Across education, healthcare, banking, and more, connected device solutions have revolutionized how companies communicate. Direct communication with end users is essential across all channels including voice calls, video calls, SMS, web notifications, and social media. When done right, these consistent communication channels improve the user experience and drive revenue. Organizations are looking for modern software that provides a fully integrated solution.

Enter the Communication Platform as a Service (CPaaS), which has practical and impactful applications across every industry. In this article, you’ll learn what CPaaS is, how various platforms provide off-the-shelf CPaaS solutions, and how CPaaS is used in various sectors. You’ll also find evaluation parameters and guidance on selecting a suitable CPaaS provider to help inform your own search. Let’s get started.

What is CPaaS?

CPaaS is a cloud-based delivery model that enables businesses to improve communications channels end-to-end with seamless application integrations that do not require expertise to understand underline complexity related to real time communication.

Consumers expect great service across various communication channels such as instant messaging and chat, video calls, email, social media, and SMS notifications. CPaaS facilitates these communication capabilities with minimal spending on deployment and maintenance. CPaaS provides APIs (Application Programming Interfaces), SDKs (Software Development Kits), libraries, and unique components which help developers build and embed communication strategies in existing solutions. 

Recommended reading: Cloud-Driven Innovations: What Comes Next?

CPaaS offers small to medium companies an affordable option to add communication streams and digitally transform their products. In addition, CPaaS provides unique solutions and use cases to deliver services. 

CPaaS vs UCaaS: What’s the Difference?

Like CPaaS, UCaaS (Unified Communications as a Service) facilitates communication between employees and their customers, enhancing communication without owning and maintaining the infrastructure. And like CPaaS, it also provides communication tools through the cloud, enabling teams to use standard messaging, video, and phone capabilities.

But while CPaaS provides unique API, SDK, and libraries for integrated and customized application solutions, UCaaS offers unique integration capabilities with CRM tools such as SalesForce. There used to be a difference between UCaaS and CPaaS due to their customization and API support options, but the lines are beginning to blur as many UCaaS providers have started providing APIs for customization. 

Here are a few key differences between CPaaS and UCaaS:


Requires integration using API/SDK  Ready to go without any developer intervention
Focused on customization of solutions Focused on communication (employee-employee or employee-customer)
Can be initiated by application Majorly initiated by user
Pay-as-you-go pricing model Per-seat pricing model


Emerging Use Cases for CPaaS


During times of peak COVID infection, healthcare systems were put to the test like never before. Many healthcare providers were forced to begin building or enhancing their existing applications and solutions. One innovation was providing secure telehealth video calls for remote assistance and patient consultation, for example. Additionally, hospitals opted for CPaaS platforms to build messaging and voice solutions for communication between hospital staff.


Online education has gained mass adoption in recent years and is now largely powered by CPaaS solutions that provide video calling and presentation. Education platforms can enhance learning services by adding interactive solutions like digital blackboards.

Banking, Financial Services & Insurance (BFSI)

Over the last decade, BFSI companies and organizations have increasingly digitized to keep pace with evolving customer expectations and security, privacy, and operational challenges. By using CPaaS, banks can enhance their applications. For example, many banks provide a dedicated relationship manager or customer service provider to customers through online chat or phone through their banking applications. Similarly, insurance companies now often use video calls to meet with customers.

Recommended reading: Cloud – A Great Refactor for the Financial Services Industry

Tips for Choosing a CPaaS Solution

There can be business and technological implications in your choice of CPaaS. The following are the major considerations to consider while evaluating your options and selecting a CPaaS provider.

Feature Coverage

The CPaaS solutions space is crowded, with some covering every aspect and others providing niche functionalities. Choosing the correct solution is important as it impacts the short-term vision of early market release and the long-term vision of future product expansion and maintenance.


One of the major differences between UCaaS and CPaaS is the customization options of APIs and SDKs. Ideally, you’re looking for a comprehensive solution for both API and SDK. For example, if the platform claims to provide a notification service using API for Android devices but lacks notification capabilities for iOS and web browsers, it’s not a comprehensive solution. In addition, there should be coverage for development platforms and languages for SDK, such as iOS, Java, JavaScript, and C#.

Community Support

Platform providers should have the infrastructure to support end-to-end environments for application development. However, even when providers have these aspects, developers may face challenges. Resolving these issues alone by trial and error can be time-consuming and resource-intensive.  Active community helps to have access to support and a community of expertise to help resolve issues.

Security and Compliance

Security and compliance are essential not only in regulated industries such as healthcare or BFSI but in general, given the inherent vulnerabilities of customer-facing communications and data. Look for security policies and a history of updates that safeguard usage and personal data.


Consider licensing costs and the support and usage structure of each CPaaS candidate. In general, CPaaS providers claim to follow a pricing model per interaction rather than per set basis. Once an application is launched there is no turning back, which is why it’s important to consider the CPaaS platform cost thoroughly from the beginning.

Prominent CPaaS Providers Compared

Based on the latest Gartner CPaaS Review and Ratings report, there are three CPaaS providers with top ratings: Twilio, Message Bird, and Bandwidth.

CPaaS Features Comparison (as of Dec 2022)

Features Twilio Message Bird Bandwidth
SIP Trunking Yes Yes Yes
SMS Yes Yes Yes
Bulk SMS Yes Yes Yes
Email Yes Yes No
Bulk Email Yes No No
Chat Yes Yes Yes
Notification Yes Yes Yes, Limited
Audio Call Yes Yes Yes
Video Call Yes Yes No
PSTN calling Yes Yes Yes
Conferencing Yes No Yes
Voice Recording Yes No Yes
Video recording Yes Yes No
Screen Sharing Yes , limited No No
Social Media Whatsapp API Whatsapp API, also with other social media available No


CPaaS Parameters Comparison (as of Dec 2022)


Parameters Twilio Message Bird Bandwidth
API/SDK Coverage Good support for both Server as well as client SDK

Good support for Server SDK, No client SDK

Good support for both Server as well as client SDK.

Community and Support Support and Active Twilio community


Support and Less Active developer community

Security and compliances Certified ISO/IEC 27001

Major Compliance : HIPAA, GDPR

Certified ISO/IEC 27001:2013

Major Compliance : GDPR

Certified ISO 27001:2013

Pricing Pay as you go Plans, no cost for support

Monthly as well as Pay as you go plans. Additional support plans

Pay as you go Plans, no cost for support


Each application has a similar goal: to provide users with the best information or communication features inside a seamless experience. With a consistent need for application digitalization, CPaaS will continue to play an important role in improving customer communications in a wide spectrum of industries. 

With the rise of AI in the last few years throughout every domain, application-initiated communication is more prominent. We should expect to see CPaaS remain a significant partner in delivering quality communication options to end users for years to come.

Looking to modernize and personalize your company’s contact center? We help clients craft proactive, predictive customer experiences across channels and adapt quickly to your customers’ needs. Explore GlobalLogic’s data-driven customer experience services here.

More helpful resources:

Every project has its challenges and triumphs. In this particular example, GlobalLogic partnered with a multinational manufacturer and provider of animal care services to find an alternative to an existing application. Its limitations in client system deployment and application scalability for users and hospitals called for a robust, cloud-based Point-of-Care technology solution.

In this post, you can see how we tackled this complex project and overcame critical engagement challenges. We’ll share the lessons learned in QA; for example, how the customer QA manager worked dynamic insights into the daily project objectives. You’ll also discover how each release and iteration drove improvements.

