Day: July 11, 2023

Cloud-native technology has been changing the way payment services are architected. In 2020, I presented a series with insights from real implementations adopting open-source and cloud-native technology to modernize payment services.

The architectures presented were based on open-source cloud-native technologies, such as containers, microservices, and a Kubernetes-based container platform. The major omission in this series was to avoid discussing any aspect of cloud-native observability. This series will take a look at fixing that omission with an open-source standards-based cloud-native observability platform that helps DevOps teams control the speed, scale, and complexity of a cloud-native world for their financial payments architecture.

GraalVM, as the name suggests, represents the Holy Grail of modern cloud-native development by boosting the performance of Java applications and, at the same time, making highly efficient and seamless polyglot programming a reality. But what exactly lies behind these claims? In this article, we will look into the platform’s evolution and prospects to understand why you will benefit from integrating the technology in production. We will also summarize the key aspects of GraalVM licensing, including the new license introduced by Oracle in 2023.

Benefits of GraalVM for Java Development

GraalVM is a platform based on Java HotSpot VM implemented in Java. It includes the Java Development Kit (JDK), the advanced just-in-time compiler, the ahead-of-time compiler, and tools for adding programming languages to the project. Its goal is accelerating JVM-based applications and providing a foundation for multilingual programming. The benefits of the technology for Java developers can be summarized as follows:

The Juran Trilogy: Empowering Management, Testers, and Development Teams for Quality Planning

We can plan for quality. Dr. Joseph Juran showed many companies how to do this. The Juran Trilogy helps management plan for quality, and it can also be used by testers and development teams to do the same.

Joseph Juran was born in Romania and moved to the USA. He worked with Walter Shewhart at Bell Telephones and he later taught quality control at New York University. After World War Two he helped to rebuild the Japanese economy where his techniques became part of the management culture. He went on to work with many others including Steve Jobs [1]. The Emperor of Japan and the President of the USA gave Juran honors.

APIs are everywhere, and in most cases, we don’t give them much thought, even when using them multiple times a day. Whenever you log into a website using your Google or Facebook account, check the location of a new restaurant on Google Maps right from the restaurant’s website, or pay for your purchase on an eCommerce site using your PayPal account, you get to witness APIs in action.

But while APIs usually serve a single purpose and are not particularly large or complex software products, it takes a lot of testing on the developers’ side to ensure the spotless performance, complete functionality, and strong security of an API. And many organizations now prefer to automate API testing to save time and money on QA and get more consistent results. In today’s guide, we are going to talk about why and how to use API automation testing in your company.

Have you ever come across a stunning image and wished you could instantly generate a captivating text prompt that matches its style? Look no further. In this guide, we'll explore an incredible AI model called "img2prompt" which allows you to generate approximate text prompts that align with the style of any given image. Whether you're an artist, a writer, or simply looking to explore the creative possibilities of AI, this model will revolutionize the way you approach image-to-text generation.

To kick things off, let's take a closer look at the img2prompt model on AIModels.fyi and understand how we can utilize this powerful tool to bring our imaginative ideas to life.

AWS Vault is an open-source tool by 99Designs that enables developers to store AWS credentials in their machine keystore securely. After using it for a while at Jit, I decided to dig deeper into how it works and learned a lot along the way. In this article, I will summarize and simplify the information I learned to help others with their AWS Vault adoption and lower the barrier to usage.

I will start with a basic explanation of AWS access keys, the Session Token Service, and its helpful API calls. Then I will show how AWS Vault uses it to provide a secure way to access AWS resources, reducing the risk of exposing AWS credentials. In addition, I will represent a typical AWS account pattern, and again we'll see how AWS Vault works perfectly with it.

The Email Spreadsheets add-on for Google Sheets can save office workers a ton of time by automating the reporting of spreadsheet data and dashboards by email. With this add-on, you can schedule reports to be sent automatically on a recurring schedule, so you don’t have to manually email spreadsheets to colleagues anymore.

With Email Spreadsheets, you can schedule reports and it will automatically send them by email on a recurring schedule. You can email entire workbooks, specific sheets inside a workbook or even range of cells. Watch the video to get started.

And because the add-on runs on the Google Cloud, your spreadsheet reports will be delivered even while you are offline or on vacation.

Email Google Sheets Automatically

For this example, our Google Spreadsheet has two sheets - the first sheet contains a data table and the second sheet contains an image chart with a neatly formatted table. We’ll build a scheduled workflow that will email the sheets data, including charts, on the first Monday of every week.

Step 1: Select Sheets to Export

Install the Email Google Sheets addon from Google marketplace. Next, open any Google Spreadsheet in your Google Drive, go to the Extensions menu inside the sheet, choose Email Spreadsheets from the dropdown. Click Open to launch the app and click the Create Workflow button to create your first scheduled email report.

