it's an organizational decision. The structure of your repositories shapes how teams collaborate, communicate, make decisions, and ultimately how quickly your organization can deliver software. THE BIGGEST MISCONCEPTION Most organizations evaluate repository strategies using technical criteria. Questions like: * Can Git handle millions of files? * How fast are clone operations? * How quickly does CI complete? * Which strategy scales better? These are valid engineering concerns, but they aren't the questions that determine long-term success. The real question is: Where does your organization pay its coordination cost? A repository strategy doesn't eliminate coordination—it simply determines where that coordination happens. Whether you choose a monorepo or a multirepo, your teams still need to collaborate. The only difference is how visible that collaboration becomes. UNDERSTANDING MONOREPOS A monorepo stores multiple applications, services, libraries, infrastructure code, and shared components inside a single repository. This creates several important advantages: * Shared tooling * Consistent standards * Easier large-scale refactoring * Unified dependency management * Atomic cross-project changes * Complete visibility across the entire system When teams are closely aligned, a monorepo enables rapid cross-cutting changes because everything lives together under one build system and one source of truth. However, as organizations grow, coordination becomes increasingly centralized. Shared libraries require approval from multiple teams, dependency updates affect everyone simultaneously, and build systems become more complex as additional teams join the repository. The technical challenges often blamed on monorepos are actually symptoms of growing organizational complexity rather than limitations of Git itself. THE HIDDEN COST OF MONOREPOS Large monorepos rarely fail because of technology. Git itself can manage repositories containing millions of files. Companies like Google successfully operate enormous monorepos. Instead, organizations encounter problems such as: * Slow code reviews * Long build pipelines * Complex branching strategies * Frozen dependencies * Endless coordination meetings * Difficult release planning These issues arise because every significant architectural decision requires agreement across more teams. As organizations grow, the repository doesn't become technically unmanageable—it becomes organizationally expensive. The true scaling challenge is coordination, not source control. HOW MULTIREPOS WORK A multirepo architecture separates services, products, or components into independent repositories. Each team owns its own repository, deployment pipeline, testing strategy, and release schedule. The benefits include: * Independent deployments * Clear ownership * Team autonomy * Smaller repositories * Faster local builds * Flexible release cycles However, the coordination burden doesn't disappear. Instead of coordinating through code reviews and shared repositories, teams coordinate through: * APIs * Versioning * Release notes * Contracts * Documentation * Governance processes The coordination simply moves from code into communication between teams. ORGANIZATIONAL DEBT One of the most valuable ideas discussed in this episode is organizational debt. Unlike technical debt, organizational debt doesn't exist in the codebase. It appears as: * Unclear ownership * Slow approvals * Excessive meetings * Complicated release processes * Duplicate workflows * Ambiguous decision-making These problems accumulate over time and become the real bottleneck for software delivery. Many organizations attempt to solve organizational debt by changing repository strategies. In reality, neither monorepos nor multirepos solve these problems—they simply expose them differently. CONWAY'S LAW  A key concept behind repository design is Conway's Law. It states that software systems naturally mirror the communication structure of the organizations that build them. If teams are divided into silos, the architecture will eventually become siloed as well. Changing repository layouts cannot fix poor communication. Likewise, organizations with highly collaborative teams can successfully operate either monorepos or multirepos because the underlying communication patterns already support effective collaboration. Your repository structure is often a reflection of your organizational structure rather than its cause.  THE COMMUNICATION ARCHITECTURE MODEL Rather than thinking about repositories as storage mechanisms, it is more useful to think of them as communication architectures. A monorepo encourages: * Shared visibility * Continuous collaboration * Immediate feedback * Centralized coordination A multirepo encourages: * Clear contracts * Independent ownership * Explicit APIs * Autonomous deployments Neither model is inherently superior. The best choice depends on how your teams naturally communicate and collaborate. Repository strategy should reflect your communication model—not dictate it. AI IS CHANGING THE EQUATION The rapid adoption of AI-assisted development introduces a new challenge. AI coding assistants dramatically increase software output. Developers can generate significantly more code than before, but code review and verification have not accelerated at the same pace. This creates what can be described as a verification tax. Organizations capable of generating code twice as fast often find that reviews, architectural validation, testing, and integration become the new bottlenecks. AI doesn't eliminate organizational fragmentation—it amplifies it by increasing the volume of work flowing through existing coordination processes.  Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support [https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support?utm_source=rss&utm_medium=rss&utm_campaign=rss].

