5 ways to measure and improve your QA Effectiveness; is your vendor up to the mark?

The benefits of QA testing in software are widely accepted.  However, quantifying these benefits and optimizing the performance is tricky.  The performance of software development can be measured by the difficulty and amount of code committed in a given sprint.  Measuring the effectiveness of QA is harder when its success is measured by the lack of problems in software application deployment to production.

If you can’t measure it, you can’t improve it.

The ‘right’ metrics to evaluate QA effectiveness depend on your organization. However, it is generally a good idea to measure efficiency and performance for a well-rounded guide for performance evaluations.

Test coverage

While improving test coverage ideally means creating more tests and running them more frequently, this isn’t the actual goal, per se.  It will just mean more work if the right things are not getting tested with the right kind of test. Hence the total number of tests in your test suite by itself isn’t a good metric or reflection of your test coverage. 

Instead, a good metric to consider would be to check if your testing efforts cover 100% of all critical user paths.  The focus should be on building and maintaining tests to cover the most critical user flows of your applications.  You can check your analytics platform like Google Analytics or Amplitude to prioritize your test coverage.

Test reliability

The perfect test suite would have the correct correlation between failed tests and the number of defects identified.  A failed test will always include a real bug and the tests would only pass when the software is free of these bugs. 

The reliability of your test suite can be measured by comparing your results with these standards.  How often does your test fail due to problems with the test instead of actual bugs? Does your test suite have tests that pass sometimes and fail at other times for no identifiable reason?

Keeping track of why the tests fail over time, whether due to poorly-written tests, failures in the test environment, or something else, will help you identify the areas to improve.

Time to test

The time taken to test is a crucial indicator of how quickly your QA team creates and runs tests for the new features without affecting their quality. The tools that you use are a key factor here. This is where automated testing gains importance.

Scope of automation

Automated testing is faster than manual testing.  So one of the critical factors to measure your QA effectiveness would include the scope of automation in your test cycles.  What portion of your test cycle can be profitably automated, and how will it impact the time to run a test?  How many tests can you run in parallel, and the number of features that can be tested simultaneously to save time?

Time to fix

This includes the time taken to figure out whether a test failure represents a real bug or if the problem is with the test. It also includes the time taken to fix the bug or the test.  It is ideal to track each of these metrics separately so that you know which area takes the most time.

Escaped bugs

Tracking the number of bugs found after production release is one of the best metrics for evaluating your QA program. If customers aren’t reporting bugs, it is a good indication that your QA efforts are working.  When customers report bugs, it will help you identify ways to improve your testing.

If the bug is critical enough in the first two cases, the solution is to add a test or fix the existing test so your team can rely on it.  For the third case, you may need to look at how your test is designed—and consider using a tool that more reliably catches those bugs.

Is your Vendor up to the mark?

Outsourcing QA has become the norm on account of its ability to address the scalability of testing initiatives and bring in a sharper focus on outcome-based engagements.

Periodic evaluation of your QA vendor is one of the first steps to ensuring a rewarding long-term outsourcing engagement. Here are vital factors that you need to consider. 

Communication and people enablement

Clear and effective communication is an integral component of QA, more so when DevOps, Agile, and similar collaboration-heavy initiatives are pursued to achieve QA at scale. Ensure that there is effective communication right from the beginning of the sprint so that cross-functional teams are cognizant of the expectations from each of them and have their eye firmly fixed on the end goal of application release.

Also, your vendor’s ability to flex up/down to meet additional capacity needs is a vital factor for successful engagement. An assessment of the knowledge index of their team in terms of ability to learn your business and their ability to build fungibility (cross skill / multi-skill) into the team can help you evaluate their performance. 

Process Governance 

The right QA partner will be able to create a robust process and governing mechanism to track and manage all areas of quality and release readiness, visibility across all stages of the pipeline through reporting of essential KPIs, documentation for managing version control, resource management, and capacity planning. 

Vendor effectiveness can also be measured by their ability to manage operations and demand inflow. For example, at times, toolset disparity between various stages and multiple teams driving parallel work streams creates numerous information silos leading to fragmented visibility at the product level. The right process would focus on integration aspects as well to bridge these gaps.

Testing Quality 

The intent of a  QA process is mainly to bring down the defects between builds over the course of a project. Even though the total count of defects in a project may depend on different factors, measuring the rate of decline in the defects over time can help you understand how efficiently QA teams are addressing the defects. 

The calculation can be done by plotting the number of defects for each build and measuring the slope of the resulting line. A critical exception is when a new feature is introduced. This may increase the number of defects found in the builds. These defects should steadily decrease over time until the build becomes stable

Test Automation 

Measuring the time efficiency often boils down to the duration it takes to accomplish the task. While it takes a while to execute a test for the first time, subsequent executions will be much smoother and test times will reduce. 

You can determine the efficiency of your QA team by measuring the average time it takes to execute each test in a given cycle. These times should decrease after initial testing and eventually plateau at a base level. QA teams can improve these numbers by looking at what tests can be run concurrently or automated.

Improve your QA effectiveness with Trigent

Trigent’s experienced and versatile Quality Assurance and the Testing team is a major contributor to the successful launch, upgrade, and maintenance of quality software used by millions around the globe. Our experienced responsible testing practices put process before convenience to delight stakeholders with an impressive industry rivaled Defect Escape Ratio or DER of 0.2.

Trigent is an early pioneer in IT outsourcing and offshore software development business. We enable organizations to adopt digital processes and customer engagement models to achieve outstanding results and end-user experience. We help clients achieve this through enterprise-wide digital transformation, modernization, and optimization of their IT environment. Our decades of experience, deep domain knowledge, and technology expertise deliver transformational solutions to ISVs, enterprises, and SMBs.

Ensure the QA effectiveness and application performance. Talk to us

Quality Assurance outsourcing in the World of DevOps-Best Practices for Dispersed (Distributed) Quality Assurance Team

Why Quality Assurance (QA) outsourcing is good for business

The software testing services is expected to grow by more than USD 55 Billion between 2022-2026. With outsourced QA being expedited through teams distributed across geographies and locations, many aspects that were hitherto guaranteed through co-located teams have now come under a lot of pressure. Concerns range from constant communication and interworking to coverage across a wide range of testing types – unit testing, API testing, as well as validating experiences across a wide range of channels.

Additionally, it is essential to note that DevOps is the preferred methodology for software development and release, with collaborating teams oriented towards faster delivery cycles augmented by early feedback. And QA is regarded as a critical binding thread of DevOps practice, thereby ensuring a balanced approach in maintaining collaboration and communication between teams while ensuring that delivery cycles are up to speed and the quality of the delivered product meets customer expectations.

Best practices for ensuring the effectiveness of distributed QA teams

Focus on the right capability: 
While organizations focus to a large extent on bringing capabilities across development, support, QA, operations, and product management in a scrum team, paramount from a quality perspective would be QA skills. The challenge is to find the right skill mix. For example, a good exploratory tester; and automation skills (not necessarily in the same person). In addition, specialist skills related to performance, security, and accessibility also need to be thought through. The key is to choose an optimum mix of specialists and generalists.

Aim to achieve the right platform/tool mix: 
It is vital to maintain consistency across the tool stacks used for engagement. According to a 451 research survey, 39% of respondents juggle between 11 to 30 tools to keep an eye on their application infrastructure and cloud environment; 8% are found to use over 21 to 30 tools. Commonly referred to as tool sprawl, this makes it extremely difficult to collaborate in an often decentralized and distributed QA environment. It’s imperative to have a balanced approach toward the tool mix by influencing the team to adopt a common set of tools instead of making it mandatory.

Ensure a robust CI/CD process and environment:
A weak and insipid process may cause the development and operations team to run into problems while integrating new code.  With several geographically distributed teams committing code consistently into the CI environment, shared dev/test/deploy environments constantly run into issues if sufficient thought process has not gone into identifying environment configurations.  These can ultimately translate into failed tests and, thereby, failed delivery/deployment.  A well-defined automated process ensures continuous deployment and monitoring throughout the lifecycle of an application, from integration and testing phases through to the release and support.

A good practice would be to adopt cloud-based infrastructure, reinforced by mechanisms for managing any escalations on deployment issues effectively and quickly.  Issues like build failure or lack of infrastructure support can hamper the productivity of distributed teams.  When strengthened by remote alerts, robust reporting capabilities for teams, and resilient communication infrastructure, accelerated development to deployment becomes a reality.

Follow good development practices:
Joint backlog grooming exercises with all stakeholders, regular updates on progress, code analysis, and effective build and deployment practices, as well as establishing a workflow for defect/issue management, are paramount in ensuring the effectiveness of distributed teams. Equally important is the need to manage risk early with ongoing impact analysis, code quality reviews, risk-based testing, and real-time risk assessments. In short, the adoption of risk and impact assessment mechanisms is vital.

Another critical area of focus is the need to ascertain robust metrics that help in the early identification of quality issues and ease the process of integration with the development cycle. Research conducted in 2020 by Gatepoint and Perfecto surveyed executives from over 100 leading digital enterprises in the United States on their testing habits, tools, and challenges. The survey results showed that 63 percent start testing only after a new build and code is developed. Just 40 percent test upon each code change or at the start of new software.

