Bicep Data Types Explained

Bicep is a Domain-Specific Language (DSL) for defining Azure Resource Manager (ARM) templates. It provides a concise and readable way to describe Azure resources and their properties. Understanding data types is crucial in Bicep, as they define the structure and behavior of resources.

This is a new series of articles about ‘BiCep’ technology by Microsoft – it is a game changer for resource management in the cloud – well worth investigating if you are a cloud builder!

Basic Data Types in Bicep


Strings in Bicep are sequences of characters enclosed in single or double quotes. They are used to represent text values. Strings in Bicep support interpolation, enabling dynamic content insertion.


param storageAccountName string = ‘myStorageAccount’

Multi-line Strings

Bicep supports multi-line strings using triple quotes ”’ ”’. This is useful when defining long text values. The characters entered within the opening and closing sequence are read exactly as they are, and there is no need for escaping characters.


var longText = ”’

This is a



Integers are whole numbers without a decimal point. In Bicep, integers are represented as 64-bit integers. However, the range of values may be constrained by the SDK or command-line tool used for deployment when passed as inline parameters. For instance, when deploying a Bicep template using PowerShell, integer types typically range from -2147483648 to 2147483647.

To work around this limitation, it is advisable to specify large integer values in a parameter file. Additionally, it is worth noting that resource types may impose their own restrictions on integer properties.


Note: Bicep does not currently support floating-point, decimal, or binary formats.


param numberOfInstances int = 3


Boolean values represent true or false. These data types are useful for logical decisions and conditions in your code.

Note: Avoid enclosing the value in quotation marks.


param useSSLEncryption bool = true

Complex Data Types


Objects in Bicep are collections of key-value pairs enclosed in curly braces {}. They are used to represent complex data structures and are commonly used to define properties of Azure resources. Each key in an object is a property name, and the corresponding value is the property value.

Objects allow you to group related properties together, which can improve the readability and maintainability of your Bicep code. They also enable you to pass structured data to resources or modules, making your templates more flexible and reusable.


var storageAccountConfig =
name: ‘myStorageAccount’,
type: ‘Standard_LRS’,
environment: ‘production’,
department: ‘finance’

You can access properties of an object using dot notation (.). For example, to access the name property of storageAccountConfig’, you would use ‘’.


Arrays in Bicep are ordered collections of values enclosed in square brackets []. They are used to represent lists of items. Arrays can be declared in a single line or multiple lines, providing flexibility in coding.

Use commas (,) to separate values in single-line declarations, while in multiple-line declarations, they are not required.


var instanceTypes = [

Secure Objects

Bicep has introduced secure objects to enhance security by protecting sensitive information. These objects are encrypted and provide an extra layer of protection for confidential data. Thus, to enhance the security of a string or object, apply the @secure() decorator to it.


param mySuperSecretObject object

Secure Strings

Similar to secure objects, secure strings provide additional security for sensitive information. These strings are encrypted and are designed to prevent unauthorized access to critical data.


param intAsString string
var num = int(intAsString)

Now that we have covered the supported data types in Bicep, let’s explore how user-defined data types can further enhance your Bicep code in the next section.

User-Defined Data Types in Bicep

Bicep extends its supported data types by enabling the definition of user-defined types using the `type` statement. This feature enhances code reusability and simplifies Bicep projects by allowing developers to define custom types based on primitive literals, arrays, and objects.

User-defined types can be utilized across a Bicep file, including in `param` statements and object type properties, making it easy to encapsulate complex data structures and reuse them throughout your code.

This capability empowers developers to create efficient and maintainable infrastructure as code solutions. Whether representing tagged union types or importing types from external sources, Bicep’s user-defined data types provide the flexibility and expressiveness needed for robust Azure deployments.


type SkuType = ‘Standard_LRS’ | ‘Standard_GRS’
type StorageAccountConfig = {
name: string
sku: SkuType



So then, we have learned that mastering data types in Bicep is essential for creating concise and effective Azure Resource Manager templates. By understanding and utilizing the various data types available, you can accurately define the structure and behavior of your Azure resources, leading to more efficient deployments.