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aflevering Microsoft Graph Connectors - Simply Explained artwork

Microsoft Graph Connectors - Simply Explained

Welcome to another episode of Knowledge Nuggets with Mirko Peters. In this episode, we're exploring Microsoft Graph Connectors, now increasingly referred to as Microsoft Copilot Connectors. While Microsoft 365 Copilot can search emails, Teams chats, SharePoint, and OneDrive out of the box, most organizations store critical business information in systems like Salesforce, ServiceNow, Jira, Confluence, SAP, GitHub, and many other third-party platforms. You'll learn how Graph Connectors bridge that gap, the difference between Synced and Federated Connectors, how Microsoft Graph indexes external content, how security permissions are preserved, and how these connectors dramatically expand what Copilot can understand across your organization. WHY GRAPH CONNECTORS MATTER Modern organizations rarely keep all their business data inside Microsoft 365. Customer information often lives in Salesforce, IT tickets are managed in ServiceNow, documentation resides in Confluence, source code is stored in GitHub, and project information may be spread across Jira, Google Drive, Dropbox, or countless other business applications. Without Graph Connectors, Microsoft 365 Copilot can only answer questions using Microsoft 365 content. This creates major knowledge gaps because some of the most valuable business information exists outside Microsoft's ecosystem. Graph Connectors eliminate these blind spots by making external business content searchable through Microsoft Graph, allowing Copilot to generate answers using data from multiple systems instead of only Microsoft 365. WHAT ARE MICROSOFT GRAPH CONNECTORS? A Microsoft Graph Connector imports external business content into the Microsoft Graph, Microsoft's unified data and intelligence platform that powers Microsoft Search and Microsoft 365 Copilot. Think of Microsoft Graph as a centralized knowledge index. Once external data enters this index, Copilot can search, summarize, reference, and reason over that information just as naturally as it does with SharePoint documents or Outlook emails. Although Graph Connectors have existed for years to power Microsoft Search, they have become significantly more valuable with the arrival of Microsoft 365 Copilot because AI can now understand and combine information across multiple connected systems instead of simply returning search results. SYNCED VS FEDERATED CONNECTORS Microsoft currently supports two different connector models. Synced Connectors copy external data into Microsoft Graph. The information is indexed, semantically processed, and stored inside Microsoft 365. This approach provides fast search, semantic understanding, and broad availability across Microsoft Search and Copilot. Synced connectors work particularly well for relatively static information such as: * HR documentation * Knowledge bases * Company policies * Wikis * Archived contracts * Reference documentation Federated Connectors operate differently. Instead of copying information, Copilot retrieves data directly from the external system whenever a user asks a question. The data remains in its original location and is retrieved in real time using the Model Context Protocol (MCP). Federated connectors are ideal for rapidly changing information including: * Support tickets * CRM records * Inventory systems * Live project status * Current pricing * Operational dashboards Many organizations ultimately use both approaches together depending on the nature of their business data. SECURITY AND PERMISSIONS One of the biggest strengths of Microsoft Graph Connectors is that they preserve existing security permissions. Every indexed item contains an Access Control List (ACL) that defines exactly which users are allowed to view that content. If a user doesn't have permission inside the original system, Copilot won't expose that information either. Authentication uses modern OAuth 2.0 standards, while data transferred through connectors is encrypted during transit. Synced connector data is also encrypted at rest within Microsoft 365. For organizations with on-premises systems, Microsoft provides the Microsoft Graph Connector Agent, allowing local data to be indexed securely without moving entire file repositories into the cloud. Because connectors inherit Microsoft 365's enterprise security and compliance capabilities, organizations can extend Copilot while maintaining existing governance and regulatory requirements. CONNECTING EXTERNAL SYSTEMS Microsoft offers more than one hundred pre-built Graph Connectors for popular enterprise applications. Examples include: * Salesforce * ServiceNow * Jira * Confluence * GitHub * Google Drive * Dropbox * Box * Azure DevOps * Many additional partner applications For organizations with proprietary systems, developers can also build custom connectors using the Microsoft Graph Connectors API and Microsoft 365 development tools, allowing virtually any business application to become searchable through Microsoft Graph and Copilot. GETTING STARTED Setting up Microsoft Graph Connectors begins inside the Microsoft 365 Admin Center, where administrators can browse available connectors, authenticate external systems, define synchronization schedules, configure field mappings, and apply security permissions. After deployment, administrators should verify that Copilot can retrieve relevant information while ensuring users only see data they're authorized to access. Organizations often begin by connecting one high-value business system, such as ServiceNow or Salesforce, before gradually expanding their connected knowledge base to additional applications. This incremental approach delivers immediate value while simplifying governance and administration. KEY TAKEAWAYS Microsoft Graph Connectors dramatically expand what Microsoft 365 Copilot can understand by connecting external business systems to Microsoft Graph. Whether using Synced Connectors for indexed knowledge or Federated Connectors for real-time information, organizations can break down data silos and give Copilot access to the information employees need most. By preserving existing permissions, supporting enterprise security, and integrating with hundreds of business applications, Graph Connectors transform Copilot from a Microsoft 365 assistant into an AI that can reason across your organization's complete knowledge landscape. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support [https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support?utm_source=rss&utm_medium=rss&utm_campaign=rss].