Devote special attention to automation testing:
Manual (or exploratory) testing allows you to ensure that product features are well tested, while automation of tests (or, as some say, checks) helps you improve coverage for repeatable tasks. Though planning for both during your early sprint planning meetings is essential, test automation services have become an integral testing component. 

As per studies, in 2020, approximately 44 percent of IT companies have automated half of their testing. Businesses are continuously adopting test automation to fulfill the demand for quality at speed. Hence it is no surprise that according to Data Bridge Market research, the automation testing market will reach an estimated value of USD 19.9 billion by 2028 and grow at a CAGR of 14.89% in the forecast period of 2021 to 2028.

Outsourcing test automation is a sure-shot way of conducting testing and maintaining product quality. Keeping the rising demand in mind, let us look at a few benefits of outsourcing test automation services.

Early non-functional focus: 
Organizations tend to overlook the importance of bringing in occasional validations of how the product fares around performance, security vulnerabilities, or even important regulations like accessibility until late in the day. As per the 2020 DevSecOps Community Survey, 55 percent of respondents deploy at least once per week, and 11 percent claim multiple daily deployments.  But when it comes to security, 44 percent of the mature DevOps practices know it’s important but don’t have time to devote to it.

Security has a further impact on CI/CD tool stack deployment itself, as indicated by a 451 research in which more than 60% of respondents said a lack of automated, integrated security tools is a big challenge in implementing CI/CD tools effectively. 

It is essential that any issue which is non-functional in nature be exposed and dealt with before it moves down the dev pipeline. Adoption of a non-functional focus depends to a large extent on the evolution of the product and the risk to the organization.

Benefits of outsourcing your QA

To make distributed QA teams successful, an organization must have the capability to focus in a balanced and consistent way across the length and breadth of the QA spectrum, from people and processes to technology stacks. However, the ability to make these practices work hinges on the diligence with which an organization institutionalizes these best practices as well as platforms and supplements it with an organizational culture that is open to change.

Trigent’s experienced and versatile Quality Assurance and Testing team is a major contributor to the successful launch, upgrade, and maintenance of quality software used by millions around the globe. Our experienced, continuous testing practices put process before convenience to delight stakeholders with an impressive industry rivaled Defect Escape Ratio or DER of 0.2.

Ensure increased application availability and infrastructure performance. Talk to us.

5 Ways You are Missing Out on ROI in QA Automation

QA Automation is for everyone, whether you are a startup with a single product and few early adopters or a mid-sized company with a portfolio of products and multiple deployments. It assures product quality by ensuring maximum test coverage that is consistently executed prior to every release and is done in the most efficient manner possible.

Test Automation does not mean having fewer Test Engineers – It means using them efficiently in scenarios that warrant skilled testing, with routine and repetitive tests automated.

When done right, Test Automation unlocks significant value for the business. The Return on Investment (RoI) is a classical approach that attempts to quantify the impact and in turn, justify the investment decision.

However, the simplistic approach that is typically adopted to compute RoI provides a myopic view of the value derived from test automation. More importantly, it offers very little information to the Management on how to leverage additional savings and value from the initiative. Hence, it is vital that the RoI calculations take into account all the factors that contribute to its success.

Limitations of the conventional model to compute Test Automation ROI

Software leadership teams treat QA as a cost center and therefore apply a simplistic approach to computing RoI. The formula applied is

You may quickly notice the limitation in this formula. RoI should take into account the ‘Returns’ gained from ‘Investments’ made.

By only considering the Cost Savings gained from the reduction in testing, the true value of Test Automation is grossly underestimated.

In addition to the savings in terms of resources, attributes like the value of faster time to market, the opportunity cost of a bad Customer Experience due to buggy code, and being resilient to attrition, need to be factored in to fully compute the “Returns” earned. How to determine the value of these factors and incorporate them into the RoI formula is another blog in itself

Beyond Faster Testing – 5 ways to lower costs with Test Automation

For the moment, we will explore how companies can derive maximum savings while in Test Automation implementation. While calculating the ‘Cost Savings’ component of the RoI, it is important to take at least a 3-year view of the evolution of the product portfolio and its impact on the testing needs. The primary reason is that the ratio of manual tests to regression tests decreases over time and the percentage of tests that can be automated to total tests increases. With this critical factor in mind, let us look at how businesses can unlock additional savings

Test Automation Framework – Build vs. Partner

The initial instinct of software teams is to pick one of the open-source frameworks and quickly customize it for your specific need. While it’s a good strategy to get started, as the product mix grows and the scope of testing increases, considerable effort is needed to keep the Framework relevant or to fully integrate the framework into your CI/CD pipeline. This additional effort could wipe away any gains made with test automation

By using a vendor or testing partner’s Test Automation Framework, the Engineering team can be assured that it’s versatile to suit their future needs, give them the freedom to use different tools, and most importantly benefit from the industry best practices, thereby eliminating trial and error.

Create test scripts faster with ‘Accelerators’

When partnering with a QE provider with relevant domain expertise, you can take advantage of the partners’ suite of pre-built test cases to get started quickly. With little or no customization, the ‘accelerators’ allow you to create and run your initial test scripts and get results faster.

Accelerators also serve as a guide to design a test suite that maximizes coverage

Using accelerators to create the standard use cases typical for that industry ensures that your team has the bandwidth to invest in the use cases unique to your product and requires special attention.

Automate Test Design, Execution and Maintenance

When people talk of Test Automation, the term “automate” usually refers to test execution. However, execution is just 30% of the testing process. To accelerate the pace of production releases require unlocking efficiency across the testing cycle including design & maintenance.

Visual Test Design to gather functional requirements and develop the optimal number of most relevant tests, AI tools for efficient and automated test maintenance without generating any technical debt need to be leveraged. When implemented right, they deliver 30% gains in creation and 50% savings in maintenance

Shift Performance Testing left with Automation

In addition to creating capacity for the QA team to focus on tests to assure that the innovations deliver the expected value, you can set up Automated Performance Testing to rapidly check the speed, response time, reliability, resource usage, and scalability of software under an expected workload.

Shifting performance testing left allows you to identify potential performance bottleneck issues earlier in the development cycle. Performance issues are tricky to resolve, especially if issues are related to code or architecture. Test Automation enables automated performance testing and in turn, assures functional and performance quality.

Automate deployment of Test Data Sets

Creating or generating quality test data, specially Transactional Data Sets, have been known to cause delays. Based on our experience, the average time lost in waiting for the right test data is 5 days, while for innovation use cases, they take weeks. For thorough testing, often the test data needs to change during the execution of the test, which needs to be catered for

With a Test Data Automation, the test database can be refreshed on-demand. Testers access data subsets required for their suite of test cases and consistent data sets are utilized across multiple environments. Using a cogent test data set across varied use cases allows for data-driven insights for the entire product – which would be difficult with test data silos

Maximize your ROI with Trigent

The benefits, and therefore the ‘Returns’, from Test Automation, go well beyond the savings from reduced manual testing time and effort. It also serves as insurance against attrition! Losing people is inevitable, but you can ensure that the historical product knowledge is retained with your extensive suite of automated test scripts.

Partnering with a QE Service Provider having relevant domain experience will enable you to get your Quality processes right the first time – And get it done fast. Saving you valuable time and money. And it frees up your in-house team to focus on the test cases to assure the customer experiences that make your product special.

Do your QA efforts meet all your application needs? Is it yielding the desired ROI? Let’s talk!

Five Metrics to Track the Performance of Your Quality Assurance Teams and the efficiency of your Quality Assurance strategy

Why Quality Assurance and Engineering?

A product goes through different stages of a release cycle, from development and testing to deployment, use, and constant evolution. Organizations often seek to hasten their long release cycle while maintaining product quality. Additionally, ensuring a superior and connected customer experience is one of the primary objectives for organizations. According to a PWC research report published in 2020, 1 in 3 customers is willing to leave a brand after one bad experience. This is where Quality Engineering comes in.

There is a need to swiftly identify risks, be it bugs, errors, and problems, that can impact the business or ruin the customer experience. Most of the time, organizations cannot cover the entire scope of their testing needs, and this is where they decide to invest in Quality Assurance outsourcing.

Developing a sound Quality Assurance (QA) strategy

Software products are currently being developed for a unified CX. To meet the ever-evolving customer expectations, applications are created to deliver a seamless experience on multiple devices on various platforms. Continuous testing across devices and browsers, as well as apt deployment of multi-platform products, are essential. These require domain expertise, complimenting infrastructure, and a sound QA strategy. According to a report published in 2020-2021, the budget proportion allocated for QA was approximately 22%. 

Digital transformation has a massive impact on the time-to-market. Reduced cycle time for releasing multiple application versions by adopting Agile and DevOps principles has become imperative for providing a competitive edge. This has made automation an irreplaceable element in one’s QA strategy. With automation, a team can run tests for 16 additional hours (excluding the 8 hours of effort, on average, by a manual tester) a day, thus reducing the average cost of testing hours. In fact, as per studies, in 2020, approximately 44 percent of IT companies have automated half of their testing. 