Happy cloud building!

How to Talk to Customers to Find Out Their Pain Points When Building an AI Startup?

Building an AI startup is an innovative and exciting endeavor. It’s vital to have a deep understanding of your target audience’s pain points and needs to create a successful business. In this article, we will explore different techniques for engaging with potential customers, identifying their pain points, and understanding real needs that go beyond surface-level wants and preferences.

A mentor of mine said to me once ‘if someone is not paying you money for what you are producing, then you dont ahve a business, yhou have a hobby’ … Having a hobby is fine, but dont make the mistake that it is a business – they are very very different things! … building a business is HARD WORK! …. it involves pain – you do something, take a beating, break it down, build it again, go in for the next fight … success rarely happens overnight – but ther eis a fast track to speed things up – heres a simple secret for you … TALK TO CUSTOMERS.. ASK THEIR PAIN-POINTS its reallly that simple 🙂

Key Takeaways

  • Talking to customers is crucial to building a successful AI startup.
  • Prioritizing customer insights, understanding pain points, and aligning with desires can drive innovation and ensure success.
  • Engage with potential customers to gain valuable insights.
  • Identify customer pain points and real needs to tailor your AI solutions.
  • Align AI solutions with customer desires while streamlining processes.

Engaging with Potential Customers

When building an AI startup, the first step in understanding customer pain points is directly talking and engaging with your potential customers. By building relationships with your target audience, you can gain valuable insights into their needs and desires. Here are some effective techniques to engage with customers:

  • Conduct surveys: Online surveys can help you gather basic information about potential customers, including demographic data and their preferences for AI solutions.
  • Participate in online communities: Join discussion groups related to your target audience and AI to engage with potential customers. Leave comments, answer questions, and ask for feedback to build relationships.
  • Host webinars: Webinars are a great way to educate your target audience about the benefits of AI and your specific solutions. They also offer an opportunity to gather feedback and engage with potential customers in real-time.

Identifying Customer Pain Points

Developing AI solutions that address customer needs starts with identifying their pain points. Pain points are the challenges and frustrations that customers face when trying to achieve their goals or complete tasks.

There are several methods for identifying customer pain points:

  • Surveys and feedback forms: Ask customers to share their challenges and areas where they struggle through online surveys, feedback forms, or in-person interviews.
  • Customer service interactions: Analyze customer service interactions and support tickets to identify recurring issues and complaints.
  • Social media: Monitor social media channels to gain insights on customer frustrations and complaints.

Real-Life Example

When launching their subscription-based meal kit delivery service, Blue Apron, the company conducted extensive market research and customer surveys to identify pain points in the meal preparation process. They found that customers often struggled with meal planning and grocery shopping, which led to waste and dissatisfaction with their meals.

Using this insight, Blue Apron developed AI-powered algorithms that could suggest meals based on dietary preferences and provide precise ingredients and portions to eliminate food waste. As a result, they were able to provide a solution that addressed a key pain point for their customers, setting them apart from competitors and driving growth in their business.

Understanding Real Customer Needs

Building an AI startup that solves genuine problems requires a deep understanding of your customers’ real needs.

Apart from feedbacks through surveys, interviews, and interactions with focused groups, observing how customers interact with your product or service can also provide valuable information. Another way of understanding customer needs involves analyzing data collected from customer interactions with your business.

Remember that customers’ needs evolve over time, so keeping an open dialogue throughout the entire process is essential. Listening to the voice of the customer helps to ensure that your startup solves their real needs.

Strategic AI: Crafting Value-Driven Solutions for Customer Impact

AI has revolutionized numerous industries, particularly in the area of automating repetitive tasks. However, it’s important to keep in mind that automating tasks solely for the sake of doing so may not always be beneficial for the customer.