20 jul 202615 min
aflevering Azure Advisor - Simply Explained artwork

Azure Advisor - Simply Explained

Welcome to another episode of Knowledge Nuggets with Mirko Peters. In this episode, we're exploring Azure Advisor, Microsoft's free optimization service that continuously analyzes your Azure environment and provides personalized recommendations to improve cost, security, reliability, performance, and operational excellence. Rather than acting as just another dashboard, Azure Advisor functions like a cloud consultant that compares your deployed resources against Microsoft's best practices and identifies opportunities to optimize your environment. You'll learn how Azure Advisor works, what its five recommendation pillars include, how the Advisor Score is calculated, and how to use its recommendations to build better Azure solutions. WHAT IS AZURE ADVISOR? Azure Advisor is a free, built-in Azure service that continuously evaluates your Azure resources against the Azure Well-Architected Framework. Without requiring installation or configuration, Advisor automatically scans your subscriptions and generates personalized recommendations based on your actual workloads instead of generic best practices. Every recommendation includes an estimated impact level, allowing administrators to prioritize improvements that deliver the greatest business value. Azure Advisor also supports Quick Fix actions for selected recommendations, helping organizations implement improvements faster without manually configuring every resource. Because it's integrated directly into the Azure portal, Azure Advisor is available to every Azure customer from day one.  THE FIVE ADVISOR PILLARS Azure Advisor organizes its recommendations into five optimization categories. Cost recommendations identify opportunities to reduce Azure spending by right-sizing virtual machines, removing idle resources, purchasing Reserved Instances, using Azure Savings Plans, and enabling Azure Hybrid Benefit. Security recommendations integrate with Microsoft Defender for Cloud to improve Secure Score through features such as Multi-Factor Authentication, encryption, network protection, identity security, and compliance improvements. Reliability recommendations help increase workload availability through Availability Zones, geo-redundancy, backups, disaster recovery planning, and resilient application architectures. Performance recommendations identify bottlenecks by analyzing compute utilization, storage performance, database optimization, networking, caching, and application scalability. Operational Excellence focuses on governance, monitoring, Azure Policy, supported API versions, service retirements, logging, automation, and maintaining healthy operational practices across your Azure environment.  HOW AZURE ADVISOR WORKS Azure Advisor continuously collects telemetry from your Azure resources and compares your environment against Microsoft's cloud best practices. Most recommendations require at least seven days of resource usage before meaningful analysis becomes available. Advisor combines telemetry, platform intelligence, and machine learning to identify optimization opportunities based on actual workload behavior rather than static configuration rules. Recommendations are categorized by impact level—High, Medium, or Low—allowing administrators to prioritize improvements with the greatest return. Advisor also provides proactive notifications about upcoming service retirements and newly discovered optimization opportunities so organizations can plan ahead before issues affect production workloads.  UNDERSTANDING THE ADVISOR SCORE One of Azure Advisor's most useful features is the Advisor Score. The Advisor Score provides a percentage-based measurement showing how closely your Azure environment follows Microsoft's recommended best practices. Each of the five optimization pillars receives its own individual score, while an overall Advisor Score summarizes the health of your Azure environment. The score is calculated using the ratio of healthy resources compared to resources requiring improvement. Certain recommendation categories carry greater weighting than others, particularly within Reliability, Performance, and Operational Excellence, ensuring that more critical improvements have a greater influence on the final score. Advisor updates these scores regularly, allowing organizations to track optimization progress over time and measure improvements after implementing recommendations.  PRACTICAL USE CASES Azure Advisor helps organizations optimize both technical performance and operational efficiency. Common scenarios include: * Right-sizing underutilized virtual machines * Purchasing Reserved Instances for long-running workloads * Improving Secure Score through identity protection * Enabling Availability Zones for critical applications * Configuring backups and disaster recovery * Optimizing SQL Database performance * Identifying unsupported API versions * Detecting deprecated Azure services * Improving governance with Azure Policy * Increasing application performance through caching and scaling recommendations Because recommendations are personalized, every Azure subscription receives guidance specific to its own workloads and deployment patterns rather than generic documentation. GETTING STARTED WITH AZURE ADVISOR Getting started with Azure Advisor is straightforward. Simply open Azure Advisor from the Azure portal and review your current Advisor Score. Begin by focusing on High-impact recommendations, as these typically provide the greatest improvements with the least effort. Establishing a regular review process—weekly or monthly—helps organizations continuously improve cloud governance while preventing configuration drift over time. For larger environments, Advisor can also be combined with Azure Policy, Azure CLI, REST APIs, and automation tools to integrate optimization recommendations directly into deployment pipelines and governance processes. KEY TAKEAWAYS Azure Advisor is much more than a recommendation dashboard. It serves as a continuous optimization engine that helps organizations reduce costs, strengthen security, improve performance, increase reliability, and maintain operational excellence across their Azure environments. By regularly reviewing Advisor recommendations, monitoring the Advisor Score, and implementing High-impact improvements first, organizations can continuously optimize their cloud infrastructure while following Microsoft's Azure Well-Architected Framework and cloud best practices. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support [https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support?utm_source=rss&utm_medium=rss&utm_campaign=rss].

