DevOps Success: 7 Essentials You Need to Know

High-performing IT teams are always looking for ways to adopt and use industry best practices and solutions. This enables them to overcome obstacles and achieve consistent and reliable commercial outcomes. A DevOps strategy enables the delivery of software products and services to the market in a more reliable and timely manner. The capacity of the team to have the correct combination of human judgment, culture, procedure, tools, and automation is critical to DevOps success.

Is DevOps the Best Approach for You?

DevOps is a solid framework that aids businesses in getting the most out of their digital efforts. It fosters a productive workplace by enhancing cooperation and value generation across all teams, including development, testing, and operations.

DevOps-savvy companies can launch software solutions more quickly into production, with shorter lead times and reduced failure rates. They have higher levels of responsiveness, are more resilient to production difficulties, and restore failed services more quickly.

However, just because every other IT manager is boasting about their DevOps success stories doesn’t mean you should jump in and try your hand at it. By planning ahead for your DevOps journey, you can avoid the traps that are sure to arise.

Here are seven essentials to keep in mind when you plan your DevOps journey.

1. DevOps necessitates a shift in work culture—manage it actively.

The most important feature of DevOps is the seamless integration of various IT teams to enable efficient execution. It results in a software delivery pipeline known as Continuous Integration-Continuous Delivery (CI/CD). Across development, testing, and operations, you must abandon the traditional silo approach and adopt a collaborative and transparent paradigm. Change is difficult and often met with opposition. It is tough for people to change their working habits overnight. You play an important role in addressing such issues in order to achieve cultural transformation. Be patient, persistent, and use continuous communication to build the necessary change in the management process.

2. DevOps isn’t a fix for capability limitations— it’s a way to improve customer experiences

DevOps isn’t a panacea for all of the problems plaguing your existing software delivery. Mismatches between what upper management expects and what is actually possible must be dealt with individually. DevOps will give you a return on your investment over time. Stakeholder expectations about what it takes to deploy DevOps in their organization should be managed by IT leaders.

Obtain top-level management buy-in and agreement on the DevOps strategy, approach, and plan. Define DevOps KPIs that are both attainable and measurable, and make sure that all stakeholders are aware of them.

3. Keep an eye out for going off-track during the Continuous Deployment Run

Only until you can forecast, track, and measure the end-customer advantages of each code deployment in production can you fully implement DevOps’ continuous deployment approach. In each deployment, focus on the features that are important to the business, their importance, plans, development, testing, and release.

At every stage of DevOps, developers, testers, and operations should all contribute to quality engineering principles. This ensures that continuous deployments are stable and reliable.

4. Restructure your testing team and redefine your quality assurance processes

To match with DevOps practices and culture, you must reimagine your testing life cycle process. To adapt and incorporate QA methods into every phase of DevOps, your testing staff needs to be rebuilt and retrained into a quality assurance regimen. Efforts must be oriented toward preventing or catching bugs in the early stages of development, as well as assisting in making every release of code into production reliable, robust, and fit for the company.

DevOps testing teams must evolve from a reactive, bug-hunting team to a proactive, customer-focused, and multi-skilled workforce capable of assisting development and operations.

5. Incorporate security practices earlier in the software development life cycle (SDLC)

Security is typically considered near the end of the IT value chain. This is primarily due to the lack of security knowledge among most development and testing teams. Information security’s confidentiality, integrity, and availability must be ingrained from the start of your SDLC to ensure that the code in production is secure against penetration, vulnerabilities, and threats.

Adopt and use methods and technologies to help your system become more resilient and self-healing. Integrating DevSecOps into DevOps cycles will allow you to combine security-focused mindsets, cultures, processes, tools, and methodologies across your software development life cycle.

6. Only use tools and automation when absolutely necessary

It’s not about automating everything in your software development life cycle with DevOps. DevOps emphasizes automation and the use of tools to improve agility, productivity, and quality. However, in the hurry to automate, one should not overlook the value and significance of the human judgment. From business research to production monitoring, the team draws vital insights and collective intelligence through constant and seamless collaborative efforts that can’t be substituted by any tool or automation.

Managers, developers, testers, security experts, operations, and support teams must collaborate to choose which technologies to utilize and which automation areas to automate. Automate tasks like code walkthroughs, unit testing, integration testing, build verification, regression testing, environment builds, and code deployments that are repetitive.

7. DevOps is still maturing, and there is no standard way to implement it

DevOps is continuously changing, and there is no one-size-fits-all approach or strategy for implementing it. DevOps implementations may be defined, interpreted, and conceptualized differently by different teams within the same organization. This could cause misunderstanding in your organization regarding all of your DevOps transformation efforts. For your company’s demands, you’ll need to develop a consistent method and plan. It’s preferable if you make sure all relevant voices are heard and ideas are distilled in order to produce a consistent plan and approach for your company. Before implementing DevOps methods across the board, conduct research, experiment, and run pilot projects.