The true potential of AI in automating tasks is fully realized when startups invest time and energy in understanding the genuine wants of their customers. The journey begins with authentic conversations, active listening, and a commitment to crafting AI solutions that genuinely impact the lives of those you aim to serve. It’s not just about technology; it’s about creating value that deeply resonates with the human experience.

Further, aligning AI solutions with customer desires is a critical driver of innovation. Moving beyond mere task automation, you should aim to add tangible value to the overall customer experience. This strategic alignment sets the venture apart from competitors and shapes a unique value proposition tailored to the customer base.

Case Study: Company X

Company X is a leading AI startup that has successfully leveraged customer insights to drive innovation. The company invested heavily in understanding their customers through surveys, focus groups, and one-on-one interviews. By listening to their customers’ thoughts and concerns, Company X was able to develop cutting-edge solutions that met their needs effectively.

As a result, Company X has achieved significant success in the marketplace, winning awards for their innovative solutions and gaining numerous customers. By taking a customer-centric approach, Company X has been able to differentiate itself from other AI startups and positioned itself as a market leader.


In short, for a successful AI startup – talking to your potential customers and understanding their pain points is essential when building an AI startup. By prioritizing customer insights and aligning with their genuine needs, you can drive innovation, create solutions that truly address their challenges, and ensure the success of your venture.

Happy learning! 

Using Azure Immersive Reader Technology to Help People Consume and Understand Text Based Information

Azure Immersive Reader Technology is revolutionizing the way people engage with text-based information. With its powerful AI capabilities, this technology enhances reading comprehension and enables users of all ages and reading abilities to consume and understand text more effectively. Whether it’s translating text into multiple languages, having text read aloud with synchronized highlighting, or using visual aids to support understanding, it opens up a world of possibilities for inclusive education and effective information consumption.

Understanding Azure Immersive Reader

Azure Immersive Reader is a cloud-based service powered by artificial intelligence (AI) that allows you to consume and comprehend text-based information more effectively. Leveraging advanced natural language processing (NLP) capabilities, it facilitates various features aimed at enhancing reading experiences for individuals with different learning styles and abilities.

Key Features and Benefits

Azure Immersive Reader incorporates literacy-enhancing features that have been proven effective. These include reading aloud, language translation, and visual aids, all of which help users engage with text and deepen their understanding.

  • Text-to-Speech Capabilities: One of the standout features of Azure Immersive Reader is its text-to-speech functionality, which converts written text into spoken words. This feature not only aids individuals with visual impairments but also benefits auditory learners and those who prefer auditory stimuli for comprehension.
  • Customizable Formatting Options: The ability to customize text formatting, including font size, spacing, and background color, enables users to tailor their reading experience according to their preferences and needs. This flexibility ensures optimal readability and reduces cognitive strain, particularly for individuals with dyslexia or attention-related challenges.
  • Translation: With support for over 100 languages, Azure Immersive Reader ensures that text-based information is accessible to users around the world. Whether users are reading in their native language or seeking to understand foreign texts, the built-in translation feature facilitates seamless comprehension and fosters cross-cultural communication.
  • Grammar and Syllabification Tools: For language learners and individuals grappling with complex grammatical structures, Azure Immersive Reader offers grammar and syllabification tools that break down sentences into more digestible segments. This feature enhances comprehension and facilitates language acquisition by providing contextual cues and linguistic scaffolding.

Getting Started Azure Immersive Reader Technology

Integrating Azure Immersive Reader into your applications or platforms is a straightforward process. Follow these steps to begin leveraging its transformative capabilities:

  1. Sign Up for Azure: If you haven’t already, create an Azure account to access the Immersive Reader service. Navigate to the Azure portal and follow the prompts to set up your account.
  2.  Enable Immersive Reader:
    Once logged into the Azure portal, navigate to the AI Services section and select Immersive Reader. Follow the instructions to enable the service and configure its settings according to your requirements. 
  3. Integrate Immersive Reader: API
    Integrating Immersive Reader into your applications or websites is facilitated through the Immersive Reader API. Access the API documentation for comprehensive guidance on implementation, including code samples and best practices. 
  4. Customize User Experience:
    Tailor the user experience by exploring the various customization options offered by Immersive Reader. Experiment with text formatting, language settings, and additional features to optimize accessibility and usability for your target audience. 
  5. Test and Iterate:
    Before deploying Immersive Reader-enabled solutions to your audience, thoroughly test the functionality to ensure seamless performance across different devices and platforms. Solicit feedback from users and iterate on your implementation to address any usability issues or accessibility concerns.