You’ll be presented with a list of sheets available in the current workbook. Select one or more sheets that you would like to send with the scheduled email. You may export sheets in PDF, Excel, CSV or a PNG image. Each sheet is attached as a separate file in the email but you can choose the “Entire Workbook” option to create a single file from all sheets in the workbook.

You may also use dynamic markers to customize the file name of the exported files. For instance, the marker {{Sheet Name}} {{Day}}-{{Month}} will append the current date and month to the exported sheet name.

Tip: If your Google Sheet table is large, you can specify the cell range in A1 notation (like A1:G14) and only the specified range would be exported.

Step 2: Custom PDF Export Settings

The Email Google Sheets addon lets you customize the PDF layout that is exported from Google Sheets. You can change the paper orientation (Portrait or Landscape), the paper size or alter the print margins to fit more content on a page. You can choose to show gridlines, notes, sheet names and page numbers in the exported file.

Step 3: Write the Email Template

Next, we create an email template that will be sent with your reports. You can specify one or email recipients in the TO, CC, or BCC fields.

You can also specify dynamic email recipients based on cell values in the spreadsheet. For instance, if the email address of the recipient is specified in cell B2 of a sheet titled “Employee Shifts”, you can put {{Employee Shifts!B2}} in the To field, and the add-on will pull the dynamic value from the cell at the time of sending the email report.

These dynamic cell values enclosed inside double curly braces can be used inside any of the email fields including subject, email body, and the sender’s name.

The email body can include dynamic cell values as well as ranges that make it easy of you to send portions of the spreadsheet without sharing the full workbook. For instance, you can write {{Employee Wages!B2:F9}} to include only the specific range (B2:F9) from the Wages sheet. Internally, the add-on converts the range to an HTML table, retaining all the display formatting with CSS, and embed it into the email.

Charts and Timelines can be embedded into the email body using a special {{ Chart }} marker - you can find these markers inside the markers dropdown of the email editor. Business can also add their own logo and signature in the email body.

Tip: Use the Test Email button to send an email with the exported files before setting up the schedule.

Step 4: Setup the Email Schedule

The Email Google Sheets add-on includes an email scheduler to help you set up recurring schedules visually.

You can schedule and send emails hourly, daily, weekly, monthly or even on a yearly recurring basis. It is also possible to exclude dates and your spreadsheet won’t be emailed on the specified dates.

That’s it. Save the workflow and it will be activated instantly. You can also schedule multiple emails from the same Google Spreadsheet by adding more workflows.

The Email Spreadsheets add-on is a powerful tool that can help you automate the reporting of spreadsheet data and dashboards by email. To learn more about the Email Spreadsheets add-on and to download it, please visit the Google Workspace Marketplace.

Email Google Sheets - How it works?

The add-on is written in Google Apps Script. It uses the Google Sheets API to convert sheets to PDF files and uses the Gmail API for sending the converted files as attachments.

Evolution

Towards the end of 2019, Azure SQL Data Warehouse was integrated as 'Dedicated SQL pools' into Synapse Analytics. Synapse brought in additional Serverless and Big Data Analytics capabilities. 

Microsoft Fabric, now in Public Preview, represents the next evolution of data platforms in the Azure cloud, unifying a bunch of PaaS services into a single SaaS platform.  Fabric is presented as an end-to-end, unified analytics platform serving engineers, data scientists, business analysts, and business users alike. The components of this new platform are of two main types: 

Navigating the journey from building machine learning (ML) models to deploying them in production can often be a rocky road. It’s an essential yet complex process where data scientists and engineers must bridge their knowledge gap. Data scientists, adept at creating models, might stumble when it comes to production deployment. On the other hand, engineers may struggle with the continuous iteration of ML models, leading to inefficient, error-prone operations.

Consider this specific scenario: you have just created an ML model for text summarization, which performs brilliantly in tests. You plan to share this model with your team to build an application on top of it. However, shipping this model poses a unique challenge: ensuring your team can use your model without fiddling with code or environment setups.

In today's digital landscape, cross-platform app development has emerged as a powerful approach to reach a wider audience and maximize success. By leveraging the right tech stack, developers can unlock unparalleled growth opportunities and achieve unprecedented success. 

With the staggering number of smartphone and tablet users worldwide, the mobile app industry is thriving like never before. People are glued to their mobile devices, checking them an average of 262 times a day, spending a whopping 88% of their mobile time on apps. This presents a golden opportunity for app developers and publishers, but success hinges on two crucial factors: getting users to download your app and ensuring they actually use it.