A thorough strategy provides transparency on delivery timelines and strong interactions between developers and the testing team that comprehensively covers every aspect of the testing pyramid, from robust unit tests and contracts to functional end-to-end tests. 

Key performance metrics for QA

There are a lot of benefits to tracking performance metrics. QA performance metrics are essential for discarding inefficient strategies. The metrics also enable managers to track the progress of the QA team over time and make data-driven decisions. 

Here are five metrics to track the performance of your Quality Assurance team and the efficiency of your Quality Assurance strategy. 

1) Reduced risk build-on-build:

This metric is instrumental in ensuring a build’s stability over time by revealing the valid defects in builds. The goal is to decrease the number of risks impacting defects from one build compared to the next over the course of the QA project. However, this strategy, whilst keeping risk at the center of any release, aims to achieve the right levels of coverage across new and existing functionality. 

If the QA team experiences a constant increase in risk impacting defects, it may be because of the following reasons:

To measure the effectiveness further, one should also note the mean time to detect and the mean time to repair a defect.

2) Automated tests

Automation is instrumental in speeding up your release cycle while maintaining quality as it increases the depth, accuracy, and, more importantly, coverage of the test cases. According to a research report published in 2002, the earlier a defect is found, the more economical it is to fix, as it costs approximately five times more to fix a coding defect once the system is released.

With higher test coverage, an organization can find more defects before a release goes into production. Automation also significantly reduces the time to market by expediting the pace of development and testing. In fact, as per a 2020-2021 survey report, approximately 69% of the survey respondents stated reduced test cycle time to be a key benefit of automation. 

To ensure that the QA team maintains productivity and efficiency levels, measuring the number of automation test cases and delivering new automation scripts is essential. The metric monitors the speed of test case delivery and identifies the programs needing further testing. We recommend analyzing your automation coverage by monitoring total test cases. 

While measuring this metric, we recommend taking into account:

  • Requirements coverage vs. automated test coverage
  • Increased test coverage due to automation (for instance, multiple devices/browsers)
  • Total test duration savings

3) Tracking the escaped bugs and classifying the severity of bugs:

Ideally, there should be no defects deployed into the production. However, despite best efforts, most of the time, bugs make it into production. To track this would involve the team establishing checks and balances and classifying the severity of the defects. The team can measure the overall impact by analyzing the bugs of high severity levels that made into production. This is one of the best overall metrics for evaluating the effectiveness of your QA processes.  Customer-reported issues/defects may help identify specific ways to improve testing. 

4) Analyzing the execution time of test cycles:

The QA teams should keep track of the time taken to execute a test. The primary aim of this metric is to record and verify the time taken to run a test for the first time compared to subsequent executions. This metric can be a useful one to identify automation candidates, thereby reducing the overall test cycle time. The team should identify tests that can be run concurrently to increase effectiveness. 

5) Summary of active defects

This includes a team capturing information such as the names and descriptions of a defect. The team should keep a track/summary of verified, closed, and reopened defects over time. A low trajectory in the number of defects indicates a high quality of a product.

Be Agile and surge ahead in your business with Trigent’s QE services 

Quality Assurance is essential in every product development, and applying the right QA metrics enables you to track your progress over time. Trigent’s quality engineering services empower organizations to increase customer adoption and reduce maintenance costs by delivering a superior-quality product that is release-ready.

Are you looking to build a sound Quality Assurance strategy for your organization? Need Help? Talk to us. 

5 ways QA can help you accelerate and improve your DevOps CI/CD cycle

A practical and thorough testing strategy is essential to keep your evolving application up to date with industry standards.

In today’s digital world, nearly 50% of organizations have automated their software release to production. It is not surprising given that 80% of organizations prioritize their CX and cannot afford a longer wait time to add new features to their applications.  A reliable high-frequency deployment can be implemented by automating the testing and delivery process. This will reduce the total deployment time drastically. 

Over 62% of enterprises use CI/CD (continuous integration/continuous delivery) pipelines to automate their software delivery process.  Yet once the organization establishes its main pipelines to orchestrate software testing and promotion, these are often left unreviewed.  As a result, the software developed through the CI/CD toolchains evolve frequently.  While the software release processes remain stagnant. 

The importance of an optimal QA DevOps strategy

DevOps has many benefits in reducing cost, facilitating scalability, and improving productivity. However, one of its most critical goals is to make continuous code deliveries faster and more testable. This is achieved by improving the deployment frequency with judicious automation both in terms of delivery and testing. 

Most successful companies deploy their software multiple times a day. Netflix leverages automation and open source to help its engineers deploy code thousands of times daily. Within a year of its migration to AWS, Amazon engineers’ deployed code every 11.7 seconds with robust testing automation and deployment suite.  

A stringent automated testing suite is essential to ensure system stability and flawless delivery. It helps ensure that nothing is broken every time a new deployment is made. 

The incident of Knight Capital underlines this importance. For years, Knight relied on an internal application named SMARS to manage their buy orders in the stock market. This app had many outdated sections in its codebase that were not removed. While integrating a new code, Knight overlooked a bug that inadvertently called one of these obsolete features. This resulted in the company making buy orders worth billions in minutes. It ended up paying a $460M fine and going bankrupt overnight.

A good QA protects against the failed changes and ensures that it does not trickle down and affects the other components.  Implementing test automation in CI/CD will ensure that every new feature undergoes unit, integration, and functional tests. With this, we can have a highly reliable continuous integration process with greater deployment frequency, security, reliability, and ease. 

An optimal QA strategy to streamline the DevOps cycle would include a well-thought-out and judiciously implemented automation for QA and delivery. This would help in ensuring a shorter CI/CD cycle. It would also offer application stability and recover from any test failure without creating outages. Smaller deployment packages will ensure easier testing and faster deployment. 

5 QA testing strategies to accelerate CI/CD cycle

Most good DevOps implementations include strong interactions between developers and rigorous, in-built testing that comprehensively covers every level of the testing pyramid. This includes robust unit tests and contracts for API and functional end-to-end tests. 

Here are 5 best QA testing strategies you should consider to improve the quality of your software release cycles:

Validate API performance with API testing

APIs are one of the most critical components of a software application. It holds together the different systems involved in the application. The different entities that rely on the API, ranging from users, mobile devices, IoT devices, and applications, are also constantly expanding. Hence it is crucial to test and ensure its performance. 

Many popular tools such as Soap UI and Swagger can easily be plugged into any CI/CD pipeline. These tools help execute API tests directly from your pipeline. This will help you build and automate your test suites to run in parallel and reduce the test execution time.

Ensure flawless user experience with Automated GUI testing

Just like an API, the functionality and stability of GUIs are critical for a successful application rollout.  GUI issues after production rollout can be disastrous users wouldn’t be able to access the app or parts of its functionality.  Such issues would be challenging to troubleshoot as they might reside in individual browsers or environments. 

A robust and automated GUI test suite covering all supported browsers and mobile platforms can shorten testing cycles and ensure a consistent user experience. Automated GUI testing tools can simulate user behavior on the application and compare the expected results to the actual results. GUI testing tools like Appium and Selenium help testers simulate the user journey.  These testing tools can be integrated with any CI/CD pipeline. 

Incorporating these tools in your automated release cycle can validate GUI functions across various browsers and platforms.

Handle unscheduled outages with Non-functional testing

You may often encounter unexpected outages or failures once an application is in production. These may include environmental triggers like a data center network interruption or unusual traffic spikes. These are often outlying situations that may lead to a crisis, provided your application cannot handle it with grace. Here lies the importance of automated non-functional testing

Nonfunctional testing incorporates an application’s behavior under external or often uncontrollable factors, such as stress, load, volume, or unexpected environmental events. It is a broad category with several tools that can be incorporated into the CI/CD cycle. Integrating automated non-functional testing gates within your pipeline is advisable before the application gets released to production.

Improve application security with App Sec testing

Many enterprises don’t address security until later in the application release cycle. The introduction of DevSecOps has increased focus on including security checkpoints throughout the application release lifecycle. The earlier a security vulnerability is identified, the cheaper it is to resolve. Today, different automated security scanning tools are available depending on the assets tested.

The more comprehensive your approach to security scanning, your organization’s overall security posture will be better. Introducing checkpoints early is often a great way to impact the quality of the released software. 

Secure end-to-end functionality with Regression testing 

Changes to one component may sometimes have downstream effects across the complete system functionality. Since software involves many interconnected parts today, it’s essential to establish a solid regression testing strategy.

Regression testing should verify that the existing business functionality performs as expected even when changes are made to the system. Without this, bugs and vulnerabilities may appear in the system components. These problems become harder to identify and diagnose once the application is released. Teams doing troubleshooting may not know where to begin, especially if the release did not modify the failing component.

Accelerate your application rollout with Trigent’s QA services

HP LaserJet Firmware division improved its software delivery process and reduced its overall development cost by 40%. They achieved this by implementing a delivery process that focussed on test automation and continuous integration. 

Around 88% of organizations that participated in research conducted on CI/CD claim they lack the technical skill and knowledge to adopt testing and deployment automation. The right QA partner can help you devise a robust test automation strategy to reduce deployment time and cost. 

