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How To Use AWS CodeBuild To Make MacOS Apps
Amazon AWS CodeBuild service.
CodeBuild is an Amazon Web Service tool for automating the building of software. Now you can use it to build macOS and iOS apps.
Amazon Web Services (AWS) is a comprehensive set of cloud computing services that allow you to ditch your on-premises hardware. With AWS you can shift much of your IT infrastructure to the cloud, leveraging the power of Amazon's vast resources for your compute workloads.
AWS offers a limited free tier for some cloud services, but most services require a monthly or hourly fee. In some cases, you pay only for what you use.
CodeBuild is a web service Amazon provides to allow developers to use Continuous Integration and Continuous Delivery (CI/CD) pipelines to automate building and delivering software and online services.
With CodeBuild, you can use Amazon cloud resources to build most of your software and deliver it. All without having to manage the details of the build server hardware and configuration.
Using development environment container images, you can also specify custom-build server configurations on AWS to build and deploy your workloads. AWS uses Docker container images for environment deployment.
There's also a Docker desktop app for Mac OS.
The idea with container images is so you can configure your build environment once and save it to an image. You can then deploy the image anywhere and avoid having to do the configuration each time.
In an AWS blog post Sebastien Stormacq of Amazon announced Mac support in CodeBuild. Since most apps for Apple platforms use Apple's own Xcode development tools to perform builds, you'll need to run Xcode on a Mac in most cases.
Along with Source Code Management (SCM) tools such as git, GitHub, and GitLab, your build system can be fully automated using AWS CodeBuild.
You can also use CodeBuild to create tvOS and watchOS apps.
CodeBuild leverages Amazon's other web services, which include general compute, images, and authorization services.
Getting started
CodeBuild isn't one of the AWS services included in Amazon's free tier, so you'll need to pay for it.
There are two models of pricing for CodeBuild: one in which you pay for a full 24-hour cycle, and one where you pay only for the actual hours used on AWS when you use CodeBuild.
Oddly, this is in part because Apple's macOS license agreement requires a minimum 24-hour period for any "leased permitted developer services".
All of the AWS CodeBuild Mac services run on Mac minis in one of two configurations:
AWS operates on the concept of cloud instances that use Amazon's own Elastic Compute Cloud (EC2). Each instance represents a virtual computing resource that runs in the cloud - effectively a cloud server from the consumer's standpoint.
In the AWS free tier, you can get a whopping 750 hours per month for twelve months, but this doesn't include the CodeBuild service.
CodeBuild uses two cloud capacity models, called on-demand and reserved capacity. Amazon calls them 'capacity fleets.'
If you're using the on-demand model you get automatic scaling, and pay only for build minutes used. With reserved capacity, you reserve an entire 24 hours or more for build and those AWS instances can't be released until the 24 hours have elapsed.
The default macOS CodeBuild image includes all the tools you need, including Xcode, the .NET SDK, Go, Java, Fortran, Kotlin, clang and Swift compilers, and a host of web-based tools. You can also create custom images if you like.
AWS regions
AWS has various regions around the world, with the Mac instances operational in Ohio, Virginia, Oregon, Frankfurt, and Sydney. You can specify regions in your AWS configuration, or let the service decide where to run the instances.
Amazon has a full table of which AWS services are available in which regions.
Configuration
Once you've signed up for CodeBuild, you'll need to configure your Mac services by going to the reserved capacity macOS fleet page and following the instructions there.
You can also use AWS's Virtual Private Cloud services. Once instances are provisioned and set up, it takes about eight to ten minutes for them to come online and be ready to use.
Obviously, the CodeBuild service isn't cheap, but for large and mid-sized organizations it could save money. Without a cloud build service, you'll need to have build and network infrastructure to run builds - and employees to manage it.
By using cloud build services, you can let AWS automate and manage your builds so you don't have to.
Serverless Computing With AWS Lambda
Serverless computing has transformed how developers build and deploy applications. It removes the burden of managing servers and infrastructure, allowing you to focus on code. AWS Lambda, one of the pioneers in serverless architecture, is at the forefront of this revolution. It provides scalable, event-driven computing without the need for server management. In this article, we'll explore AWS Lambda, its advantages, use cases, and best practices for leveraging its full potential.