A few data points of note for this project:

  • Line of Codes- 9,67,883 (FE) + 49,494 (BE) = 10,17,377 LoC 
  • Project Members- 274
  • Headcount of QA Members – 64
  • Independent Scrum Teams – 16 
  • Delivered Application Modules or Features – 248 
  • Delivered User Stories, Enabler & Change Requests – 3,931 
  • Valid Defects raised till Release 1 – 16,805

Our Technology Stack

# Area Tools, Languages, Libraries
1 Backend Development C#.NET Core 3.1
2 Front End Development Angular, Angular Workspace , NextJs, Puppeteer, Microsoft, Angular Material, Syncfusion, Jest, SonarCube, TypeScript, HTML, SCSS, node js
3 Database Cosmos DB, Managed SQL Instance (Cloud DB, Search Index)
4 DevOps & Infra Azure Cloud, Azure DevOps (Planning, Pipelines & Artifacts), Event Hub, App Config, Function App, App Insights, Azure Key Vault, Signal R, Statsig, Redis Cache Docker, Cloud Flare (CDN), Palo Alto(Networks), Azure Kubernetes (For Orchestrating Containers)
5 Requirement Management Microsoft AzureDevOps – Epic, Feature, User Story, Enabler, Change Request, Observation
6 Defect & Test Management Microsoft AzureDevOps – Test Plans & Defects
7 Test Automation, Security & Performance Protractor, JavaScript, Axios, Jasmine, Azure keyvault, npm Lib, ReportPortal, log4js, Page Object Model, VeraCode, JMeter, Blazemeter

Discovery, Proposal & Kickoff

June 2019 marked the beginning of our discovery phase. We first learned that an animal hospital brand that had been acquired by our client required a system to replace its outdated one that could hold 1000+ hospitals and 1000+ staff for each of the hospitals. By contrast, the existing application could only support 40 hospitals. 

The client sought a robust, scalable cloud-based web application equipped with the latest features for the pet care industry. It also needed the newest technology stack to replace the existing desktop application. 

After taking time to understand the business requirements, we sent a request to gauge the existing team’s capability to deliver Point of Care technology.

The Proposal

In October, five team members were hand-picked to deliver a proof of concept (POC) application. The main expectation for the application was to make it front-end heavy with cloud support. The team completed the POC application in December 2019. 

The client was satisfied with the POC application since the design met user interface (UI) expectations. 

The customized agile model was so well-designed to meet customers’ needs that the team won an award for their work in December 2019.

Recommended reading: POC vs MVP: What’s The Difference? Which One To Choose?

The Kickoff

When beginning a project, it’s crucial to establish a team with diverse expertise. As it can be challenging to hire technical experts, we implemented a hiring plan to thoroughly vet applicants which enabled us to quickly establish the required Scrum teams to begin the project.

In January 2020, the teams met in the India office to discuss GlobalLogic’s standards and practices, meet new team members, and review the POC project schedule.

Project Increments

PI0 – Planning & Estimation

Initially, we only had visual designs to help depict the customer’s expectations. Creating a list of initial requirements was challenging. 

After several technical brainstorming sessions, the teams could decipher the visual designs and were able to create a plan for the project. This included an estimate of the resources and work hours needed to complete it, as well as formulating test strategies. 

Recommended reading: 6 Key Advantages of Quarterly Agile Planning [Blog]

PI1 – Execution

Once the project was approved, we refined the requirements, evaluated potential gaps in knowledge, and formulated user stories.

PI1 began with domains such as [User And Staff], [Schedule And Appointment], and [Client And Patient Management]. After a few iterations, we added Admin Domains.

To create the graphical user interface (GUI) and application programming interface (API) automation, we established test automation for the POC and created a framework structure.

PI2 – Continuation

The development and testing of the POC application were on schedule. However, several problems arose with the [Ontology] domain without a frontend and exclusively data-driven (BE). 

To fix this, quality assurance (QA) began making stacks of defects and flooded the system.

With the completion of API and GUI automation, development started to reduce the regression effort in future test cycles. We also set up a User Acceptance Testing (UAT) environment and a QA environment for testing and assessing user stories.

Recommended reading: Zero-Touch Test Automation Enabling Continuous Testing

PI3 – The First Cut

As corner cases increased, more defects and heavy regressions were launched to bombard the application. We completed multiple test cycles and fixed the defects. 

Then, architects started their code standardization processes and helped to fix defects. After many evaluation cycles, we were ready to deliver the project to the customer.

PI4 – Project Scales

Given the customer’s satisfaction with the application, our team was asked to take on additional needs, including plans for the Electronic Medical Records (EMR) domain. There was also a new tower three and a team to create the EMR domain at a new location.

At tower two (Bangalore), there were two domains, the [Orders] and [Code Catalog]. The team quickly discovered that both domains had technical challenges. 

In tower one, there was also a new domain, the [Visit], which was an Azure Event-based domain with more problem statements.

QA Reforms & Process Enrichment

One challenge the customer QA manager encountered was the need to get dynamic insights into the daily project objectives. The solution to this came from the ADO dashboard since it could present dynamic queries making it easier to track progress in the project.

The team then identified, discussed, and documented the Test Automation Framework for the POC, intending to incorporate automation to reduce the time and effort for the testing cycle. With consistent focus, time, and effort, the team was able to implement automation successfully. Another focus for the team was to create 100% API Automation and 65% GUI Automation. 

The team also worked on identifying tools for Non-Functional Testing, such as Security Testing, Performance Testing, Resolution Testing, Cross Browser Testing, Globalization Testing, Keyboard Testing, and Scalability Testing. Not for resale (NFR) testing was a primary deliverable. 

The various process was laid down formally and revised as:

  • User Story Life Cycle 
  • ADO Defects Life Cycle 
  • ADO Tasks Creation & time logging 
  • Test Cases Design Guidelines 
  • Dev Environment Testing by QA

Tracking of QA work and regression testing became effective. Scrum & SoS trackers were upgraded with several ways to track the project better.

Releases & Iterations

Release Part 1 (First 10 Iterations)

The project delivery model changed after the PI model was released, and we started working on a new feature-based approach. This created a solid foundation for Release 1.

We took many steps to make the project transparent, manageable, and well-documented. We also tracked the solution design, HLD, and LLD for each feature. For TechDebt activities, we implemented code sanitization iterations. Then, the integration of User Stories began to capture the regression efforts, and the end-to-end feature testing began after each feature.

After implementing CI/CD, we began hourly deployments for the QA1 environment. We ran sanity test runs in pipelines and began building promotions controls. We then selected the QA2 environment for manual testing, and the certification of the User Stories for Scrum teams began.

Release Part 2 (Second 10 Iterations)

We conducted workshops with customers to estimate new domains and kicked off groomings for newly added domains in Release1, namely [Pharmacy],[Communication], [Document Template].

Release Part 3 (Last 10 Iterations)

After the domains were stabilized, we conducted a regular bug bash and completed the final features for a few older domains. A few domains went into maintenance mode, while others had more features to deliver.

QA Challenges

We encountered many challenges throughout this project’s journey and would like to share a few, along with the steps taken to overcome them.

A. Increasing Functionality & Features – Automation 

Due to significant efforts and iterations in regression testing, there were increasing functionality and test cases in the system. 