20 jul 202615 min
aflevering Azure Cost Management - Simply Explained artwork

Azure Cost Management - Simply Explained

Welcome to another episode of Knowledge Nuggets with Mirko Peters. In this episode, we're exploring Azure Cost Management, Microsoft's built-in solution for monitoring, analyzing, controlling, and optimizing your Azure spending. Cloud computing promises flexibility and pay-as-you-go pricing, but without proper visibility, it's surprisingly easy to waste money on idle virtual machines, oversized databases, forgotten storage, and unused resources. You'll learn how Azure Cost Management helps you track spending, understand billing, create budgets, configure alerts, analyze resource costs, and apply proven optimization strategies that can significantly reduce your monthly Azure bill without sacrificing performance. WHY COST MANAGEMENT MATTERS One of the biggest misconceptions about cloud computing is that it's automatically inexpensive. While Azure allows you to pay only for the resources you consume, organizations often continue paying for resources they no longer need. Idle virtual machines, oversized compute instances, unattached managed disks, unused public IP addresses, forgotten snapshots, and development environments running overnight can quietly generate unnecessary costs month after month. Industry research consistently shows that a significant percentage of cloud spending is wasted due to poor visibility and lack of governance. Azure Cost Management helps eliminate this waste by providing clear insight into where money is being spent before unexpected bills arrive. Instead of reacting after receiving an invoice, organizations can proactively monitor costs and optimize cloud usage every day.  UNDERSTANDING AZURE COST MANAGEMENT Azure Cost Management is included with every Azure subscription and provides four core capabilities: * Monitor cloud spending * Analyze resource costs * Control budgets and alerts * Optimize Azure resources The service collects cost information directly from your Azure subscriptions and presents it through interactive dashboards, reports, forecasts, and filtering options. Administrators can analyze spending across subscriptions, resource groups, individual resources, services, regions, departments, projects, or custom tags. Cost data is refreshed regularly, allowing organizations to identify unusual spending patterns quickly rather than waiting until the monthly invoice arrives. Together with Azure Advisor, Cost Management also delivers optimization recommendations that help reduce unnecessary cloud expenses. BILLING HIERARCHY AND RESOURCE ORGANIZATION Understanding Azure's billing structure is essential for accurate cost reporting. Azure separates the Billing Hierarchy from the Resource Hierarchy. The billing hierarchy consists of Billing Accounts, Billing Profiles, Invoice Sections, and Subscriptions, determining how Microsoft invoices your organization. The resource hierarchy consists of Management Groups, Subscriptions, Resource Groups, and individual Azure Resources, representing where workloads actually run. Because financial reporting and technical organization don't always align naturally, Azure supports Tags that connect resources to departments, environments, projects, applications, or cost centers. Proper tagging allows organizations to answer important business questions such as: * Which department generated these costs? * Which project is consuming the largest budget? * How much does production cost compared to development? * Which application is driving Azure spending? Without