What is AWS Lambda?
AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS). It allows developers to run code without provisioning or managing servers. When you upload your code to AWS Lambda, it automatically scales based on incoming requests or events. AWS Lambda can execute code in response to a wide variety of events such as HTTP requests, file uploads to S3, changes in DynamoDB tables, or events from other AWS services.
The core of AWS Lambda is its simplicity. You write code in supported languages like Python, JavaScript, or Java. You then upload it to AWS Lambda and configure triggers. When an event happens, AWS Lambda runs your code. It handles everything from provisioning resources to scaling and monitoring, freeing you to focus solely on functionality.
How Does AWS Lambda Work?
AWS Lambda works on an event-driven model. Each time a configured event occurs, it invokes the Lambda function. Let's break down its workflow:
Define a Function: Write your code and upload it to Lambda. You can use the AWS Management Console, CLI, or SDKs.
Set Up Triggers: Configure which events will trigger your function. These could be anything from an API Gateway HTTP request to a new file uploaded in S3.
AWS Lambda Invokes the Function: When a trigger event occurs, AWS Lambda allocates compute resources and executes your code.
Scaling and Execution: AWS Lambda automatically scales by running your code in parallel based on the incoming traffic. If there are multiple events, Lambda can execute multiple instances simultaneously.
Pay for Usage: You only pay for the time your code runs. Billing is based on the number of requests and the duration your code runs, measured in milliseconds.
AWS Lambda's architecture ensures that you don't over-provision resources. You save costs because you pay only for the actual computing time, unlike traditional server models that require you to pay for idle resources.
Advantages of AWS Lambda
AWS Lambda provides several compelling benefits:
No Server Management: Lambda handles server management, patching, and scaling. You never have to worry about configuring or maintaining servers.
Automatic Scaling: Lambda scales automatically based on incoming events. There's no need to worry about traffic spikes or underutilized servers.
Cost Efficiency: You pay only for the execution time and number of requests. This model can significantly reduce costs, especially for applications with unpredictable traffic patterns.
Event-Driven Execution: Lambda is ideal for executing code in response to specific events. This feature makes it perfect for building reactive applications and microservices.
Seamless Integration with AWS Services: Lambda integrates natively with other AWS services like S3, DynamoDB, API Gateway, and CloudWatch. This integration enables you to build sophisticated applications using existing AWS services as building blocks.
Reduced Operational Overhead: With AWS Lambda, you don't need to manage scaling, maintenance, or capacity planning. This reduction in overhead frees up resources and time for development and innovation.
Use Cases for AWS Lambda
AWS Lambda is highly versatile, making it suitable for a wide range of use cases:
Microservices: AWS Lambda is a great fit for microservices. Each microservice can be represented as a separate Lambda function that interacts with other services through REST APIs or events.
Real-Time File Processing: Lambda can process files in real-time. For instance, you can configure a Lambda function to trigger whenever a new image is uploaded to an S3 bucket. The function could then resize the image, apply filters, or convert formats.
Backend for Web and Mobile Applications: Lambda can serve as a backend for web or mobile applications. By using AWS API Gateway in conjunction, you can expose Lambda functions as RESTful APIs to handle client requests.
Data Processing: Lambda can perform data transformations, filter data streams, or run analytics in response to incoming data. It's often used with AWS Kinesis or DynamoDB to process real-time data.
Scheduled Tasks: Lambda can replace traditional cron jobs by using CloudWatch Events to schedule task execution. This setup is ideal for recurring tasks like database backups or cleanup operations.
Chatbots and Voice Assistants: AWS Lambda can be integrated with Amazon Alexa or other chatbots to handle user interactions and provide real-time responses based on user input.
Security and Compliance Automation: Lambda can respond to security events or changes in your AWS account. For example, it can be triggered when a new IAM role is created, ensuring it adheres to security best practices.