Solution: Several initiatives to gear up API & GUI Automation

  1. Framework Enhancements in libs and functions 
  2. Redesigning several aspects 
  3. Code sanitization and standardization 
  4. Prioritizing automation test cases
  5. Smart Automation by clustering the functional flows

B. Continuous Implementation & Deployments

Numerous scrub teams involved in the implementation and deployment process introduced several constraints.

Solution: Several steps were taken to improve the customer experience: 

  1. Automated Build Deployments
  2. Hourly Deployment from Master Branch to Q1. 
  3. Sanity Test Execution is Pipeline on QA1 Env. 
  4. Every 4 Hours Code Promotion to QA2 Env. 
  5. Regression Test Execution in Pipeline on QA2 Env.

Recommended reading: Experience Sequencing: Why We Analyze CX like DNA

C. Testing Layers

Various QA testing stages in multiple environments – including Dev, QA1, QA2, UAT, Stag, Train1, and Train2 – added to this project’s complexity.

Solution: A lengthy work item cycle with different states tracked the defects from new state to closed.

D. Reports & Statistics

We generated reports, statistics, and a representation of Work Items, as Ado is not a great defect management tool and people are less familiar with it. 

Solution: We worked in multiple directions by breaking and solving one by one.

  1. Extensive usage of tags. 
    1. While defect logging for environment identification. 
    2. For retesting of a defect in different environments. 
    3. Categorizing User Stories, Enablers, Change Requests, and Defects using tags for release notes.
    4. Categorization of blocker defects. 
  2. Extensive usage of Queries 
    1. Tracking defects raised by various teams for different features. 
    2. Tracking defects fixed and ready for QA. 
    3. Assignment for testing of defects on multiple environments. 
    4. Scrum Of Scrum – Defect Dashboards. 
    5. Preparing Release Notes. 
    6. Data submission for Metrics.

E. Finding Defects

It was crucial to locate any other defects to ship quality products. 

Solution: We created specialized defect hunters to identify defects. We saw significant results in different domains with this approach. 

F. Defect Hunters 

Quality requires discipline, environment, and a culture of quality product shipping

Solution: We identified and groomed specialized defect hunters with encouragement and support for bombarding defects. In a few domains, this was carried out as a practice, and achieved fantastic results despite consumer Domains.

G. Flexibility

The team often worked around 15 hours daily to meet the client’s deliverables. 

Solution: Many managerial and individual initiatives were taken to achieve the milestones.

  1. Teams showcased commitment.
  2. The teams conducted numerous brainstorming sessions to be able to diagnose and solve problems.
  3. Extensive usage of chat tools. 
  4. Limited emails.
  5. Thorough communication. 
  6. A proactive approach and agility.

H. Conflict Management – Dev vs. QA conflicts

It’s often said that “developers and testers are like oil and water,” and indeed, there was friction when the teams collaborated. 

Solution: With patience, mentoring, and guidance from leadership, they were able to work together cohesively. We implemented a QA bidimensional for major problems where each QA team member worked closely with Scrum teams.

Lessons Learned from Challenges and Bottlenecks

A. Requirement Dependency Management

Given the project’s magnitude and the multiple scrum teams involved, there were still areas where improvements could be made in the future. 

  1. There was less coordination among domain POs for required dependencies, causing problems for consumer domains, as producer domains make delays and insert defects at each level in the project life cycle

Solution: By having onshore & offshore domain POs, you could enforce better communication practices.

  1. Defects are not logged by developers in code but are due to the integration with various other functionalities and domains.

Solution: Due to a lack of formal Product Requirement Documentation, POs and developers deviate or miss the defects at the integration point. Teams can reduce risk by adding national Reviews of User Stories ACs. 

  1. Due to frequent requirement changes and gaps in communication, we encountered delays and defects. The project had cohesive functionality and features with a high degree of interdependence. 

Solution: The customer cannot isolate functionalities due to the tight coupling of the features for an end-user. Daily defect triage was conducted with POs to reduce the gaps and conclude requirements. However, we were still unable to control the delays.

B. Locking Master

By locking master while the sprint ends regressions, we lost time for other work items or next sprint deliverables. 

Solution: For a few sprints, master was not locked and control code promotion by QA Code approvals for each of the work items. This solved the problem somewhat, but only temporarily. Further developer discipline enhanced it and resulted in a regular cadence.

C. Sanity Failures at QA1 

Domains must wait until the other domain sanity failures at QA1 are resolved. 

Solution: We assigned other productive tasks to the team during this time.

D. Unplanned Medical Leaves

Unplanned medical leave due to COVID and medical emergencies.

Solution: With COVID restrictions, more teams could work from home, which helped to balance any progress lost due to unplanned medical leave. 

Recommended reading: 3 Tips for Leading Projects Remotely with Flexible Structure

E. Adhoc Work 

High level of Adhoc work and activities assigned, which were not planned and enforced to achieve. 

Solution: At a later stage in the project, its solution and Tech Debt is being taken care of along with regular development. Due to this reduction in Adhoc work and more planned work allocated.

F. Multiple Environments

Having multiple environments for testing for QA presented challenges for producing high-quality products. 

Solution: Scope of testing per environment decided like on Development Environment only positive scenarios to be checked. On QA2, in-depth certification was to be done over the build. On UAT, only defect verification is to be ensured. By this approach, a significant amount of work was reduced, but it came late.

Project Highlights 

Some of the highlights from the project include: 

  1. Having Automation QA focus on scripting and Manual QA focus on defect hunting. 
  2. Not pushing the dev team to participate in functional testing.
  3. Cross-domain cohesiveness in the QA track to understand the overall product requirements for shipping.

We met display requirements, and developers’ input helped improve the overall application. QA also provided various suggestions and observations, which helped to enrich the user experience. With guidance from the project’s architects, we created stability through complex engagement.

The problem must be taken as a challenge to solve. For example, in Agile, an Epic is broken into User Stories which are broken down into simple, achievable user stories and at the end each of the acceptance criteria is agitated to achieve the goals. 

As you can see, the team was effective in our mission and learned valuable skills along the way. If you’re presented with a complex problem, as we were, it helps to plan out the processes step-by-step. The more the problem is broken down, the more realistic its potential solutions become. 

More helpful resources:

We have entered a new era of how television content is created, delivered, and even defined. The digitalization of papers, the evolution of streaming media, an explosion of mass content creation, and on-demand access to various content are among the factors driving this transformation. 

What’s next in the future of television? 

And for businesses in media and entertainment, a more pressing question looms: will this evolution drive growth, or will the television market become stagnant?

The TV landscape has changed dramatically over the last decade. From DVRs to streaming services, the way we watch TV has significantly changed. As new technologies emerge, they often disrupt existing industries. We can see this demonstrated in the rise of streaming services such as Netflix, Hulu, Amazon Prime Video, and HBO Max, which meant that consumers no longer needed cable to watch their favorite shows. 

This shift has led to increased competition between companies that produce original programming. As a result, networks are looking to adapt to meet viewer demands. Let’s examine how television has evolved over time and what companies need to focus on next to meet consumer demands.

Television’s Past

In 1926, Japan developed the first working example of a fully electronic television receiver, a system that employed a cathode ray tube (CRT) display with just 40-line resolution scan lines. Now, try to compare this 40-line resolution to 4320 pixels (separate dots) of vertical resolution (forming the total image dimensions of 7680×4320). This will give you a rough but vivid comparison between the first TV and the current highest “ultra-high definition” television (UHDTV) resolution used in digital television and digital cinematography (8K UHD).

Kenjiro Takayanagi transmitted the picture of a Japanese katakana character comprised of 40 scan lines.