Security and Compliance of Azure Immersive Reader Technology

Azure Immersive Reader Technology boasts robust security measures and adheres to industry standards. With Microsoft’s substantial investment of over $1 billion annually in cybersecurity research and development, the service upholds the highest security protocols. As a leading cloud provider, Azure sets itself apart with its extensive certifications, demonstrating compliance with various industry regulations. Opting for Azure Immersive Reader Technology means choosing a trusted and compliant solution.

Moreover,Azure Immersive Reader Technology prioritizes data privacy. It does not store any customer data, ensuring an additional layer of protection for your information.

Read more:

Happy learning!

What is the future for engineers – is AI going to take all our jobs?

Welcome to our article where we explore an intriguing question that has been on the minds of many engineers: What is the future for engineers? More specifically, is AI going to take all our jobs?

The rapid advancements in artificial intelligence (AI) have raised concerns among engineers about the future of their careers. Many worry that AI will replace human jobs, leaving engineers unemployed. But is this fear justified and are robots goign to take over the world?!

Join us as we delve into the impact of AI on engineering jobs and whether it is a real threat or an opportunity for growth. We’ll debunk the misconceptions surrounding AI and its role in the development of engineering technologies. We’ll also examine the skills and career prospects that lie ahead in an era of automation and AI integration.

The Advancements of AI: Friend or Foe to Engineers?

AI has made significant advancements in recent years, revolutionizing various industries, including engineering. While some engineers see AI as a threat that could replace their jobs, others view it as a valuable tool that can enhance their work. In this section, we will delve into the advancements of AI, its potential benefits and challenges for engineers, and examine whether it is a friend or a foe to the engineering profession.

AI has rapidly evolved, thanks to advancements in machine learning and deep learning algorithms. Engineers can now leverage AI technologies to perform complex calculations, make accurate predictions, and automate repetitive tasks. This has the potential to greatly increase efficiency and productivity in various engineering domains.

AI is not just limited to replacing human tasks; it also has the ability to augment engineers’ capabilities. For example, AI-powered tools can assist in designing and optimizing complex systems, helping engineers explore innovative solutions and achieve optimal performance. These advancements have the potential to revolutionize the way engineers work and lead to breakthroughs in engineering innovation.

However, there are also challenges to consider. One of the main concerns is the potential impact of AI on job displacement. As AI technologies become more advanced, there is a possibility that certain tasks traditionally performed by engineers may be automated. This raises questions about the future of engineering jobs and the skills that engineers need to develop to remain relevant in an AI-driven world.

Furthermore, ethical considerations and biases in AI algorithms need to be addressed to ensure that AI is used in a fair and responsible manner. Engineers must be vigilant in designing and implementing AI systems that uphold ethical standards and minimize biases that may arise from training data.

Real AI vs Perceived AI: Debunking Myths in Engineering Professions

In this section, we will delve into the realm of AI myths and review differences between real AI and its perceived counterpart.

The Misconceptions of Artificial Intelligence

Artificial intelligence has long been shrouded in myths and misconceptions. One prevalent myth is that AI will completely replace human engineers, rendering their expertise obsolete. However, the truth is that AI acts as a tool to augment and enhance engineering work, rather than replacing it entirely. By dispelling these misconceptions, we can better understand the true nature and potential of AI in the engineering profession.

“The belief that AI will eliminate the need for human engineers is a common misconception. In reality, AI works in collaboration with engineers, providing them with powerful tools and insights to tackle complex problems more efficiently.”

It is essential to distinguish between real AI and the perceived version, as the latter often stems from a lack of understanding about the capabilities and limitations of AI technologies.