consistent tagging, accurate cost allocation becomes significantly more difficult. COST ANALYSIS, BUDGETS, AND ALERTS The Cost Analysis dashboard is the heart of Azure Cost Management. It allows administrators to visualize spending over time, compare historical trends, forecast future costs, and drill down from subscriptions to individual Azure resources. Interactive filtering makes it easy to identify the services or workloads responsible for increasing costs. Budgets provide proactive financial control by allowing organizations to define monthly or yearly spending limits. Alerts can automatically notify administrators when spending reaches predefined thresholds such as 50%, 75%, 90%, or 100% of the allocated budget. Azure also supports Anomaly Detection, using machine learning to identify unusual spending patterns that may indicate configuration mistakes, unexpected workload growth, or security incidents. Combined with Azure Monitor and Action Groups, organizations can even trigger automated responses when budgets or anomalies occur.  OPTIMIZING AZURE COSTS Monitoring costs is only the first step. Azure Cost Management also helps organizations reduce spending through practical optimization strategies. Common cost-saving opportunities include: * Right-sizing oversized virtual machines * Automatically shutting down development environments after business hours * Deleting orphaned disks and unused resources * Purchasing Reserved Instances for predictable workloads * Using Azure Savings Plans for flexible compute discounts * Enabling Azure Hybrid Benefit for Windows Server and SQL Server licenses * Using Spot Virtual Machines for interruptible workloads * Reviewing Azure Advisor recommendations regularly Even small improvements across multiple resources can generate substantial long-term savings while maintaining application performance and availability. BUILDING A COST-CONSCIOUS CULTURE Successful cloud cost optimization is not only a technical challenge but also an organizational one. Development teams, administrators, architects, and finance departments should all understand how cloud resources impact operational expenses. Establishing consistent tagging policies, reviewing Azure costs regularly, assigning ownership to deployed resources, and making cost visibility part of everyday operations helps prevent waste before it occurs. Rather than optimizing every resource individually, organizations often achieve the greatest savings by focusing on the small percentage of resources responsible for the majority of their cloud spend. Azure Cost Management provides the visibility needed to identify these opportunities quickly and confidently. KEY TAKEAWAYS Azure Cost Management is much more than a billing dashboard. It provides the visibility, governance, forecasting, budgeting, and optimization capabilities needed to control cloud spending across Azure environments of every size. By combining Cost Analysis, Budgets, Alerts, Tags, Azure Advisor recommendations, Reserved Instances, Savings Plans, and automation, organizations can significantly reduce unnecessary cloud costs while maintaining secure, scalable, and high-performing Azure workloads. Whether you're managing a single Azure subscription or a global enterprise environment, Azure Cost Management should be one of the first services you configure to ensure every cloud investment delivers maximum business value. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support [https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support?utm_source=rss&utm_medium=rss&utm_campaign=rss].