Kenjiro Takayanagi transmitted the picture of a Japanese katakana character comprised of 40 scan lines.

A lack of respective available content is why UHD TVs are mostly just interesting tech rather than everyday devices in our living rooms. But with Netflix, Amazon, Hulu, and many other services now offering 4K streaming – and Comcast,  Verizon, and Virgin all ramping up 4K sports and movies for their platforms – that excuse is firmly vanishing.

Still, let’s be honest. We’re reaching a point when it’s hard or even impossible for the human eye to see the difference in resolutions, which is why manufacturers will shift their focus toward image quality (e.g., color scheme and black levels). For example, I am using the HDR feature on my phone to edit pictures. It’s a method of obtaining more significant variance in contrast and color. This high dynamic range technology is becoming essential for modern TVs.

Television’s Present

Recent studies show that more people across age groups are moving away from traditional cable TV. On average, families can save money by selecting a couple of popular streaming services over standard cable, and they don’t have to deal with contracts and enjoy ad-free viewing. It’s no wonder people are moving away from cable TV.

The media industry is progressing and transforming significantly. The growing number of “cord cutters” and emerging group of “cord nevers” just confirms this trend.

The future of television is unlikely to result in a shift back to cable TV, as video streaming technology and content improves.

The latest trends also show that TV is slowly but steadily merging with social media. I’m not talking about Facebook pages for TV channels or comments on live shows, but social channels partnering with major media industry incumbents to host video content on their platforms. We see more news streams on Twitter, Facebook, and other platforms, and Facebook even invests and pays for creating unique live video content. At the same time, Google is launching a streaming bundle of channels under the YouTube umbrella.

These blurred boundaries aren’t just on social media. While the traditional media industry still seems to be robust, the disruption created by new online digital video services is massive. Cable networks, telecom operators, and traditional content producers are all trying to rethink their current business models and find solutions to capitalize on modern technology and retain a large user base. 

Even though traditional media industry players provide slightly different ways of consuming entertainment from newer online video services, at the end of the day, all of them are competing for viewers and utilizing the same revenue models (e.g., advertising or subscription).

The widespread deployment of broadband internet access, combined with many connected devices (e.g., tablets, phones, STBs) and their respective software solutions, have given viewers access to high-quality video content anytime and anywhere. This effectively made distribution almost free to the end user. 

According to Statista, US viewers spent an average of 8 hours and 5 minutes on digital media each day in 2021. The impact of digital media is further impacting how users spend their days each year.

There’s no need to stick to broadcaster scheduling anymore. Even many traditional broadcasters and providers are distributing their content through OTT software video platforms. Of course, each company differs in its approach to mitigating the current market situation. Some offer smaller channel bundles delivered via their online streaming services, while others try to integrate content production with distribution.

Recommended reading: Best Practices for Managing Video Streaming Platforms

Television’s Future

In light of all these new trends and changes, where should media companies focus their attention for innovation and R&D?

1. User Experience

The first and most important aspect is user experience. Users usually don’t care about different delivery and consumption technologies. They just look for the best content with an intuitive platform and high-quality resolution.

Many of my friends get frustrated because of all the different devices and remote controls in their living rooms (e.g., STB, Smart TV, Xbox, and Google Chromecast). Similar feelings arise when you jump between dozens of different apps to get your desired content. 

Ideally, there should be a universal search to manage the flood of content and for situations when you know exactly what you want to watch. Users should also be able to channel surf when they want to relax and explore — like the traditional TV experience.

A successful company or service will always put the customer first, but it’s also important to go beyond just a momentary user experience. Companies must work on long-term product strategies (i.e., employing new technology and business models) rather than simply working on current products and trying to get the most out of existing revenue models. This will allow them to better personalize their offerings, deliver differentiated value, and ultimately gain new users and retain existing customers.

2. Data

The second important aspect to focus on is data in content distribution and advertisement. Businesses shouldn’t underestimate user data. Relevant content distribution and targeted advertisement are based on user data and machine learning capabilities. 

Companies that utilize this wisely can provide a better user experience and boost their business, thus gaining a tremendous competitive advantage in the market. I think big data and analytics offer a good opportunity for OTT providers. Growing a user base from both “cord cutters” and “cord nevers” will lead to increased customer data, which can positively impact revenue through improved analytics and targeting.

3. Content

The final important element is content. It has always been and will remain a key part of the media industry. TV services that provide as much original content as possible will succeed (although this does not always imply producing their own movies). 

I should note that there is a high probability that the role of super aggregators will be occupied not by industry-relevant TV and video services providers but by companies like Google or Facebook. One interesting peculiarity that can contribute here is the growing amount of amateur content. Many children and young adults subscribe to at least one amateur YouTube channel, Instagram creator, or vlog. Even though most creators make this content on their smartphones or GoPro cameras, it’s still attracting millions of viewers.

Top social media and video content creators are creating content right on their smartphones, a trend that will have implications for the future of television.

On the other hand, content is something that can impede the media industry’s progress. Even when all necessary technology solutions are in place, media companies can struggle with commercial deals to get content into their systems. Rights-holders often restrict various aspects of content delivery to a particular channel or service, country, or date interval. This significantly affects the user experience, forcing us to jump from app to app, although I think such restrictions are part of an old-school approach to media and won’t change anytime soon.

Recommended reading: Digital Rights Management in the OTT Ecosystem

The Future of Television is Still Bright 

In this environment where digital technologies are rapidly changing the media landscape, it is crucial to understand how consumers’ behavior is trending in order to develop effective strategies for reaching them.

Our goal is to provide insights into what drives consumer decisions and behaviors and how they interact with each other and help provide solutions to meet consumer demands. We help media and entertainment companies including OTT brands, broadcasters, studios, and ad tech providers design and develop innovative, next-gen solutions and platforms that captivate audiences and generate revenue. Check out our Media Software Development Solutions & Services to learn more.

Keep Reading:

Since the AI-driven chatbot “ChatGPT” was introduced to the public in November 2022, it has been a hot topic for discussion. The ability of AI-based technology to perform characteristically ‘human’ tasks such as telling stories, writing code, authoring poetry, telling jokes and composing essays on virtually any topic has shocked and astonished many. 

These activities are among those that we think of as particularly human. If a software package can do these very human tasks, what does it mean to be human?

I’m pretty sure that humanity has asked a variant of this question every time a new technology has appeared. Probably the invention of the wheel was greeted with dismay by some because lifting and carrying items—or transporting those items on a horse or donkey—was thought of at the time as a human or animal task. Not something to be done by an inanimate object such as this new ‘wheel’ gadget.

Does ChatGPT spell the end of human creativity?

The AI-driven chatbot invention strikes particularly close to home for me, however, because what I’ve conventionally seen myself as being good at is making associations between concepts that might seem very different. This can be a simple association like answering a question for my colleagues like, “Where has GlobalLogic done something similar to this project before?” My experience, memory, and ability to make associations have served me well in helping me answer this type of question. 

Such questions are a bit harder to answer and require more creativity than might appear at first glance because GlobalLogic has hundreds of clients and does literally thousands of projects per year. Also, associations can happen across many dimensions—similar technology, similar business problem, similar situation, and so on. GlobalLogic of course does have search and other electronic means of answering most such questions. Nonetheless, for the hard or critical ones—those requiring ‘lateral’ thinking–I’ve been a good resource and am frequently called on to answer this type of question.