New-age applications are complex. While the DevOps CI/CD cycle may quicken its rollout, it may fail if not bolstered by a robust QA strategy. QA is integral to the DevOps process; without it, continuous development and delivery are inconceivable. 

Does your QA meet all your application needs? Need help? Let’s talk

TestOps – Assuring application quality at scale

The importance of TestOps

Continuous development, integration, testing, and deployment have become the norm for modern application development cycles. With the increased adoption of DevOps principles to accelerate release velocity, testing has shifted left to be embedded in the earlier stages of the development process itself. In addition, microservices-led application architecture has led to the adoption of shift right testing and testing individual services, and releases in the later stages of development, adding further complexity to the way quality is assured.

These challenges underline the need for automated testing. An increasing number of releases on one hand and an equally reducing release cycle times on the other have led to a strong need to exponentially increase the number of automated tests developed sprint after sprint. Although automation test suites reduce testing times, scaling these suites for large application development cycles mandates a different approach.

TestOps for effective DevOps – QA integration

In its most simplistic definition, TestOps brings together development, operations, and QA teams and drives them to collaborate effectively to achieve true CI/CD discipline. Leveraging four core principles across planning, control, management, and insights helps achieve test automation at scale.

  • Planning helps the team prioritize key elements of the release and analyze risks affecting QA like goals, code complexity, test coverage, and automatability. It’s an ongoing collaborative process that embeds rapid iteration for incorporating faster feedback cycles into each release.
  • Control refers to the ability to perform continuous monitoring and adjust the flow of various processes. While a smaller team might work well with the right documentation, larger teams mandate the need for established processes. Control essentially gives test ownership to the larger product team itself regardless of what aspect of testing is being looked at like functional, regression, performance, or unit testing.
  • Management outlines the division of activities among team members, establishes conventions and communication guidelines, and organizes test cases into actionable modules within test suites. This is essential in complex application development frameworks involving hundreds of developers, where continuous communication becomes a challenge.
  • Insight is a crucial element that analyses data from testing and uses it to bring about changes that enhance application quality and team effectiveness. Of late, AI/ML technologies have found their way into this phase of TestOps for better QA insights and predictions.

What differentiates TestOps

Unlike existing common notions, TestOps is not merely an integration of testing and operations. The DevOps framework already incorporates testing and collaboration right from the early stages of the development cycle. However, services-based application architecture introduces a wide range of interception points that mandate testing. These, combined with a series of newer test techniques like API testing, visual testing, and load and performance testing, slow down release cycles considerably. TestOps complements DevOps to plan, manage and automate testing across the entire spectrum, right from functional and non-functional testing to security and CI/CD pipelines. TestOps brings the ability to continuously test multiple levels with multiple automation toolsets and manage effectively to address scale.

TestOps effectively integrates software testing skillset and DevOps capability along with an ability to create an automation framework with test analytics and advanced reporting. By managing test-related DevOps initiatives, it can effectively curate the test pipeline, own it, manage effectively to incorporate business changes, and adapt faster. Having visibility across the pipeline through automated reporting capabilities also brings the ability to detect failing tests faster, driving faster business responses.

By sharply focusing on test pipelines, TestOps enables automatic and timely balancing of test loads across multiple environments, thereby driving value creation irrespective of an increase in test demand. Leveraging actionable insights on test coverage, release readiness, and real-time analysis, TestOps ups the QA game through root cause analysis of application failure points, obviating any need to crunch tons of log files for relevant failure information.

Ensure quality at scale with TestOps

Many organizations fail to consistently ensure quality across their application releases in today’s digital-first application development mode. The major reason behind this is their inability to keep up with test coverage of frequent application releases. Smaller teams ensure complete test coverage by building appropriate automation stacks and effectively collaborating with development and operations teams. For larger teams, this means laying down automation processes, frameworks, and toolsets to manage and run test pipelines with in-depth visibility into test operations. For assuring quality at scale, TestOps is mandatory. 

Does your QA approach meet your project needs at scale? Let’s talk

QE strategy to mitigate inherent risks involved in application migration to the cloud

Cloud migration strategies, be it lift & shift, rearchitect or rebuild, are fraught with inherent risks which need to be eliminated with the right QE approach

The adoption of cloud environments has been expanding for several years and is presently in an accelerated mode. A multi-cloud strategy is the defacto approach adopted by multiple organizations, as per Flexera 2022 State of the Cloud Report. The move toward cloud-native application architectures, exponential scaling needs of applications, and increased frequency and speed of product release launches have contributed to increased cloud adoption.

The success of migrating the application landscape to the cloud hinges on the ability to perform end-to-end quality assurance initiatives specific to the cloud. 

Underestimation of application performance

Availability, scalability, reliability, and high response rates are critical expectations from an application in a cloud environment. Application performance issues can come to light on account of incorrect sizing of servers or network latency issues that might not have surfaced when the application is tested in isolation. It can also be an outcome of an incorrect understanding of probable workloads that can be managed by an application while in a cloud environment. 

The right performance engineering strategy involves designing for performance in mind and fulfilling performance validations, including load testing. This ensures that the application under test remains stable in normal and peak conditions and defines and sets up application monitoring toolsets and parameters. There needs to be an understanding of workloads with the potential to be moved to the cloud and ones that need to remain on-premise. Incompatible application architectures need to be identified. Load testing should be carried out in parallel to record SLA response times across various loads for those moved to the cloud. 

Security and compliance

With the increased adoption of data privacy norms like GDPR and CCPA, there is a renewed focus on ensuring the safety of data migrated from application to cloud. Incidents like the one with Marriott hotel, where half a million sensitive customer information like credit cards and identity were compromised, have brought the need to test the security of data loaded onto cloud environments. 

A must-have element of a sound QA strategy is to ensure that both applications and data are secure and can withstand malicious attacks. With cybersecurity attacks increasing both in quantity and innovative tactics, there is a strong need for the implementation of security policies and testing techniques, including but not limited to vulnerability scanning, penetration testing, and threat and risk assessment. These are aimed at the following.

  • Identifying security gaps and weaknesses in the system
  • DDoS attack prevention
  • Provide actionable insights on ways to eliminate potential vulnerabilities

Accuracy of Data migration 

Assuring the quality of data that is being migrated to the cloud remains the top challenge, without which the convenience and performance expectation from cloud adoption falls flat. It calls for assessing quality before migrating, monitoring during migration, and verifying the integrity and quality post-migration. This is fraught with multiple challenges like migrating from old data models, duplicate record management, and resolving data ownership, to name a few. 

White-box migration testing forms a key component of a robust data migration testing initiative. It starts off by logically verifying a migration script to guarantee it’s complete and accurate. This is followed by ensuring database compliance with required preconditions, e.g., detailed script description, source, and receiver structure, and data migration mapping. Furthermore, the QA team analyzes and assures the structure of the database, data storage formats, migration requirements, the formats of fields, etc. More recently, predictive data quality measures have also been adopted to get a centralized view and better control over data quality. 

Application Interoperability

Not all apps that need to migrate to the cloud may be compatible with the cloud environment. Some applications show better performance in a private or hybrid cloud than in a public cloud. Some others require minor tweaking, while others may require extensive reengineering or recoding. Not identifying cross-application dependencies before planning the migration waves can lead to failure. Equally important is the need to integrate with third-party tools for seamless communication across applications without glitches. 

A robust QA strategy needs to identify applications that are part of the network, their functionalities, and dependencies among applications, along with each app’s SLA since dependencies between systems and applications can make integration testing potentially challenging. Integration testing for cloud-based applications brings to the fore the need to consider the following: 

  • Resources for the validation of integration testing 
  • Assuring cloud migration by using third-party tools
  • Discovering glitches in coordination within the cloud
  • Application configuration in the cloud environment
  • Seamless integration across multiple surround applications

Ensure successful cloud migration with Trigent’s QE services

Application migration to the cloud can be a painful process without a robust QE strategy. With aspects such as data quality, security, app performance, and seamless connection with a host of surrounding applications being paramount in a cloud environment, the need for testing has become more critical than ever. 

Trigent’s cloud-first strategy enables organizations to leverage a customized, risk-mitigated cloud strategy and deployment model most suitable for the business. Our proven approach, frameworks, architectures, and partner ecosystem have helped businesses realize the potential of the cloud.

We provide a secure, seamless journey from in-house IT to a modern enterprise environment powered by Cloud. Our team of experts has enabled cloud transformation at scale and speed for small, medium, and large organizations across different industries. The transformation helps customers leverage the best architecture, application performance, infrastructure, and security without disrupting business continuity. 

Ensure a seamless cloud migration for your application. Contact us now!

The Best Test Data Management Practices in an Increasingly Digital World

A quick scan of the application landscape shows that customers are more empowered, digitally savvy, and eager to have superior experiences faster. To achieve and maintain leadership in this landscape, organizations need to update applications constantly and at speed. This is why dependency on agile, DevOps, and CI/CD technologies has increased tremendously, further translating to an exponential increase in the adoption of test data management initiatives. CI/CD pipelines benefit from the fact that any new code that is developed is automatically integrated into the main application and tested continuously. Automated tests are critical to success, and agility is lost when test data delivery does not match code development and integration velocity.