Best Practices for Using AWS Lambda
To get the most out of AWS Lambda, it's essential to follow some best practices:
Keep Functions Lightweight: Keep your Lambda functions lightweight by including only the necessary dependencies. A smaller package size results in faster cold start times.
Optimize Memory and Timeout Settings: Optimize memory allocation and timeout settings based on your function's workload. Higher memory allocation can reduce execution time, but it may increase costs. Find the balance that works for your application.
Minimize Cold Starts: A cold start occurs when a new Lambda container is initialized. Reduce cold start times by using the right runtime and limiting dependencies.
Use Environment Variables: Use environment variables to pass configuration details to your functions. This practice avoids hardcoding and makes it easy to update configuration without redeploying the function.
Monitor and Log with CloudWatch: Use CloudWatch for logging and monitoring function executions. Set up alarms and dashboards to gain insights into performance and errors.
Leverage AWS Lambda Layers: Lambda layers allow you to package and reuse code across multiple functions. Use layers for common libraries or utilities to reduce deployment size and complexity.
Secure Lambda Functions: Use IAM roles and permissions to secure Lambda functions. Grant the minimum privileges required to perform the function's tasks.
Use Versioning and Aliases: Use function versioning to maintain different iterations of your Lambda function. Use aliases to route traffic between versions seamlessly.
Error Handling and Retries: Implement proper error handling and define retry policies. Use AWS Step Functions if you have complex workflows requiring multiple retries and error-handling mechanisms.
Future of Serverless Computing with AWS Lambda
AWS Lambda has paved the way for a new computing paradigm. As more organizations embrace cloud-native and microservices architectures, serverless computing will continue to grow. AWS is constantly adding new features to Lambda, such as better support for container images and enhanced performance.
The future of serverless computing will see increased integration with machine learning, IoT, and edge computing. AWS Lambda's ability to run code at the edge with services like Lambda@Edge shows its potential for low-latency applications. With advancements in cold start reduction and support for new runtimes, AWS Lambda will further solidify its position as the go-to service for serverless applications.
In conclusion, AWS Lambda represents a powerful tool for modern application development. It simplifies infrastructure management and enables rapid innovation. Whether you're building a new application or modernizing an existing one, AWS Lambda's flexibility, scalability, and cost efficiency make it an essential service in any developer's toolkit. As the adoption of serverless computing continues to rise, AWS Lambda will remain a key player in shaping the future of cloud computing.
Top 3 Things To Know About Amazon Honeycode
Amazon Web Services' new Amazon Honeycode – now in beta -- allows customers to build mobile and web applications without writing any programming code.
Amazon Web Services' new Amazon Honeycode – now in beta – puts AWS into the no-code application competition with Microsoft Power Apps and Google Cloud's AppSheet.
Designed for citizen developers, the fully managed service allows customers to build mobile and web applications without writing any programming code.
Amazon Honeycode allows customers to bypass hiring developers to build often-costly custom applications – or resorting to emailing spreadsheets or documents -- for tasks ranging from approving purchase orders, inventory management and conducting simply surveys, to managing complex project workflows for multiple teams or departments, according to AWS.
"Today's spreadsheets fill an important gap between mass-produced packaged applications and custom-built code created by teams of dedicated developers," AWS "chief evangelist" Jeff Barr wrote in a blog post. "Every tool has its limits, however. Sharing data across multiple users and multiple spreadsheets is difficult, as is dealing with large amounts of data. Integration and automation are also challenging and require specialized skills. In many cases, those custom-built apps would be a better solution than a spreadsheet, but a lack of developers or other IT resources means that these apps rarely get built."
Amazon Honeycode combines the familiar interface of a spreadsheet with the data management capability of a database. Customers can use its visual application builder to create interactive web and mobile applications backed by an AWS-built database to perform tasks including tracking data over time, notifying users of changes, routing approvals and facilitating interactive business processes, according to AWS.
San Francisco's Slack Technologies, which offers a channel-based messaging platform, and Mountain View, Calif.-based SmugMug, an image and video sharing and hosting service, are among the AWS customers planning to use Amazon Honeycode, according to the cloud provider.