Recommended reading: The AI-Powered Project Manager

Likewise, I enjoy writing: essays, stories, and even the occasional bit of poetry. I think writing is good when people can relate to the author’s experiences or narrative, and when it makes sometimes unexpected associations that people might find interesting, funny, or engaging. When I write, I know that I certainly aspire to do this. What is surprising and a bit disconcerting, to me and I think to others, is that the AI-driven ChatGPT does a pretty good job at both! I’ve seen ChatGPT make some fairly surprising—but valid—associations, and it can even describe situations in a way that is emotionally moving. Its grammar is also fluid, and readable.

Relatable story-telling and surprising associations were generally thought of as uniquely human activities requiring creativity. The fact that a mechanical process can do both, and do them fairly well—even in its relative infancy—is disconcerting to many of us. 

Advances in AI are helping us redefine what it means to be human.

However, much of creativity—human or otherwise—has always been about forging associations between items previously thought to be different. For example, between green-colored rocks and copper; between “my love” and “a summer’s day”; between space and time. Indeed, it would be more surprising if a software process that can read, process, and classify all of the literature; all of the scientific knowledge; and literally everything written, did NOT make some surprising connections. The programming challenge would be more around pruning the possible associations for relevancy, rather than generating the possible associations in the first place.

In prehistory, the inventions of storytelling and drawing, and many thousands of years later, of writing, were considered milestones in the human journey. All of these enabled one person to leverage the experiences gained by others, expanding what a single person could know and do. 

The introduction of the printing press 500 years ago multiplied this capability by making the writings, drawings, and stories of others available to a wider audience. More recently—arguably starting in the 1990s—the large-scale digitization of printed content, along with the generation of digital-native content such as blogs and websites, eliminated the need for the physical production of printed media before information could be consumed. This had the effect of drastically lowering the cost of distribution and making more content available to a wider audience than had ever before been possible.

Many of us did not appreciate the full implications at the time: digitized content is also machine-readable. Therefore, not only people but also software can use it to ‘learn’. We knew this in a limited sense, with powerful search engines and knowledge digests such as those provided by Google, Microsoft, and others being part of our lives for decades. However, a general-purpose, interactive AI that itself digests and synthesizes this information in ‘creative’ ways is new to many of us and has become a fact we must all come to terms with.

Recommended reading: Cloud-Driven Innovations: What Comes Next?

Throughout the history of technology, many inventions and discoveries have forced people to rethink and redefine who they are, and what it means to be ‘human.’ One such instance was the Copernican revolution in the 1500s, where it became widely accepted that the Earth goes around the Sun rather than vice-versa. This required a major shift in humanity’s thinking about our central role—or lack thereof—in the universe. But many smaller inventions and discoveries have had deep consequences on our individual identities when our identity has become tied up with a particular capability.

One example from American Folklore is told in “The Ballad of John Henry.” 

John Henry is a man who works building the railroads of pre-Civil War America (before 1861), manually using a hammer to pound in the nails that held the tracks. His pride is his speed and physical strength. When the technical innovation of the steam drill is introduced, John Henry is defiant and refuses to admit that this new mechanical device could perform his job as well as he could. He says to his boss (the “captain”), who has introduced this new machine:

John Henry said to his captain, 

“A man is nothing but a man, 

But before I let your steam drill beat me down, 

I’d die with a hammer in my hand, Lord, Lord,

I’d die with a hammer in my hand.”

In the ballad, in a contest between man and machine, John Henry does indeed outperform the first version of the steam drill. However, he works so hard to do so, he dies from a heart attack in the process. And we can only suppose that future versions of the steam drill would outperform any human’s best efforts.

We’re being challenged now by the “creative” AI.

John Henry clearly identified with his physical strength and speed—to him, that was what he was good at, and what had become his identity. He believed his physical strength and speed made him worthwhile, both as a person, and—rightly or wrongly—also as an employee. 

With this emerging technology, those of us in the professions as well as all “creative” types: doctors, lawyers, poets, writers, artists, researchers, inventors, engineers–and yes, CTOs–now also face a new form of ‘competition’ for what we believe we have to offer the world, and for what we do best. This might be seen as poetic justice or karma since the previous innovations with the potential to change how we see our value–including this one–originated from this very group.

Those of us who identify with our creativity are now challenged by a new technology: what we might call the “creative AI.” Like John Henry’s situation, it’s clear that a machine—an AI—can now start to do things we thought of as uniquely human and, to some extent, uniquely “us.” It’s clear that—like the steam drill–even if creations generated by this new technology are somewhat primitive today, they will become increasingly better over time. 

We can either face this fact, even if it means re-assessing what it is that truly makes us ‘human’ and valuable to others, or we can fight it and deny that machines have any role to play in the creative/generative process. The latter course, I fear, will result in an outcome along the lines of John Henry’s contest with the steam drill.

As creative people, we can let the fact that there are now creative machines (AIs) detract from our feelings of self-worth, and make us fear for our future and our jobs. On the other hand, we can accept these AIs as a fact, and embrace the possibility that human creativity coupled with AI creativity might produce results that are truly awesome. If John Henry had leveraged his skills and experience and learned to co-exist with or even to operate that steam drill, we would have missed out on a great American folk ballad. However, I think that John Henry—and his employer and humanity—would have been better off.

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The importance of usability cannot be overstated. Users expect websites and apps to be usable and intuitive. If they encounter difficulties using them, they’ll likely abandon their attempts to complete a task.

To help solve this, World Usability Day takes place annually to raise awareness about usability issues in software design. The goal of this event is to encourage developers and designers to think about how users interact with websites and applications. This can include making sure buttons are big enough for easy clicking, using color contrast to help users read text, and avoiding distracting animations.

In this post, we’ll dig into usability a bit deeper and explore why it matters to consumers and the companies who design, develop, and maintain products for them.

What is Usability?

Usability is the degree to which a system or product can be quickly learned and operated by specified user groups under stated conditions. The goal is to create intuitive, efficient, effective, and valuable systems.

There are five quality components to usability, according to this definition from the Nielsen Norman Group: 

  • Learnability: How easy is it for users to accomplish basic tasks the first time they encounter the design?
  • Efficiency: Once users learn the design, how quickly can they perform tasks?
  • Memorability: When users return to the design after not using it, how easily can they reestablish proficiency?
  • Errors: How many errors do users make? How severe are these errors? How easily can they recover from them?
  • Satisfaction: How pleasant is it to use the design?

We measure usability using observable and quantifiable metrics:

  • Effectiveness: The accuracy and completeness with which users achieve specified goals
  • Efficiency: The resources expended in relation to the accuracy and completeness with which users achieve goals
  • Satisfaction: The comfort and acceptability of use

Usability enables developers to create better products based on users’ objective and subjective experiences.

Recommended reading: Top 10 UX Design Principles for Creating Successful Products and Experiences – Method

Why is Usability Important?

When we meet usability standards, the product’s interface is transparent, and the cognitive load caused by the interface is low. This allows the user to focus on the task, be less error-prone, make decisions quickly, and feel more satisfied.

Usability is important to end users and the companies who develop products for them as it impacts revenue, loyalty, brand reputation, and more.


A happy user will continue using the product and be more inclined to recommend it to their peers. This will increase the user base and user loyalty, positively affecting revenue. So from a business point of view, usability is not a cost — it’s an investment.

How Can We Improve Usability?

Usability is a process. It’s involved in each stage of the development lifecycle. We recommend that you start assessing and measuring usability as early as possible. This approach enables you to discover errors sooner, making more room to iterate and test the solutions and improvements.