Why Test Data Management?

Industry data shows that up to 60% of development and testing time is consumed by data-related activities, with a significant portion dedicated to testing data management. This amply validates that the global test data management market is expected to grow at a CAGR of 11.5% over the forecast period 2020-2025, according to the ResearchandMarkets TDM report.

Best Practices for Test Data Management

Any organization focusing on making its test data management discipline stronger and capable of supporting the new age digital delivery landscape needs to focus on the following three cornerstones.

Applicability:
The principle of shift left mandates that each phase in an SDLC has a tight feedback loop that ensures defects don’t move down the development/deployment pipeline, making it less costly for errors to be detected and rectified. Its success hinges to a large extent on close mapping of test data to the production environment. Replicating or cloning production data is manually intensive, and as the World Quality Report 2020-21 shows, 79% of respondents create test data manually with each run. Scripts and automation tools can take up most heavy lifting and bring this down to a large extent when done well. With production quality data being very close to reality, defect leakage is reduced vastly, ultimately translating to a significant reduction in defect triage cost at later stages of development/deployment.

However, using production-quality data at all times may not be possible, especially in the case of applications that are only a prototype or built from scratch. Additionally, using a complete copy of the production database is time and effort-intensive – instead, it is worthwhile to identify relevant subsets for testing. A strategy that brings together the right mix of product quality data and synthetic data closely aligned to production data models is the best bet. While production data maps to narrower testing outcomes in realistic environments, synthetic data is much broader and enables you to simulate environments beyond the ambit of production data. Usage of test data automation platforms that allocates apt dataset combinations for tests can bring further stability to testing.

Tight coupling with production data is also complicated by a host of data privacy laws like GDPR, CCPA, CPPA, etc., that mandate protecting customer-sensitive information. Anonymizing data or obfuscating data to remove sensitive information is an approach that is followed to circumvent this issue. Usually, non-production environments are less secure, and data masking for protecting PII information becomes paramount.

Accuracy:
Accuracy is critical in today’s digital transformation-led SDLC, where app updates are being launched to market faster and need to be as error-free as possible, a nearly impossible feat without accurate test data. The technology landscape is also more complex and integrated like never before, percolating the complexity of data model relationships and the environments in which they are used. The need is to maintain a single source of data truth. Many organizations adopt the path of creating a gold master for data and then make data subsets based on the need of the application. Adopting tools that validate and update data automatically during each test run further ensures the accuracy of the master data.

Accuracy also entails ensuring the relevance of data in the context of the application being tested. Decade-old data formats might be applicable in the context of an insurance application that needs historic policy data formats. However, demographic data or data related to customer purchasing behavior applicable in a retail application context is highly dynamic. The centralized data governance structure addresses this issue, at times sunsetting the data that has served its purpose, preventing any unintended usage. This also reduces maintenance costs for archiving large amounts of test data.

Also important is a proper data governance mechanism that provides the right provisioning capability and ownership driven at a central level, thereby helping teams use a single data truth for testing. Adopting similar provisioning techniques can further remove any cross-team constraints and ensure accurate data is available on demand.

Availability:
The rapid adoption of digital platforms and application movement into cloud environments have been driving exponential growth in user-generated data and cloud data traffic. The pandemic has accelerated this trend by moving the majority of application usage online. ResearchandMarkets report states that for every terabyte of data growth in production, ten terabytes are used for development, testing, and other non-production use cases, thereby driving up costs. Given this magnitude of test data usage, it is essential to align data availability with the release schedules of the application so that testers don’t need to spend a lot of time tweaking data for every code release.

The other most crucial thing in ensuring data availability is to manage version control of the data, helping to overcome the confusion caused by conflicting and multiple versioned local databases/datasets. The centrally managed test data team will help ensure single data truth and provide subsets of data as applicable to various subsystems or based on the need of the application under test. The central data repository also needs to be an ever-changing, learning one since the APIs and interfaces of the application keeps evolving, driving the need for updating test data consistently. After every test, the quality of data can be evaluated and updated in the central repository making it more accurate. This further drives reusability of data across a plethora of similar test scenarios.

The importance of choosing the right test data management tools

In DevOps and CI/CD environments, accurate test data at high velocity is an additional critical dimension in ensuring continuous integration and deployment. Choosing the right test data management framework and tool suite helps automate various stages in making data test ready through data generation, masking, scripting, provisioning, and cloning. World quality report 2020-21 indicates that the adoption of cloud and tool stacks for TDM has witnessed an increase, but there is a need for more maturity to make effective use.

In summary, for test data management, like many other disciplines, there is no one size fits all approach. An optimum mix of production mapped data, and synthetic data, created and housed in a repository managed at a central level is an excellent way to go. However, this approach, primarily while focusing on synthetic data generation, comes with its own set of challenges, including the need to have strong domain and database expertise. Organizations have also been taking TDM to the next level by deploying AI and ML techniques, which scan through data sets at the central repository and suggest the most practical applications for a particular application under test.

Need help? Partner with experts from Trigent to get a customized test data management solution and be a leader in the new-age digital delivery landscape.

4 Rs for Scaling Outsourced QA

The first steps towards a rewarding QA outsourcing engagement

Expanding nature of products, the need for faster releases to market much ahead of the competition, knee jerk or ad hoc reactions to newer revenue streams with products, ever-increasing role of customer experience across newer channels of interaction, are all driving the need to scale up development and testing. With the increased adoption of DevOps, the need to scale takes a different color altogether.

Outsourcing QA has become the norm on account of its ability to address the scalability of testing initiatives and bring in a sharper focus on outcome-based engagements. The World Quality Report 2020 mentions that 34% of respondents felt QA teams lack skills especially on the AI/ML front. This further reinforces their need to outsource for getting the right mix of skill sets so as to avoid any temporary skill set gaps.

However, ensuring that your outsourced QA gives you speed and scale can be a reality only if the rules of engagement with the partner are clear. Focusing on 4 R’s as outlined below while embarking on the outsourcing journey, will help you derive maximum value.

  1. Right Partner
  2. Right Process
  3. Right Communication
  4. Right Outcome

Right Partner

The foremost step is to identify the right partner, one with a stable track record, depth in QA, domain as well as technology, and the right mix of skill sets across toolsets and frameworks. Further, given the blurring lines between QA and development with testing being integrated across the SDLC, there is a strong need for the partner to have strengths across DevOps, CI/CD in order to make a tangible impact on the delivery cycle.

The ability of the partner to bring to the table prebuilt accelerators can go a long way in achieving cost, time and efficiency benefits. The stability or track record of the partner translates to the ability to bring on board the right team which stays committed throughout the duration of the engagement. The team’s staying power assumes special significance in longer duration engagements wherein shifts in critical talent derail efficiency and timelines on account of challenges involved with newer talent onboarding and effective knowledge transfer.

An often overlooked area is the partner’s integrity. During the evaluation stages, claims pertaining to industry depth as well as technical expertise abound and partners tend to overpromise. Due care needs to be exercised to know if their recommendations are grounded in delivery experience. Closer look at the partner’s references and past engagements not only help to gain insight into their claims but also help to evaluate their ability to deliver in your context.

It’s also worthwhile to explore if the partner is open to differentiated commercial models that are more outcome-driven and based on your needs rather than being fixated on the traditional T&M model.

Right Process

With the right partner on board, creating a robust process and governing mechanism assumes tremendous significance. Mapping key touchpoints from the partner side, aligning them to your team, and identifying escalation points serve as a good starting point. With agile and DevOps principles having collaboration across teams as the cornerstone, development, QA, and business stakeholder interactions should form a key component of the process. While cross-functional teams with Dev QA competencies start off each sprint with a planning meeting, formulating cadence calls to assess progress and setting up code drop or hand-off criteria between Dev and QA can prevent Agile engagements from degrading into mini waterfall models.

Bringing in automated CI/CD pipelines obviates the need for handoffs substantially. Processes then need to track and manage areas such as quality and release readiness, visibility across all stages of the pipeline through reporting of essential KPIs, documentation for managing version control, resource management, and capacity planning. At times, toolset disparity between various stages and multiple teams driving parallel work streams creates numerous information silos leading to fragmented visibility at the product level. The right process should focus on integration aspects as well to bridge these gaps. Each team needs to be aware and given visibility on ownership at each stage of the pipeline.

Further, a sound process also brings in elements of risk mitigation and impact assessment and ensures adequate controls are built into SOP documents to circumvent any unforeseen event. Security measures are another critical area that needs to be incorporated into the process early on, more often it is an afterthought in the DevOps process. Puppet 2020 State of DevOps report mentions that integrating security fully into the software delivery process can quickly remediate critical vulnerabilities – 45% of organizations with this capability can remediate vulnerabilities within a day.

Right Communication

Clear and effective communication is an integral component of QA, more so when DevOps, Agile, and similar collaboration-heavy initiatives are pursued achieving QA at scale. Effective communication at the beginning of the sprint ensures that cross-functional teams are cognizant of the expectations from each of them and have their eye firmly fixed on the end goal of application release. From then on, a robust feedback loop, one that aims at continuous feedback and response, cutting across all stages of the value chain, plays a vital role in maintaining the health of the DevOps pipeline.