The AI Job Market Trends Transforming Engineering Careers Today

One of the key trends in the AI job market is the increasing demand for professionals with expertise in AI technologies. As companies across various sectors recognize the potential of AI, they are actively seeking engineers with specialized knowledge in areas such as machine learning, robotics, and natural language processing.

The demand for AI engineers is skyrocketing, with companies investing heavily in AI-driven projects. This presents a significant opportunity for engineering professionals to carve out a successful career in this rapidly growing field.

Like the introduction of the car, and its displacement of an entire industry surrounding horses as the primary mode of transport, the rise of automation in modern engineering has also led to a shift in job roles. While some traditional engineering tasks are being automated, new opportunities are emerging for engineers to work on developing and maintaining AI systems, integrating AI into existing processes, and creating innovative solutions. This requires engineers to acquire new skills and adapt to the changing demands of the job market.

The ability to collaborate with AI technologies and apply them effectively in engineering projects has become a highly sought-after skill. Engineers who possess a strong understanding of AI concepts and can leverage AI tools and algorithms are in high demand wnd will continue to be so.

Furthermore, the demand for engineers with a combination of technical skills and domain-specific knowledge is on the rise. For example, engineers with expertise in AI for healthcare or AI for manufacturing have a unique advantage in the job market, as industries increasingly look for specialists who can apply AI technologies to solve industry-specific challenges.

It is essential for engineers to continuously update their skills and stay ahead of the curve to remain competitive in the evolving AI job market. By acquiring the necessary expertise in AI technologies and staying informed about the latest trends, engineers can unlock exciting career opportunities and make a significant impact in the field of engineering.

Engineers’ Unemployment Concerns: How Many Jobs Has AI Replaced?

AI automation in engineering

The fear of unemployment among engineers due to the impact of AI is a valid concern. As technology continues to advance and automation becomes more prevalent, it is natural for engineers to have concerns about the future of their careers.

Automated Efficiency: Positive or Negative for Employment?

Automation has undoubtedly brought about increased efficiency and productivity in various industries, including engineering. However, there is a debate about whether this increased efficiency is positive or negative for employment. On one hand, automation can streamline processes and free up time for engineers to focus on more complex tasks. On the other hand, it can lead to job displacement as certain roles become redundant. AI implementation requires engineers with specialized skills to develop and maintain the systems, and the integration of AI in engineering processes can lead to the creation of new roles and fields that were previously non-existent.

Government’s Role in Facilitating Skills Transition

The government plays a crucial role in facilitating the transition of skills in the engineering sector in an AI-driven world. Recognizing the importance of upskilling and reskilling, governments around the world are implementing initiatives to support engineers in adapting to the demands of the future.

Through funding and grants, governments are investing in programs that provide training and education opportunities for engineers. These initiatives aim to bridge the gap between traditional engineering skills and emerging AI-driven technologies. By creating collaborative partnerships between academia and industry, governments also foster innovation and help engineers gain practical experience in AI-related projects.

In my opinion, engineers have a promising future ahead. By embracing lifelong learning and seizing the opportunities presented by AI, engineers can pivot their skills and envision a future career that is not threatened by automation but rather driven by innovation and creativity – as I’ve said before – stand still as an engineer, and you become outdated very very fast!


The future of engineering in the age of AI presents a unique blend of challenges and opportunities. Throughout this article, we have explored the impact of AI on engineering careers and debunked misconceptions surrounding its development. We have witnessed the advancements of AI and how it can be both a friend and a foe to engineers. However, as the landscape evolves, it is crucial for us, as engineers, to adapt and embrace the opportunities that come with AI.

The rise of AI does not spell the end of engineering careers. Instead, it offers a multitude of opportunities for us to make a significant impact. Collaboration between humans and AI allows for innovative breakthroughs and pushes the boundaries of engineering. Emotional intelligence also plays a crucial role in understanding human needs and integrating AI systems effectively. By harnessing these skills, we can lead the way in engineering AI research and development.