While there are several ways to improve usability (depending on the process stage), user testing is the most basic and valuable approach. It’s not necessarily a costly or lengthy process. It can be quick and inexpensive, suitable for any company, product, or stage. There are four simple steps to improve usability:

  1. Acquire representative users.
  2. Ask the users to perform representative tasks with the design.
  3. Observe what the users do, where they succeed, and where they have difficulties.
  4. Analyze the data and then iterate until they meet the predefined usability KPIs.

To create a valuable user experience, you must observe, interact, and focus on their needs, expectations, and skills.

Recommended reading: Is Kanzi Really Transforming UI Design?

Creating an Excellent User Experience 

At GlobalLogic, we strive to create highly usable products. With a user experience team of more than 140 experts across six countries, we can improve the usability of existing products and incorporate usability assessments and testing as part of our user-centered design approach to product development.

For example, when a major Latin American cable TV provider contacted us so we could assess the usability of its upcoming on-demand video service, the first thing we did was organize a series of user research and user testing activities. We asked current customers to test the client’s potential product to determine three main usability metrics: task success rate, user error rate, and satisfaction (using two common questionnaires, System Usability Scale and Net Promoter Score). 

The results were not ideal: high error rates, low satisfaction, and a low Net Promoter Score. We recommended that the client not release the product to market before working on and testing new solutions.

The Result

Once the client accepted our recommendation, we invited their customers to discuss how they consume media. We also visited their homes and performed onsite interviews and observations. Based on what we learned through these exercises, we developed a first round of wireframes and prototypes that the same users then tested. Through these sessions, were able to significantly improve the product’s usability KPIs.

When the client finally launched the new service, its users said they enjoyed its flexibility and ease of use. Not only did the service function efficiently, but it was intuitive and well-designed — proving that usability plays a huge role in successful products. 

Moreover, the client saved millions of dollars by developing the right product for a fast-paced market with strong competitors and newcomers.

We live in a world where technology has become ubiquitous, but many products still fail to meet users’ expectations. This is why it’s more important than ever to spend time researching how to perfect your user experience to keep up with technological advances and save time and money in the long run.

Learn more about World Usability Day here.

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According to Deloitte, there will be 470 million connected vehicles on highways worldwide by 2025. These connected vehicles provide opportunities and have a higher cybersecurity risk than any other connected devices; even the FBI had to make a statement about it. 

A typical new model car runs over 100 million lines of code and has up to 100 electrical control units (ECUs) and millions of endpoints. The stakes are high, too, considering the safety implications some of these security issues may cause. Supporting satellite, Bluetooth, telematics and other types of connectivity while protecting drivers and public safety is essential, and completely reliant on vehicle design and manufacturing.

Vehicle Cybersecurity Regulations for Manufacturers to Know

Considering this, the UNECE released new vehicle cybersecurity regulations in the middle of 2021 (UN R155 and UN R156), and ISO came up with ISO/SAE 21434. These standards laid the foundation of cybersecurity in connected vehicles. While they are complex, these security considerations can be classified in three main categories:

  1. In-vehicle cybersecurity: Cybersecurity aspects within the vehicle, such as OBD-II hacking, key fob hacking, theft of personal data, remote takeover, malware, etc. 
  2. Network cybersecurity: Cybersecurity aspects of vehicle network connectivity. This covers most general network threats such as DoS, Syn-flood, etc.
  3. Backend cybersecurity: Cybersecurity aspects of backend systems, which are typically the same as any cloud security aspects. Connected vehicles exchange information and data with the backend systems generally hosted on the cloud. These backend systems perform various tasks such as vehicle software updates, navigation, alerts, etc.

Recommended reading: How Smart Cars Will Change Cityscapes

Examples of Cybersecurity for Automotives Across Threat Categories

Each threat category requires different solutions and skills of the vehicle manufacturer. For example, these are some of the solutions required for each of the above categories. 

In-vehicle cybersecurity 

  • Hardware-based crypto-accelerators and secure key storage
  • JTAG memory and register access restriction
  • Firmware signing
  • Electronic Control Unit (ECU) authentication
  • Anti-tampering and side channel attack protections
  • SSH or secured access
  • Secure key storage

Network cybersecurity 

  • Encrypted and secure communication
  • IDS/IPS to track potential packet floods
  • Network segmentation
  • Virtual private network (VPN)
  • Firewall

Backend cybersecurity

  • Data loss prevention and data integrity strategy
  • OTA package encryption and signature
  • Secure images
  • Activity and log monitoring

Our team works with leading connected vehicle manufacturers and OEMs to build secure connected vehicles across all three categories. We help our clients with the cross-industry best practices required to develop solutions such as in-vehicle infotainment systems, ECUs, and advanced driver assistance systems without compromise on security or reliability.

Learn more: 

Smart cars are becoming more common all the time. Today, there are over 31 million cars worldwide with at least some level of automation, offering drivers a safer driving experience, improved fuel efficiency, and better parking options. 

They also improve cityscapes through their ability to communicate with other vehicles and infrastructure. In this way, smart cars are changing the way cities function – and the experiences people have within them. 

But what exactly is a smart car? And how will smart cars change our cities? 

What is a Smart Car?

Smart cars are equipped with advanced technologies such as sensors, cameras, GPS, and wireless communication devices. These features allow them to interact with each other and with road infrastructure, enabling smart cars to act as a conduit for useful information that helps drivers respond to traffic conditions.


Smart cars are improving safety, reducing congestion, and increasing mobility. As a result, these vehicles are helping to transform urban landscapes.

The rise of autonomous driving means fewer drivers will be needed to operate public transportation systems. In addition, traffic congestion will decrease significantly due to fewer traffic accidents caused by distracted drivers.

Recommended reading: Introduction to Autonomous Driving [Whitepaper]

A Smart City is One Where People Know the Value of Data

Consulting company PwC coined the term “data-driven city” to describe a smart city. The instantaneous collection, transmission, and analysis of information circulating in an urban space allow municipalities to radically change their approach to transportation management. It also impacts urban resource management (e.g., water, energy, etc.), safety improvements, environmental impacts, medicine production, and management of education and the other city services available for residents.

How is this being put into practice? New York City has a unified data collection and analysis system that feeds several effective city solutions, including a fire prediction system, garbage removal, and recycling. It also includes a health information system that collects data from citizens’ wearable devices (such as fitness trackers) and transfers it to medical institutions.

Another example is in Barcelona, where hundreds of sensors collect information on traffic, noise, electricity, and lights through an integrated system called Sentilo, which is  in the public domain. This means that city authorities can make effective management decisions, and third-party businesses can develop additional services for residents.

Technological Breakthroughs and Cities of the Future

The IEEE published research in 2017 that defines a whole range of technological trends that will influence the cities of the future, including:

Internet of Things

Smart sensors are enabling the gathering of more information from the environment. According to global forecasts, there will be 75.4 billion connected devices by 2025. IoT technology allows real-time monitoring of all city life aspects: traffic speed, outdoor security, resource consumption, etc.

Cloud Technologies

With the amount of generated data growing, there will be a need for rapid and qualitative processing. Cloud application systems will become the brain of a city, helping city managers make effective decisions (e.g., traffic regulation) based on the analysis of terabytes of data.

Recommended reading: Cloud-Driven Innovations: What Comes Next?

Open Data

By providing easier access to information, city authorities not only make communication with residents more transparent but also create the basis for new businesses, for example, developing mobile applications to monitor the environmental situation in the city.