While regular stand-up meetings have their own place in DevOps, effective communication needs to go much beyond to focus on tools, insights across each stage, and collaboration. A wide range of messaging apps like Slack, email, and notification tools accelerate inter-team communication. Many of these toolkits are further integrated with RSS feeds, google drive, and various CI tools like Jenkins, Travis, Bamboo, etc. making build pushes and code change notifications fully automated. Developers need notifications when a build fails, testers need them when a build succeeds and Ops need to be notified at various stages depending on the release workflow.

The toolkits adopted by the partner also need to extend communication to your team. At times, it makes sense for the partner to have customer service and help desk support as an independent channel to accept your concern. The Puppet report further mentions that companies at a high level of DevOps maturity use ticketing systems 16% more than what is used by companies at the lower end of the maturity scale. Communication of the project’s progress and evolution to all concerned stakeholders is integral irrespective of the platforms used. Equally important is the need to categorize communication in terms of priority and based on what is most applicable to classes of users.

Documentation is an important component of communication and from our experiences, commonly underplayed. It is important for sharing work, knowledge transfer, continuous learning, and experimentation. Code that is well documented enables faster completion of audit as well. In CI/CD-based software release methodology, code documentation plays a strong role in version control across multiple releases. Experts advocate continuous documentation as core communication practice.

Right Outcome

Finally, it goes without saying that setting parameters for measuring the outcome, tracking and monitoring those, determines the success of the partner in scaling your QA initiatives. Metrics like velocity, reliability, reduced application release cycles and ability to ramp up/ramp down are commonly used. Further, there are also a set of metrics aimed at the efficiency of the CI/CD pipeline, like environment provisioning time, features deployment rate, and a series of build, integration, and deployment metrics. However, it is imperative to supplement these with others that are more aligned to customer-centricity – delivering user-ready software faster with minimal errors at scale.

In addition to the metrics that are used to measure and improve various stages of the CI/CD pipeline, we also need to track several non-negotiable improvement measures. Many of these like deployment frequency, error rates at increased load, performance & load balancing, automation coverage of delivery process and recoverability helps to ascertain the efficiency of QA scale up.

Closely following on the heels of an earlier point, an outcome based model which maps financials to your engagement objectives will help to track outcomes to a large extent. While the traditional T&M model is governed by transactional metrics, project overlays abound in cases where engagement scope does not align well to outcome expectations. An outcome-based model also pushes the partner to bring in innovation through AI/ML and similar new-age technology drivers – providing you access to such skillsets without the need for having them on your rolls.

If you are new to outsourcing or working with a new partner, it may be good to start with a non-critical aspect of the work (for regular testing or automation), establish the process and then scale the engagement. For those players having maturity in terms of adopting outsourced QA functions in some way or the other, the steps outlined earlier form an all-inclusive checklist to ensure maximization of engagement traction and effectiveness with the outsourcing partner.

Partner with us

Trigent’s experienced and versatile Quality Assurance and Testing team is a major contributor to the successful launch, upgrade, and maintenance of quality software used by millions around the globe. Our experienced responsible testing practices put process before convenience to delight stakeholders with an impressive industry rivaled Defect Escape Ratio or DER of 0.2.

Trigent is an early pioneer in IT outsourcing and offshore software development business. We enable organizations to adopt digital processes and customer engagement models to achieve outstanding results and end-user experience. We help clients achieve this through enterprise-wide digital transformation, modernization, and optimization of their IT environment. Our decades of experience, deep domain knowledge, and technology expertise deliver transformational solutions to ISVs, enterprises, and SMBs.

Contact us now.

Poor application performance can be fatal for your enterprise, avoid app degradation with application performance testing

If you’ve ever wondered what can possibly go wrong’ after creating a foolproof app, think again. Democrats’ Iowa Caucus voting app is a case in point. The Iowa caucus post-mortem pointed towards a flawed software development process and insufficient testing.

The enterprise software market revenue is expected to grow with a CAGR of 9.1% leading to a market volume of US$ 326,285.5 m by 2025. It is important that enterprises aggressively work towards getting their application performance testing efforts on track to ensure that all the individual components that go into the making of the app provide superior responses to ensure a better customer experience.

Banking app outages have also been pretty rampant in recent times putting the spotlight on the importance of application performance testing. Customers of Barclays, Santander, and HSBC suffered immensely when their mobile apps suddenly went down. It’s not as if banks worldwide are not digitally equipped. They dedicate at least 2-3 percent of their revenue to information technology along with additional expenses on building a superior IT infrastructure. What they also need is early and continuous performance testing to address and minimize the occurrence of such issues.

It is important that the application performs well not just when it goes live but later too. We give you a quick lowdown on application performance testing to help you gear up to meet modern-day challenges.

Application performance testing objectives

In general, users today, have little or no tolerance for bugs or poor response times. A faulty code can also lead to serious bottlenecks that can eventually lead to slowdown or downtime. Meanwhile, bottlenecks can arise from CPU utilization, disk usage, operating system limitations, or hardware issues.

Enterprises, therefore, need to conduct performance testing regularly to:

  • Ensure the app performs as expected
  • Identify and eliminate bottlenecks through continuous monitoring
  • Identify & eliminate limitations imposed by certain components
  • Identify and act on the causes of poor performance
  • Minimize implementation risks

Application performance testing parameters

Performance testing is based on various parameters that include load, stress, spike, endurance, volume, and scalability. Resilient apps can withstand increasing workloads, high volumes of data, and sudden or repetitive spikes in users and/or transactions.

As such, performance testing ensures that the app is designed keeping peak operations in mind, and all components comprising the app function as a cohesive unit to meet consumer requirements.
No matter how complex the app is, performance testing teams are often required to take the following steps:

  • Setting the performance criteria – Performance benchmarks need to be set and criteria should be identified in order to decide the course of the testing.
  • Adopting a user-centric approach – Every user is different and it is always a good idea to simulate a variety of end-users to imagine diverse scenarios and test for use cases accordingly. You would therefore need to factor in expected usage patterns, the peak times, length of an average session within the application, how many times do users use the application in a day, what is the most commonly used screen for the app, etc.
  • Evaluating the testing environment – It is important to understand the production environment, the tools available for testing, and the hardware, software, and configurations to be used before beginning the testing process. This helps us understand the challenges and plan accordingly.
  • Monitoring for the best user experience – Constant monitoring is an important step in application performance testing. It will give you answers to what, when, and why’ helping you fine-tune the performance of the application. How long does it take for the app to load, how does the latest deployment compare to previous ones, how well does the app perform while backend performances occur, etc. are things you need to assess. It is important that you leverage your performance scripts well with proper correlations, and monitor performance baselines for your database to ensure it can manage fresh data loads without diluting the user experience.
  • Re-engineering and re-testing – The tests can be rerun as required to review and analyze results, and fine-tune again if necessary.

Early Performance Testing

Test early. Why wait for users to complain when you can proactively run tests early in the development lifecycle to check for application readiness and performance? In the current (micro) service-oriented architecture approach, as soon as the component or an interface is built, performance testing at a smaller scale can allow us to uncover issues w.r.t concurrency, response time/latency, SLA, etc. This will allow us to identify bottlenecks early and gain confidence in the product as it is being built.

Performance testing best practices

For the app to perform optimally, you must adopt testing practices that can alleviate performance issues across all stages of the app cycle.

Our top recommendations are as follows:

  • Build a comprehensive performance model – Understand your system’s capacity to be ready for concurrent users, simultaneous requests, response times, system scalability, and user satisfaction. The app load time, for instance, is a critical metric irrespective of the industry you belong to. Mobile app load times can hugely impact consumer choices as highlighted in a study by Akamai which suggested conversion rates reduce by half and bounce rate increases by 6% if a mobile site load time goes up from 1 second to 3. It is therefore important that you factor in the changing needs of customers to build trust, loyalty, and offer a smooth user experience.
  • Update your test suite – The pace of technology is such that new development tools will debut all the time. It is therefore important for application performance testing teams to ensure they sharpen their skills often and are equipped with the latest testing tools and methodologies.

An application may boast of incredible functionality, but without the right application architecture, it won’t impress much. Some of the best brands have suffered heavily due to poor application performance. While Google lost about $2.3 million due to the massive outage that occurred in December 2020, AWS suffered a major outage after Amazon added a small amount of capacity to its Kinesis servers.

So, the next time you decide to put your application performance testing efforts on the back burner, you might as well ask yourself ‘what would be the cost of failure’?

Tide over application performance challenges with Trigent

With decades of experience and a bunch of the finest testing tools, our teams are equipped to help you across the gamut of application performance right from testing to engineering. We test apps for reliability, scalability, and performance while monitoring them continuously with real-time data and analytics.

Allow us to help you lead in the world of apps. Request a demo now.

Bandwidth Testing for superior user experience – here’s how?

The Bandwidth Testing process simulates a low internet bandwidth connection and checks how your application behaves under desired network speed.