Amazon Honeycode And The APN
AWS Partner Network (APN) members can use Honeycode internally to improve their business processes and productivity needs, according to Meera Vaidyanathan, AWS' director of product management for Amazon Honeycode.
"Honeycode is a great product for consulting/services partners to use to build apps for their customers that they might not have had time to develop with code," Vaidyanathan said. "We are working on enabling Honeycode in the APN program. Right now, partners can sign up today and start learning, building and using Honeycode."
AWS decided on the Amazon Honeycode name to entice business users for whom coding is out of reach or a little daunting, according to Vaidyanathan.
"Honey represents something sweet, enjoyable and familiar," Vaidyanathan said. "By bringing honey and code together, we wanted the service name to convey that building apps is now accessible to business users, and that it can even be fun."
Amazon Honeycode Basics
Amazon Honeycode currently is available in beta in AWS' U.S. West (Oregon) cloud region only, although AWS said it would be expanded to additional regions soon. Customers can build applications with up to 20 users for free and pay only for the users and storage for larger applications, according to AWS.
The service includes templates for common applications including simple to-do lists, customer tracking, simple surveys, inventory management, content tracking, time off reporting, event management, team task tracking, weekly demo schedules, field service agents and purchase order approvals. Users also can import data into a blank workbook and use the spreadsheet interface to define the data model and design application screens with objects like lists, buttons and input fields.
"You can customize these apps at any time, and the changes will be deployed immediately," Barr said. "You can also start with an empty table or by importing some existing data in CSV (comma-separated values) form. You can also take advantage of a repertoire of built-in, trigger-driven actions that can generate email notifications and modify tables."
Amazon Honeycode's built-in functions include common ones associated with spreadsheets and Honeycode-specific functions, including FindRow, which Barr said was a more powerful version of the Excel VLOOKUP function.
Applications can scale up to 100,000 rows in each workbook. Amazon Honeycode automates the building and linking of the three tiers of functionality found in most business applications -- database, business logic and user interface, according to AWS.
Honeycode has two application programming interfaces (APIs) -- GetScreenData and InvokeScreenAutomation -- that allow users to programmatically interact with Honeycode apps. The APIs can be used to read, write, update or delete data stored in Honeycode workbooks as users interact with Honeycode apps. External applications also can use the APIs to interact with Honeycode-built applications.
Honeycode-built applications can be shared with a click of a button. Users with mobile devices can install the Honeycode Player – there are iOS and Android versions -- to use apps shared with them.
AWS has an online Amazon Honeycode Forum, where users can post questions, find Honeycode announcements including updates, access Honeycode courses, read and watch how-to articles and videos, and find other resources.
A 'Very Lightweight' Tool
Amazon Honeycode is aimed squarely at citizen developers – non-professional developers – who are end-users inside enterprises, according to Jason Wong, research vice president at Gartner, the Stamford, Conn.-based research and advisory firm.
"The tool is very lightweight in this initial release and would not be a substitute for any custom solutions that partners would be building using AWS," Wong said.
It's unlikely that partners would use Amazon Honeycode themselves due to the "limited functionality of the tool," according to Wong.
"Over time, Amazon Honeycode could potentially be used by partners to build a no-code configurable user interface – e.G., a form or app -- into parts of a larger complex application that runs on AWS," he said. "Partners could also build and contribute app templates if a marketplace, catalog or exchange is offered by AWS at some point in the future. Gartner sees a platform marketplace as a key value driver for low-code platforms to create critical mass adoption."
Amazon Honeycode is very "lightweight" functionally compared to Microsoft's and Google's no-code application development platforms – Microsoft Power Apps, which launched in 2016, and Google Cloud's AppSheet -- according to Wong. Google acquired AppSheet, a 6-year-old Seattle startup, in January, for undisclosed terms.
"Both of those products have been in market for many years and, more importantly, are tied to Microsoft Office 365 and Google G Suite respectively," Wong said. "AWS has no such office productivity offering to leverage in positioning AWS Honeycode to reach potential citizen developer users."
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