At the same time, a smart city is a complex ecosystem that unites technological as well as human and institutional aspects. The digital transformation of cities can only happen with active involvement from municipal authorities, businesses, the local IT industry, and the citizens themselves.

Communication Between Cars in the City of the Future

The digital transformation of the automotive industry is yet another milestone in smart city development. The growing popularity of electric cars — as well as experiments with uncrewed vehicles by Tesla, Google, Mercedes, and other companies — is perhaps one of the most discussed technological topics in the media.

In the cities of the future, cars will not disappear. However, the volume of personal cars on city streets will decrease gradually as rideshare apps like Uber, car-sharing services, and autonomous vehicles for carpooling replace them. Car design will change radically, and the experience of being a passenger in an autonomous vehicle will become more comfortable. 

Unlike cars with internal combustion engines, electric cars will not pollute the city and create noise. Self-driving vehicles will save citizens from an excessive number of unsightly parking lots near the sidewalks, as there will be no need to leave cars near the office.

For several years, GlobalLogic has been developing technologies for smart cities in cooperation with automotive corporations and telecom operators. Based on our expertise, we imagine how a city might develop in 5-10 years and then experiment with related technologies. One of our predictions is that all cars will eventually be able to communicate with each other – and we already know how this will work in practice.

Communication between smart cars and smart road infrastructure will make the road a safer place to drive. In critical situations, each second matters, so the sooner drivers receive the information they need, the more likely they will avoid an accident. Communication technologies between cars will allow the driver to know about everything happening around them from a specific distance.

Recommended reading: User Experience as a Key Factor in the Automotive Industry

Incorporating Technology

So, how is this realized technologically? Cars will be able to communicate through the vehicle-to-everything (V2X) protocol, creating a powerful Wi-Fi network with instant data transfer within 1 km around themselves. 

How is this realized in practice? Using an interactive simulation environment that we developed, we tested a variety of application cases, such as:

  • The driver wants to change lanes but immediately receives an alert about a car speeding in that lane. This notification prevents drivers from making dangerous maneuvers.
  • A smart road infrastructure receives traffic data from cars and can create an alternate route for the driver. 
  • An ambulance sends a signal about driving in a certain lane. Then all drivers receive the notification to make room for the ambulance to pass. Afterward, a smart traffic light switches to green to let the ambulance pass safely through the intersection.
  • A car with a punctured tire can signal assistance to all passing cars. If the driver of a passing car cannot help, the car transmits the signal to the next vehicle.

Past Innovation

How fast will smart cars be able to communicate? And what will happen to cars that cannot? Let’s discuss the history of mobile phones. 

When they first appeared, it seemed expensive and rather pointless to purchase them since few people had a phone that you could call. But over time, more and more people became mobile users, and mobile phones became more affordable. Now, they are our main means of communication.

The same future is likely to follow for automotive communication technologies. 

First, city authorities will encourage residents to install the necessary equipment and software for the car. Then cars will come off the production line with already-integrated communicative capabilities. 

Future Innovation

At GlobalLogic, we’ve noticed numerous automotive trends and innovations that will change how we approach creating vehicles.

The widespread integration of Automotive Open System Architecture (AUTOSTAR), the personalization of cars through subscription models, autonomous vehicles, and augmented reality are just a few examples of the factors and trends influencing how smart cars will change our cityscapes in the years to come.

These advances will soon be able to create a fully autonomous car, helping us to create smarter cities and safer roads for drivers, too.

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Mobile apps play a crucial role in our lives, providing us access to information, entertainment, health tracking, financial services, and more. As such, they have become indispensable tools in our daily routines. Given that Android accounts for 71% of OS marketshare worldwide (as of Q4 2022), it’s a must for app developers to tailor their apps to these users.

But creating these apps isn’t always straightforward. Developers face challenges ranging from technical issues to changes in consumer behaviors to complex UI design. They are constantly seeking automation solutions to streamline their workflows, creating efficiencies that enable them to focus on the more creative and complex aspects of app development.

This blog reviews several open-source frameworks that Android app developers can use to significantly accelerate their time-to-market. Open-source frameworks do this by testing frameworks that automate crucial but repetitive tasks, including those for functional (acceptance) and regression testing.

What’s an Application Framework?

An application framework is a set of tools used to build applications for mobile devices such as smartphones and tablets. The frameworks include libraries, application programming interfaces (APIs), and software development kits (SDKs). These frameworks allow developers to focus on building apps rather than learning how to write code.

An Android app framework can provide developers with tools for building apps faster and easier. These include support for Google Play Services, allowing users to access location, maps, and other helpful information inside the application. Developers also benefit from Android Studio, which makes it easy to build, test, debug, and deploy applications.

Recommended reading: Choosing the Right Cross-Platform Framework for Mobile Development

Android Studio

The Android Studio is a tool used for developing apps and games for android devices. It allows developers to create applications using Java programming language. The main features of this application are:

  • Create, run, debug, build, package, test, deploy, and monitor your app on the device or emulator.
  • Use the debugger to step through code while it’s running in the IDE.
  • Support for multiple languages (Java, Kotlin, Swift, Objective-C).
  • A graphical layout editor that lets you design layouts for screens in XML files.
  • An integrated development environment (IDE) with support for many popular IDEs such as Eclipse, IntelliJ IDEA, NetBeans, and Xcode.
  • A library manager that helps you manage third-party libraries.
  • A project management system that helps you organize projects into folders and subfolders.
  • A file explorer that helps you navigate between different parts of an Android project.
  • A source control integration that enables you to use Git, SVN, Mercurial, Bazaar, Perforce, CVS, ClearCase, Subversion, etc.
  • A database explorer that helps you explore databases created by SQLite, MySQL, PostgreSQL, Oracle, and MS Access.

Android Instrumentation

Now let’s talk about some Android frameworks developers can utilize. Below are three frameworks that belong to the Android instrumentation testing category, as specified in the family tree of test frameworks shown above.

Android frameworks


The Robotium Android test framework offers full support for hybrid and mobile web applications, as well as native apps written using Android SDKs. It’s an instrumentation-specific open test framework maintained by the Google community. Robotium JAR is integrated with the IDE. Developers can use the test script and a programming language such as Java with Android Junit4. Learn more on Github.


Espresso is an Android test automation framework used to test a native application. Google released the activity-specific actions that can be tested using Espresso Espresso will concentrate only on the user interface testing following the unit testing point of view. 

The working mechanism behind Espresso is as follows:

  • ViewMatchers – allows developers to conduct view finding in the current view hierarchy
  • ViewActions – allows develpers to perform actions on the views (Click, swipe, etc.)
  • ViewAssertions – allows developers to assert state of a view (True or False)


Calabash, a behavior-driven development tool, is an open test framework that automates testing for Android mobile applications based on native, hybrid, and mobile web code. Its working mechanism is Cucumber Gherkin, integrated with the Calabash gem to execute the test scripts written as a feature file.

It’s an open source framework available in GitHub with source information. You can run the test script on multiple emulators or real devices connected to a single machine. Although, test steps written in simple English language can trigger certain actions in the mobile application when executed.

UI Automator

The UI Automator testing framework provides a set of APIs to build UI tests that perform interactions on user apps and system apps. The UI Automator APIs allow you to perform operations such as opening the Settings menu or the app launcher in a test device.