Considering a scenario where a specific application’s home page always loads in milliseconds in office premises this may not be the case when an end-user with low network speed accesses the application. To enhance user experience and get to know the application load times at specific network bandwidth speeds, we can simulate it and identify specific component/service call which is taking more time and can be improved further.

How to test bandwidth

Prerequisites:

Bandwidth speed test can be done using Chrome browser. You should set your ‘Network’ panel in the chrome browser as per the below requirements.

Setup:

  1. Go to Customize and control Google Chrome at the top right corner and click More tools, then select Developer tools
    • Or press keyboard shortcut Ctrl + Shift + I
    • Or press F12
  2. Then click the ‘No throttling’ dropdown and choose Add… option under the Custom section.
  3. Click Add custom profile
  4. You will need to enter profile name in order to click on Add button. For example, ‘TestApp 1 MBPS’.
  5. Fill in the Download, Upload, Latency columns as below and click Add.

Example for 100Kbps:

Download (kb/s)Upload (kb/s)Latency (ms)
10050300

Example for 1Mbps:

Download (kb/s) Upload (kb/s)Latency (ms)
102451250

Example for 2.5Mbps:

Download (kb/s)Upload (kb/s)Latency (ms)
2600150030

Configuring Chrome is a one-time affair. Once Chrome has been configured for bandwidth speed test, use the same settings by selecting the profile name [TestApp 1 MBPS] from the No Throttling drop-down.

Metrics to be collected for bandwidth testing:

  • Data transferred (KB)
  • Time taken for data transfer (seconds)

Using Record network activity option in the Chrome browser, you can get the above attributes.

Note: Toggle button “Record network log”/”Stop recording network log” and button “Clear” are available in the network panel.

It is best practice to close all the non-testing applications/tools in the system and other tabs from Chrome where the testing is performed.

Steps for recording network activity:

  1. Open Developer Tools and select the Network tab.
  2. Clear network log before testing.
  3. Make sure Disable cache checkbox is checked.
  4. Select the created network throttling profile (say ‘TestApp 1 MBPS’).
  5. Start recording for the steps to be measured as per the scenario file.
  6. Wait for the completion of step and page is fully loaded to check the results
  7. Data transferred size for each recorded step will be displayed down in the status bar as highlighted. The size will be in byte/kilobyte/megabyte. Make note of it.
  8. Time taken for data transfer will be displayed in the timeline graph. The horizontal axis represents the time scale in a millisecond. Take the
  9. Maximum time. Take approximate value from the graph and make note of it.

Here is the sample screenshot taken for login process of snapdeal application page in which specific js component (base.jquery111.min.js) loading took 4.40s and also while searching for any product searchResult.min.js took 4.08s which can be improved further for better user experience.

This Bandwidth Testing Process helps in every possible way to improve user experience by identifying specific component or API calls which are taking more time to load and it helps developers to fix those specific components.

Your application’s performance is a major differentiator that decides whether it turns out to be a success or fails to meet expectations. Ensure your applications are peaked for optimal performance and success.

Improve page load speed and user experience with Trigent’s testing services

Trigent’s experienced and versatile Quality Assurance and Testing team is a major contributor in the successful launch, upgrade and maintenance of quality software used by millions around the globe. Our experienced responsible testing practices put process before convenience to delight stakeholders with an impressive industry rivaled Defect Escape Ratio or DER of 0.2.

Got a question? Contact us for a consultation

Responsible Testing – Human centricity in Testing

Responsibility in testing – What is responsible testing?

Consumers demand quality and expect more from products. The DevOps culture emphasizes the need for speed and scale of releases. As CI/CD crisscrosses with quality, it is vital to engage a human element in testing to foresee potential risks and think on behalf of the customer and the end-user.

Trigent looks at testing from a multiplicity of perspectives. Our test team gets involved at all stages of the DevOps cycle, not just when the product is ready. For us, responsible testing begins early in the cycle.

Introducing Quality factor in DevOps

A responsible testing approach goes beyond the call of pre-defined duties and facilitates end-to-end stakeholder assurance and business value creation. Processes and strategies like risk assessment, non-functional tests, and customer experiences are baked into testing. Trigent’s philosophy of Responsible Testing characterizes all that we focus on while testing for functionality, security, and performance of an application.

Risk coverage: Assessing the failure and impact early on is one of the most critical aspects of testing. We work along with our clients’ product development teams to understand what’s important to stakeholders, evaluate and anticipate risks involved early on giving our testing a sharp focus.

Collaborative Test Design: We consider the viewpoints of multiple stakeholders to get a collaborative test design in place. Asking the right questions to the right people to get their perspectives helps us in testing better.

Customer experience: Responsible Testing philosophy strongly underlines customer experience as a critical element of testing. We test for all promises that are made for each of the customer touchpoints.

Test early, test often: We take the shift-left approach early on in the DevOps cycle. More releases and shorter release times mean testing early and testing often translates into constantly rolling out new and enhanced requirements.

Early focus on non-functional testing: We plan for the non-functional testing needs at the beginning of the application life cycle. Our teams work closely with the DevOps team’s tests for security, performance, and accessibility – as early as possible.

Leverage automation: In our Responsible Testing philosophy, we look at it as a means to get the process to work faster and better. Or to leverage tools that can give better insights into testing, and areas to focus on testing. The mantra is judicious automation.

Release readiness: We evaluate all possibilities of going to the market – checking if we are operationally ready, planning for the support team’s readiness to take on the product. We also evaluate the readiness of the product, its behavior when it is actually released, and prepare for the subsequent changes expected.

Continuous feedback: Customer reviews, feedback speaks volumes of their experience with the application. We see it as an excellent opportunity to address customer concerns in real-time and offer a better product. Adopting the shift-right approach we focus on continuously monitoring product performance and leveraging the results in improving our test focus.

Think as a client. Test as a consumer.

Responsibility in testing is an organizational trait that is nurtured into Trigent’s work culture. We foster a culture where our testers imbibe qualities such as critical thinking on behalf of the client and the customer, the ability to adapt, and the willingness to learn.

Trigent values these qualitative aspects and soft skills in a responsible tester that contribute to the overall quality of testing and the product.
Responsibility: We take responsibility for the quality of testing of the product and also the possible business outcomes.

Communication: In today’s workplace, collaborating with multiple stakeholders, teams within and outside the organization is the reality. We emphasize not just the functional skill sets but the ability to understand people, empathize with different perspectives, and express requirements effectively across levels and functions.

Collaboration: We value the benefits of a good collaboration with BA/PO/Dev and QA and Testing – a trait critical to understanding the product features, usage models, and working seamlessly with cross-functional teams.

Critical thinking: As drivers of change in technology, it is critical to develop a mindset of asking the right questions and anticipating future risks for the business. In the process, we focus on gathering relevant information from the right stakeholders to form deep insights about the business and consumer. Our Responsible Testing approach keeps the customer experience at the heart of testing.

Adaptability & learning: In the constantly changing testing landscape, being able to quickly adapt to new technologies and the willingness to learn helps us offer better products and services.

Trigent’s Responsible Testing approach is a combination of technology and human intervention that elevates the user experience and the business value. To experience our Responsible Testing approach, talk to our experts for QA & Testing solutions.

Learn more about responsible testing in our webinar and about Trigent’s software testing services.

Improve the quality of digital experiences with Performance Engineering

Quality at the heart of business performance

“In 2020, the key expectation is fast, reliable, and trustworthy software.” *

As businesses embrace the Agile/DevOps culture and the emphasis on CI/CD is growing, quality assurance is seen as a standalone task, limited to validating functionalities implemented. When QA and Testing is an afterthought in an Agile/DevOps culture, the result is a subpar consumer experience followed by an adverse impact on the revenue pipeline. Poor customer experience also directly impacts brand credibility and business equity. While UI/UX are the visible elements of the customer experience, product, or service performance is a critical element that is often neglected. Performance Testing identifies the gaps that are addressed through Performance Engineering.

Small steps, significant gains – the journey towards Performance Engineering

The deeper issue lies in the organization’s approach towards quality and testing – it is considered an independent phase rather than looked upon as a collaborative and an integrated approach. Performance engineering is a set of methodologies that identifies potential risks and bottlenecks early on in the development stage of the product and addresses them. It goes without saying that performance is an essential ingredient in the quality of the product, there’s a deeper need for change in thinking – to think proactively, anticipate early in the development cycle, test and deliver a quality experience to the end consumer. An organization that makes gradual changes in its journey towards performance engineering stands to gain significantly. The leadership team, the product management, and the engineering and DevOps at different levels need to take the shift-left approach towards performance engineering.

Make Performance Engineering your strategic priority today

Despite the obvious advantages, performance testing is typically a reactive measure that is addressed after the initial launch. However, organizations need to embrace performance engineering measures right from the design phase, start small, and take incremental steps towards change.

Covid-19 has rapidly changed the way consumers behave globally. Businesses caught onto remote working; consumers moved shopping, entertainment, banking, learning, and medical consultations online. Consider the quantum jump in usage triggered by the pandemic.

The dramatic increase in the use of digital services has covered decades in days.**

Companies that adopted scalability and performance centric design have moved swiftly to capture the market opportunity.

With multiple user-interfaces across sectors being the norm and the increasing complexity of digital experiences, it is critical for businesses to get it right the first time in order to gain and retain customers’ trust.