20 jul 202618 min
aflevering Azure Automation - Simply Explained artwork

Azure Automation - Simply Explained

Welcome to another episode of Knowledge Nuggets with Mirko Peters. In this episode, we're exploring Azure Automation, Microsoft's cloud service for automating repetitive IT tasks across Azure and hybrid environments. Whether you're starting and stopping virtual machines, running maintenance scripts, applying configurations, or responding automatically to alerts, Azure Automation helps eliminate manual work while improving consistency and reducing operational costs. You'll learn how Automation Accounts, Runbooks, Schedules, Hybrid Runbook Workers, Desired State Configuration, Managed Identities, and shared resources all work together to build reliable cloud automation that runs 24/7 without human intervention. WHY AZURE AUTOMATION MATTERS Every IT administrator performs repetitive tasks that consume valuable time. Starting and stopping virtual machines, patching servers, cleaning up resources, rotating logs, or running maintenance scripts may seem simple individually, but become overwhelming as environments grow. Manual administration also introduces inconsistency and human error. One forgotten patch, one incorrectly configured server, or one missed maintenance task can quickly lead to operational issues. Azure Automation centralizes these recurring activities inside an Automation Account, allowing organizations to automate repetitive operational tasks, schedule maintenance windows, react to monitoring alerts, and execute scripts consistently across hundreds or even thousands of systems without manual intervention. RUNBOOKS AND AUTOMATION ACCOUNTS The heart of Azure Automation is the Runbook. A Runbook is simply a PowerShell or Python script stored inside an Automation Account. Once written and tested, Azure executes the same sequence of actions repeatedly without requiring user interaction. Runbooks can perform almost any administrative task, including: * Starting and stopping Azure Virtual Machines * Managing storage accounts * Executing database maintenance * Sending notifications * Calling REST APIs * Managing Azure resources * Automating cloud governance Automation Accounts act as the central repository for runbooks, schedules, variables, credentials, certificates, and connections, making automation easier to organize, maintain, and secure across an entire Azure environment. SCHEDULES, TRIGGERS, AND WEBHOOKS Automation becomes valuable when runbooks execute without manual intervention. Azure Automation supports several trigger mechanisms. Schedules allow runbooks to execute once, daily, weekly, monthly, or according to custom recurrence patterns. Azure Monitor Alerts can trigger runbooks automatically whenever monitoring detects issues such as high CPU utilization, low disk space, or service failures. Webhooks expose secure URLs that external applications, Logic Apps, DevOps pipelines, or third-party systems can call to launch automation workflows instantly. Because schedules are reusable, a single schedule can trigger multiple runbooks simultaneously, making it easy to automate recurring operational tasks across multiple Azure resources. HYBRID RUNBOOK WORKERS AND STATE CONFIGURATION Azure Automation isn't limited to Azure resources. Hybrid Runbook Workers extend automation to on-premises servers, private datacenters, and other non-Azure environments. Instead of executing inside Azure's managed sandbox, runbooks execute locally on Hybrid Workers, providing direct access to internal networks, Active Directory, local databases, file shares, and legacy applications. For configuration management, Azure Automation includes Desired State Configuration (DSC), allowing administrators to define the desired configuration for servers and automatically detect or remediate configuration drift. As Microsoft evolves this capability, Azure Machine Configuration continues expanding these compliance and configuration management features while integrating more closely with Azure Policy. SHARED RESOURCES AND MANAGED IDENTITIES Automation workflows often require credentials, configuration values, certificates, or API connections. Azure Automation securely stores these shared resources centrally rather than embedding sensitive information directly inside scripts. Variables, encrypted credentials, certificates, and connection assets can all be reused across multiple runbooks while simplifying maintenance and improving security. Authentication is further simplified through Managed Identities. Instead of storing passwords or service principal secrets, Automation Accounts receive Azure-managed identities that authenticate securely to Azure resources. Azure automatically manages credential rotation, reducing administrative effort while following security best practices. Combined with Azure Role-Based Access Control (RBAC), Managed Identities provide secure, passwordless authentication for automation workloads. REAL-WORLD AUTOMATION SCENARIOS Azure Automation is commonly used to reduce operational costs and eliminate repetitive administration. Typical automation scenarios include: * Automatically starting development VMs every morning * Shutting down non-production environments after business hours * Applying scheduled maintenance * Cleaning temporary files * Rotating logs * Running compliance checks * Restarting failed services * Executing patch management tasks * Responding automatically to Azure Monitor alerts * Managing hybrid infrastructure across Azure and on-premises environments A simple example involves automatically starting development virtual machines at 6 AM and shutting them down at 7 PM every weekday. Using Automation Accounts, Runbooks, Schedules, and Managed Identities, this entire process operates without human intervention while significantly reducing Azure compute costs. KEY TAKEAWAYS Azure Automation transforms repetitive operational tasks into reliable, repeatable workflows that execute automatically in the cloud or across hybrid environments. By combining Runbooks, Automation Accounts, Schedules, Hybrid Runbook Workers, Desired State Configuration, Shared Resources, and Managed Identities, organizations can improve operational consistency, strengthen security, reduce administrative effort, and significantly lower infrastructure costs. Whether you're managing a handful of virtual machines or an enterprise-scale Azure environment, Azure Automation provides the foundation for building reliable, scalable, and secure cloud operations. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support [https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support?utm_source=rss&utm_medium=rss&utm_campaign=rss].