The UI Automator testing framework is well-suited for writing black box automated tests, where the test code does not rely on internal implementation details of the target app. It will directly interact with the UI elements associated with the mobile application, which trigger all the user actions such as entering the text in the text box, click action, swipe, drag to, multi-touch, etc.


Appium is an open-source tool for automating native, mobile web, and hybrid applications on Android platforms.

As its SourceForge description explains, Appium aims to automate any mobile app from any language and test framework, with full access to back-end APIs and databases from test code. Write tests with your favorite dev tools using all the above programming languages, and probably more (with the Selenium WebDriver API and language-specific client libraries).

Appium test scripts written in IDE will interact with the Appium Server, but the node server will interact with the specified IP address and port number. The node server then passes the request to mobile devices or emulators using the UI Automator in a JSON format. 

All the UI elements associated with the mobile application can be controlled using the Appium client, which is derived from Selenium. The diagram below shows the Appium workflow:

A diagram illustrating the open source tool Appium workflow.

Comparison Matrix

A comparison matrix is a tool for comparing different business models. The goal of a comparison matrix is to determine which model is best suited for each scenario. This allows you to choose the right business model based on your specific situation.

Below is a helpful matrix for comparing the features available with the frameworks discussed in this article:

A comparison matrix illustrating the features of various android test frameworks.

Final Takeaways

Android app automation frameworks allow developers to automate tasks within their apps without writing any code. This means you can create automated processes for repetitive tasks like sending messages, testing code, updating data, etc.

Integrating automated processes and helpful frameworks can save developers and companies valuable development time, resources, and money. 

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Microservices are a development methodology where services are independently developed and deployed. This type of architecture has become popular over recent years due to its ability to decouple systems and improve the speed of delivery. To test these applications effectively, they require specialized tools and processes.

Given the volume of independent services communicating with one another, test automation in a microservices architecture can be complex. Despite this, there are several compelling benefits to the microservices architecture, which we’ll discuss in this article.

What is a Microservice Architecture Style?

By definition, a microservice architecture style is used to develop a single application with separate processes for each mechanism. These “small services communicate by accessing each other’s exposed application programming interfaces (APIs).

A typical example is Amazon’s online shopping. As shown in the diagram below, each lightweight service runs independently from the others. Even if there’s a failure at the payment gateway, users can still add items to their shopping carts and look at other modules. Using this setup, the loss of one module does not ruin the entire system.

The benefits of this approach include the following:

  • Each component has its lifecycle. This means that it can be scaled up or down as needed.
  • It’s easy to test individual components because they don’t depend on any other system part.
  • You can use different deployment strategies, such as cloud-based hosting or self-hosted solutions.
  • You can deploy multiple software versions simultaneously without affecting the system’s overall performance.

Recommended reading: Strategies for Digital Transformation with Microservices [Whitepaper]

Why Use Microservices?

There are several reasons why organizations should adopt a microservices architecture. Some of the most common include:

Increased agility. By breaking large monolithic applications into smaller pieces, teams can quickly respond to changes and make improvements.

Improved scalability. It’s easier to scale out than to scale up. If you need more capacity, add additional servers instead of rewriting the code.

Faster time to market. You can release new features faster because you don’t have to wait for a team to complete an entire application before releasing it.

Reduced complexity. A microservices architecture reduces the number of dependencies between components. This makes testing much more straightforward.

An example of an Amazon microservices architecture.

Fig. 1:  Amazon microservice architecture

How Do Microservices Work?

When developing a microservices architecture, you break down a monolith application into small services. Each service exposes a set of APIs that allow other services to interact with it.

For example, let’s say you have a web app that allows customers to create accounts. You could build a service that handles user registration. Another service might handle authentication. And another manages customer data.

When a request comes in, the client sends it to the appropriate service. That service then performs its function and returns the results to the client.

This model works well when all the services run in the same environment. However, if you want to host these services in different environments, you must expose the API so that clients can access them.

Issues with Microservice Architectures

Even though a microservice architecture approach to software development provides countless benefits, it has some drawbacks in reporting. For example, it can be a hassle to analyze test results, identify pass/fail ratios and trends, and understand the total execution time for a particular microservice regression suite. In addition, you must ensure that the communication between services is secure.

Let’s consider the below sample microservice architecture for Netflix, where there is an ‘n’ number of services running. To maintain a stable automation pipeline, you must obtain data that answers the following questions:

  • Which services have a maximum execution time?
  • Which services have more failures?
  • What are the trends in service execution times? Are they up or down?
  • I have the name of services with a maximum number of failures, but how do I drill down and check based on the scenario?
  • Can I see a list of scenarios failing for quite a long time, and if the age of failing is high?
  • Can I get all the details of the service that has the latest build installed?

An example of microservice architecture using Netflix in the illustration.

Fig. 2: Netflix microservice architecture

Effective Microservice Management

We’ve found that one way to manage the different requirements listed above successfully is to integrate all the services into a single platform. For example, we developed a custom dashboard for a client that can be used as a report generation tool and monitor more than 50 microservices (with the potential to be extended to 100+).

The main objective of this dashboard was to be a one-stop shop for all automation reporting, trends, and monitoring. To create this dashboard, we used the following technologies:

  • Spring Boot
  • Spring Thymeleaf
  • Maven
  • Java 1.8
  • Couchbase DB(Can be any DB)
  • Jenkins client api
  • D3.js

The dashboard was so successful that we now implement it in other projects. Below are the different reports we created to improve our automation health.

Overall Microservices Tab

This tab will answer most of the below data queries, including the historic (previous build) data.

  • Build data for all the microservices.
  • Duration of that microservice suite.
  • Total test case count, fail test case count, etc.

In this definition of microservices article, you find an example of a microservices tab in the reporting used for effective management.

Fig. 3: Overall Microservices Tab

Recommended reading: Time Series – Data Analysis & Forecasting [Whitepaper]

Execution Time Analysis Tab

This tab is a graphical representation of the above data that displays your microservice automation health trends. We can filter down based on environment and type of run (i.e., smoke, regression, etc.).

An example of execution time analysis in microservices management reports. Fig. 4: ExecutionTime-Analysis Tab

Failure Analysis Tab

This is one of my favorite reports. It tells us two essential parameters (“age” and “failed since”) so we can easily dig down to the scenarios that are failing over a long period. This report ultimately helps us improve our smoke suite (if it’s an application issue) or the quality of the automation test case (if it’s an automation issue).

An example of a Scenario Failure-Analysis tab in a microservices management report. Fig. 5: Scenario Failure-Analysis Tab

Summary Tab

This tab is helpful for managers to obtain the latest consolidated report for all microservices of their latest runs.

Repo-Analysis Tab

Larger, distributed teams where people work in different branches can find QA challenging. For example, while they might merge their code during intermediate runs to develop an interim branch, it’s easy to forget to merge their code into the main branch. This oversight can create issues during deployments, as there are always substantial differences between these individual developers and main branches.

To resolve this issue, we developed a matrix that can tell the difference between the commits of these various branches and raise an alert when needed—an auto-scheduler triggers every hour and updates the latest data in the database.

Repo Commit-Diff is a matrix that helps you identify the difference between commits. Fig. 6: Repo Commit-Diff


There a numerous use cases for microservice to increase the efficiency of internal processes. With the right tools and the information above, companies can seamlessly integrate a microservice architecture.

At GlobalLogic, consolidating requirement variations and system reports into a single dashboard has been highly influential in managing microservices. Although the specific docker files for this dashboard are proprietary to GlobalLogic, I encourage you to use the information to create your microservice dashboard.

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