Get learning, and get coding!

Bicep Resources: What They Are and How to Use Them

When deploying resources to Azure, developers often need to manage a variety of resource types, such as virtual machines, storage accounts, and networks. Bicep, a domain-specific language for deploying Azure resources, simplifies this process by providing a declarative syntax that abstracts away the complexities of Azure Resource Manager (ARM) templates. In this article, we’ll explore what Bicep resources are and how to use them effectively.

This is a new series of articles about ‘BiCep’ technology by Microsoft – it is a game changer for resource management in the cloud – well worth investigating if you are a cloud builder!

Understanding Bicep Resources

In Bicep, a resource is a unit of deployment that represents a single Azure resource, such as a virtual machine or a storage account. Resources are defined using the resource keyword, followed by the resource type and name. Here’s a basic example of defining a resource in Bicep:

Bicep Resource Simple Example

In this example, myStorageAccount is the name of the resource, Microsoft.Storage/storageAccounts@2021-06-01 is the resource type, and the object following the = sign contains the properties of the resource.

Using Bicep Resources


The declaration of a resource in Bicep includes the resource type, name, and properties. Here’s an example of declaring a virtual network resource:

Res Declaration

In this example, virtualNetwork is the name of the resource, Microsoft.Network/virtualNetworks@2021-02-01 is the resource type, and the properties object contains the address space of the virtual network.

Resource Name

The resource name is specified as the first argument in the resource declaration. It provides a unique identifier for the resource within the Bicep file.


The location property specifies the Azure region where the resource will be deployed. It ensures that the resource is deployed to a specific geographic location.


Tags are key-value pairs that can be used to categorize resources in Azure. They can be used for organizing deployed resources, cost management, and other purposes.

Managed Identities for Azure Resources

Managed identities for Azure resources provide an identity for applications to use when accessing Azure resources. You can enable managed identities for a resource using the identity property.


In this example, myAKSCluster is the name of the resource, eastus is the location, and { environment: ‘dev’ } are the tags. The identity is set to SystemAssigned.

Resource-Specific Properties

Resource-specific properties vary depending on the type of resource being deployed. For example, a virtual machine resource may have properties related to its size, operating system image, and networking configuration. These properties are specified within the properties object of the resource declaration.

The following example sets the access tier property for a storage account to “Cool” using the Bicep syntax:

Referencing an Existing Resource

Sometimes, you may need to reference an existing resource in your Bicep template. You can do this using the existing keyword. Here’s an example of referencing an existing storage account:

Creating a Child Resource

Child resources are resources that are created as part of another parent resource. You can define child resources using the child keyword. Here’s how you can create a child resource:

In this example, childResource is a child resource of parentResource.

Using Scope Extension Resources

Scope extension resources allow you to define resources that are scoped to a specific resource group or subscription. Here’s an example of using a scope extension resource:

Managing Resource Dependencies

When deploying resources, it’s essential to ensure that certain resources are deployed before others. For instance, you must have a logical SQL server in place before deploying a database. This relationship is established by specifying one resource as dependent on another. The order of resource deployment is determined by implicit and explicit dependencies.

Azure Resource Manager assesses these dependencies and deploys resources in the order of their dependencies. When resources are not dependent on each other, Resource Manager deploys them concurrently. Dependency definitions are only necessary for resources deployed within the same Bicep file.


The above code depicts dependency by referencing the nameServers property of the uniqueDnsZone resource in the customResource declaration. This means that the customResource depends on the uniqueDnsZone resource, as it needs the nameServers information from the DNS zone to function correctly. This dependency ensures that the DNS zone is created before the custom resource, fulfilling any prerequisites for the custom resource’s configuration.


Bicep resources are a powerful feature that simplify the deployment of Azure resources. By defining resources in a declarative manner, you can easily create, manage, and reference Azure resources in your Bicep templates. With the examples provided, you should now have a better understanding of how to use Bicep resources in your own deployments.

Happy cloud buildiong 😀

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