As cloud migrations continue, whether rehosting the app on an IaaS or rebuilding a new approach, performance engineering ensures that migrated systems withstand sudden surges in usage. According to a Sogeti and Neotys report, 74% of the load testing infrastructure is operated in the cloud today. Cloud infrastructure providers ensure reliability but they may not be aware of the performance metrics that matter to the business and their impact. As organizations move from monolithic systems to distributed architectures provided by an assortment of companies, corporate leaders need to recognize the importance of performance engineering and embrace it to deliver the right solutions for the first time.

Our approach to Performance Engineering philosophy

At Trigent, we put the customer experience at the heart of planning the entire testing cycle. Our performance engineering practices align with ‘metrics that matter’ to businesses in the DevOps framework. While testing identifies the gaps in performance, the onus of architecting it right lies on the DevOps engineering team with proactive inputs from QA and Testing.

Performance engineering is also a way of thinking, the ability to plan for performance at the time of design, right at the beginning. As for quality, besides testing for functionality, anticipating potential bottlenecks helps us assess the process in its entirety in the beginning.

Asking some of these customer-centric questions early on shifts the perspective right at the outset. Ask them early, and you’re on your way to a performance engineering culture.

Parameters that matter

‘Will my application meet the defined response-time requirements of my customers?’

Consider an app that doesn’t respond within the expected standards of the customer; the chances of that application making it to the customer’s phone screen is pretty slim.

‘Will the application handle the expected user load and beyond?’

An application that tested well with 10 users may fail when that number is multiplied by a thousand or two.

We take the viewpoints of multiple stakeholders, consider parameters that matter to the customer, and assess impact early on.

Customer experience matters

Performance Engineering takes into account the overall experience of the end-user and their environment.

Asking pertinent questions such as ‘Will my users experience acceptable response times, even during peak hours?’ or ‘Does the application respond quickly enough for the intended users?’ does well to anticipate potential pitfalls in network usage and latency.

‘Where are the bottlenecks in my multi-user environment?’

Understand the real environment of the user and their challenges to provide a quality user experience.

Early Focus

The non-functional aspects are integrated into the DevOps and an early focus on performance enables us to gain insights into architectural issues.

‘How can we optimize the multi-user application before it goes live?
‘How can we detect errors that only occur under real-load conditions?

Quick course corrections help optimize performance and make the product market-ready. Besides faster deployment, quality assurance gives our clients an added advantage of reduced performance costs.

Architect it right

‘What system capacity is required to handle the expected load?’
‘Will the application handle the number of transactions required by the business?’

Important questions like these focus on architecting the product for performance. As part of the performance engineering methodology, our teams consistently check and validate the capabilities at the time of developing the product or scaling it up. We take the shift-left and shift-right approach to anticipate, identify, and remove bottlenecks early on. Getting the architecture right enables us to deliver and deploy a high-quality product every time.

Performance engineering done right is sure to improve the planning-to-deployment time with high-quality products. Plus, it reduces performance costs arising out of unforeseen issues. A step-by-step approach in testing makes sure organizations move towards achieving performance engineering. Talk to our experts for scalable performance engineering solutions for your business.

Learn more about Trigent software testing services.


Reference:
* The State of Performance Engineering 2020 – A Sogeti and Neotys report
** Meet the next-normal consumer – A McKinsey & Company report

Trigent excels in delivering Digital Transformation Services: GoodFirms

GoodFirms consists of researched companies and their reviews from genuine, authorized service-buyers across the IT industry. Furthermore, the companies are examined on crucial parameters of Quality, Reliability, and Ability and ranked based on the same. This factor helps customers to choose and hire companies by bridging the gap between the two.

They recently evaluated Trigent based on the same parameters, after which they found the firm excels in delivering IT Services, mainly:


Keeping Up with Latest Technology Through Cloud computing

Cloud computing technology has made the process of meeting the changing demands of clients and customers. The companies who are early adopters of the changing technologies always achieve cutting-edge in the market. Trigent’s cloud-first strategy is made to meet the clients’ needs by driving acceleration, customer insight, and connected experience to take businesses to the next orbit of cloud transformation. Their team exhibits the highest potential in cloud computing that improves business results across the key performance indicators (KPIs). The Trigent team is instilled with productivity, operational efficiency, and growth that increases profitability.

The team possesses years of experience and works attentively in the cloud adoption journey of their clients. The professionals curate all their knowledge to bring the best of services to the table. This way, the clients can seamlessly achieve goals and secure their place as a modern cloud based-enterprise. Their vigorous effort has placed them as the top cloud companies in Bangalore at GoodFirms website.

Propelling Business with Software Testing

Continuous efforts and innovations are essential for businesses to outpace in the competitive market. The Trigent team offers next-gen software testing services to warrant the delivery of superior quality software products that are release ready. The team uses agile – continuous integration, continuous deployment – and shift-left approaches by utilizing validated, automated tools. The team expertise covers functional, security, performance, usability, accessibility testing that extends across mobile, web, cloud, and microservices deployment.

The company caters to clients of all sizes across different industries. The clients have also sustained substantial growth by harnessing their decade-long experience and domain-knowledge. Bridging the gap between companies and customers and using agile methodology for test advisory & consulting, test automation, accessibility assurance, security testing, end to end functional testing, performance testing the company holds expertise in all. Thus, the company is dubbed as the top software testing company in Massachusetts at GoodFirms.

Optimizing Work with Artificial Intelligence

Artificial intelligence has been the emerging technology for many industries during the past decade. AI is defining technology by taking it to a whole new level of automation where machine learning, natural language process, and neural networks are used to deliver solutions. At Trigent, the team promises to support clients by utilizing AI and providing faster, more effective outcomes. By serving diverse industries with complete AI operating models – strategy, design, development, and execution – the firm is automating tasks. They are focused on empowering brands by adding machine capabilities to human intelligence and simplifying operations.

The AI development teams at Trigent are appropriately applying the resources to identify and govern a process that empowers and innovate business intelligence. Besides, with their help with continuous processes enhancements and AI feedback systems, many companies have been increasing productivity and revenues. Therefore, helping clients to earn profit with artificial intelligence, the firm would soon rank in the list of the artificial intelligence programming company at GoodFirms.

About GoodFirms

GoodFirms, a maverick B2B Research and Reviews Company helps in finding Cloud Computing, Testing Services, and Artificial Intelligence firms rendering the best services to its customers. Their  extensive research process ranks the companies, boosts their online reputation and helps service seekers pick the right technology partner that meets their business needs.

Responsible Testing in the Times of COVID

As a software tester, I have ensured that software products and applications function and perform as expected. My team has been at the forefront of using the latest tools and platforms to enable a minimal defect product for the market release. We are proud to have exceeded industry standards in terms of defect escape ratios.

The health scare COVID has interrupted almost all industries and processes, but society is resilient, never gives up, and life (and business) must go on. We are up to the task and giving our best in adapting to the testing times and situations.

Testing times for a software tester

While we have leveraged existing resources and technology to run umpteen tests in the past, the current pandemic that has enveloped the world has put us in unchartered territory. While our clients understand the gravity of the situation, they also need to keep their business running. We now work from home and continue testing products just like before without interruption. There have been challenges, but we have ensured business continuity to protect our client from any adverse impact of this disruption. From our testers struggling to adapt to the new world order, I would like to share how we sailed through these trying times. It might help you do what you do best, test!

Ensure access, security/integrity

As testers, we work in different environments such as on-prem, on the cloud, or the client-side cloud environment. Working from a secure office environment, we have access to all environments. It is not the same anymore, as we now use public networks. The best and most secure way to access governed environments is to connect via a VPN to access different environments securely. VPN’s offer secure, pre-engineered access and provide additional levels of bandwidth and control.

Use cloud-devices for compatibility tests

Testing applications for different platforms and devices is simpler at the workplace as we have ready access to company-owned devices (some of which are expensive). It’s not the same when working from home. Besides, these devices cannot be a shared resource. The unavailability of devices cannot act as a blockade. I am leveraging the cloud using resources such as SauceLab, Devicefarm alongside options such as simulators and emulators configured on my system.

Augment access speed for reliable testing

One concern working from home is the need for a dependable, high-speed internet connection. However, I signed up with a service provider offering verified speed. I buttressed my connectivity by arranging for an alternate internet connection from a different service provider with similar bandwidth capability. I made a distinction between these networks as network1 and network2, ensuring that the networks get utilized for the designated purpose, and bandwidth issues avoided.

Coordinate test plans with collaboration utilities

In the initial days of the work-from-home arrangement, I found it difficult to coordinate with the team and there were productivity concerns. This is when we decided to chalk a schedule to address coordination issues. We decided to better utilize the messenger tools provided to us for seamless communication. As a first step towards making optimal use of these messenger tools we drew guidelines on the do’s and don’ts to optimally use our time. This article penned by a senior colleague worked as a handy reference on using one such communication tool.

The future looks uncertain with Covid’s impact deepening by the day. In these times when everything looks uncertain we as responsible testers can play our role in ensuring that we are available to our partners and help products and apps reach their respective audience.

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