20 jul 202615 min
aflevering Azure Managed Disks - Simply Explained artwork

Azure Managed Disks - Simply Explained

Welcome to another episode of Knowledge Nuggets with Mirko Peters. In this episode, we're exploring Azure Managed Disks, the storage technology that powers every Azure Virtual Machine. While many people simply attach a disk to a VM and move on, choosing the wrong managed disk can lead to unnecessary costs, poor performance, or both. You'll learn what Azure Managed Disks actually are, how they simplify storage management compared to the old unmanaged disk model, the five available disk types, redundancy options, encryption, snapshots, backups, and practical tips for selecting the right disk for every workload. WHAT ARE AZURE MANAGED DISKS? Azure Managed Disks are fully managed block storage volumes that Azure automatically provisions, maintains, replicates, and monitors for your virtual machines. Before managed disks were introduced, administrators had to manually create storage accounts, manage page blobs, monitor storage limits, and carefully distribute disks across multiple storage accounts to avoid performance bottlenecks. Managed Disks eliminate all of this complexity. You simply choose the disk size and performance tier while Azure handles storage accounts, replication, availability, durability, and scaling behind the scenes. By abstracting the storage infrastructure, Azure allows administrators to focus on applications instead of storage management while improving reliability, scalability, and operational simplicity. Managed Disks also automatically distribute storage across storage scale units, reducing the impact of hardware failures and increasing overall VM availability.  UNDERSTANDING THE FIVE MANAGED DISK TYPES Azure offers five managed disk options designed for different performance and pricing requirements. Ultra Disk delivers Azure's highest storage performance with extremely low latency, configurable IOPS, and throughput for mission-critical workloads like SAP HANA, enterprise databases, and high-performance analytics. Premium SSD v2 provides enterprise-level performance while allowing storage capacity, IOPS, and throughput to be configured independently. This flexibility makes it one of the most cost-efficient options for modern production environments. Premium SSD remains a popular choice for predictable production workloads where performance scales with disk size. It delivers reliable low latency for business-critical applications and virtual desktops. Standard SSD balances affordability with SSD performance, making it ideal for development, testing, web servers, and moderate production workloads. Standard HDD offers the lowest storage cost and is best suited for backup data, archives, logs, and workloads where storage capacity matters more than speed.  HOW DISK PERFORMANCE WORKS Azure Managed Disks are measured using three important performance characteristics. IOPS (Input/Output Operations Per Second) measures how many read and write operations a disk can perform every second and is particularly important for databases and transactional applications. Throughput measures how much data can be transferred every second, making it critical for file transfers, analytics, and media workloads. Latency measures how quickly data begins transferring after a request. Lower latency results in faster application response times and better user experiences. Premium SSD v2 and Ultra Disk allow administrators to configure IOPS and throughput independently from storage capacity, giving far greater flexibility than traditional disk sizing models. However, it's equally important to remember that Virtual Machines themselves also have storage performance limits, so disk performance should always be matched with the VM's capabilities.  REDUNDANCY, SECURITY, AND DISK TYPES Azure protects managed disks using multiple redundancy models. Locally Redundant Storage (LRS) maintains three synchronized copies of your data inside a single datacenter, providing exceptional durability against hardware failures. Zone-Redundant Storage (ZRS) extends protection across multiple availability zones within the same Azure region, ensuring workloads remain available even if an entire datacenter experiences an outage. Within every virtual machine, Azure supports three different disk roles. The Operating System Disk contains Windows or Linux and is required for the VM to boot. Data Disks provide persistent storage for applications, databases, and business data, with multiple disks supported depending on VM size. The Temporary Disk offers extremely fast local storage but should never be used for important information because all data is lost whenever the VM is redeployed or moved to another host. Azure also supports Ephemeral OS Disks, enabling extremely fast VM deployments for stateless workloads such as Kubernetes clusters and virtual machine scale sets.  ENCRYPTION, SNAPSHOTS, AND BACKUPS Security is built directly into Azure Managed Disks. All managed disks are automatically encrypted at rest using platform-managed encryption keys. Organizations requiring greater control can implement customer-managed keys through Azure Key Vault, while Encryption at Host provides an additional security layer protecting temporary disks and cached data. Snapshots create point-in-time copies of managed disks and are perfect for software updates, testing, and quick rollback scenarios. Azure Backup builds on snapshots by automating backup schedules, retention policies, Recovery Services Vault integration, and long-term disaster recovery. Together, these capabilities allow organizations to recover quickly from failures while meeting security, compliance, and business continuity requirements.  COST OPTIMIZATION BEST PRACTICES One of the most common mistakes in Azure is paying for oversized managed disks. Azure charges based on the provisioned disk size, not the amount of storage actually used. Choosing appropriately sized disks, deleting unattached disks, selecting the correct redundancy option, and using Premium SSD v2 instead of Ultra Disk whenever possible can significantly reduce monthly cloud costs. Standard HDD remains an excellent option for backups and archive workloads, while monitoring Azure Cost Management helps identify unused storage resources and optimization opportunities before costs increase unnecessarily.  KEY TAKEAWAYS Azure Managed Disks simplify storage management by removing the complexity of storage accounts while delivering enterprise-grade availability, security, and scalability. Understanding the differences between Ultra Disk, Premium SSD v2, Premium SSD, Standard SSD, and Standard HDD allows you to optimize both application performance and infrastructure costs. Selecting the right disk type, redundancy model, backup strategy, and encryption options ensures your Azure Virtual Machines remain secure, resilient, and cost-efficient as your cloud environment continues to grow. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support [https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support?utm_source=rss&utm_medium=rss&utm_campaign=rss].

20 jul 202615 min