(Originally published in Stickyminds)

5 Must-Haves for QA to Fit Perfectly into DevOps

DevOps is the ideal practice for software development businesses that want to code, build, test, and release software continuously. It’s popular because it stimulates cross-skilling and self-improvement by creating a fast-paced, results-oriented, collaborative workplace. QA in DevOps fosters agility, resulting in speedier operational support and fixes that meet stakeholder expectations. Most significantly, it ensures the timely delivery of high-quality software.

Quality Assurance and Testing (QAT) is a critical component of a successful DevOps strategy. QAT is a vital enabler that connects development and operations in a collaborative thread to assure the delivery of high-quality software and applications.

Integrating QA in DevOps

Five essentials play a crucial role in achieving flawless sync and seamlessly integrating QA into the DevOps process.

1. Concentrate on the Tenets of Testing

Testing is at the heart of QA; hence the greatest and most experienced testers with hands-on expertise must be on board. Some points to consider: the team must maintain a strong focus on risk, include critical testing thinking into the functional and non-functional parts of the application, and not lose sight of the agile testing quadrant’s needs. Working closely with the user community, pay particular attention to end-user experience tests.

2. Have relevant technical skills and a working knowledge of tools and frameworks

While studying and experimenting with the application is required, a thorough understanding of the unique development environment is also required. This guarantees that testers contribute value to the design stage talks and advise the development team on possibilities and restrictions. They must also be familiar with the operating environment and, most significantly, the application’s performance in the actual world.

The team’s skill set should also include a strong understanding of automation and the technologies required, as this adds rigor to the DevOps process and is necessary to keep it going. The QA team’s knowledge must be focused on tools, frameworks, and technologies. What should their automation strategy be? Do they advocate or utilize licensed or open-source software?

Are the tools for development, testing, deployment, and monitoring identified for the various software development life cycle stages? To avoid delays and derailing the process at any stage of development, it is critical to have comprehensive clarity on the use of tools. Teams with the competence should be able to experiment with technologies like artificial intelligence or machine learning to give the process a boost.

3. Agile Testing Methodologies

DevOps is synchronized agility that incorporates development, quality assurance, and operations. It’s a refined version of the agile technique. Agile/DevOps techniques now dominate software development and testing. Can the QA team ensure that in an Agile/DevOps environment, the proper coverage, aligned to the relevant risks, enhances velocity? Is the individual or group familiar with working in a fast-paced environment? Do they have the mechanisms to ensure continuous integration, development, testing, and deployment in cross-functional, distributed teams?

4. Industry experience that is relevant

Relevant industry knowledge ensures that the testers are aware of user experiences and their potential influence on business and can predict potential bottlenecks. Industry expertise improves efficiency and helps testers select testing that has the most impact on the company.

5. The Role of Culture

In DevOps, the QA team’s culture is a crucial factor. The DevOps methodology necessitates that QA team members be alert, quick to adapt, ethical, and work well with the development and operations teams. They serve as a link between the development and operations teams, and they are responsible for maintaining balance and ensuring that the process runs smoothly.

In a DevOps process, synchronizing the three pillars (development, quality assurance, and operations) is crucial for software products to fulfill expectations and deliver commercial value. The QA team serves as a link in this process, ensuring that software products transfer seamlessly from development to deployment. What factors do you believe QA can improve to integrate more quickly and influence the DevOps process?

(Originally published in Stickyminds)

QA in Cloud Environment – Key Aspects that Mandate a Shift in the QA Approach

Cloud computing is now the foundation for digital transformation. Starting as a technology disruptor a few years back, it has become the de facto approach for technology transformation initiatives. However, many organizations still struggle to optimize cloud adoption. Reasons abound – ranging from lack of a cohesive cloud strategy to mindset challenges in adopting cloud platforms. Irrespective of the reason, assuring the quality of applications in cloud environments remains a prominent cause for concern.

Studies indicate a wastage of $17.6 billion in cloud spend in 2020 due to multiple factors like idle resources, overprovisioning, and orphaned volumes and snapshots (Source parkmycloud.com). Further, some studies have pegged the cost of software bugs to be 1.1 trillion dollars. Assuring the quality of any application hosted on the cloud not only addresses its functional validation but also its performance-related aspects like load testing, stress testing, capacity planning, etc invariably addressing both the issues described above, thereby exponentially reducing the quantum of loss incurred on account of poor quality.

The complication for QA in cloud-based application arises due to many deployment models ranging from private cloud, public cloud to hybrid cloud, and application service models ranging from IaaS, PaaS, to SaaS. While looking at deployment models, testers will need to address infrastructure aspects and application quality. At the same time, while paying attention to service models, QA will need to focus on the team’s responsibilities regarding what they own, manage, and delegate.

Key aspects that mandate a shift in the QA approach in cloud-based environments are –

Application architecture

Earlier and to some extent even now, when it comes to legacy applications, QA primarily deals with a monolithic architecture. The onus was on understanding the functionality of the application and each component that made up the application, i.e., QA was not just black-box testing. The emergence of the cloud brought with it a shift to microservices architecture, which completely changed testing rules.

Multiple scrum teams work on various application components or modules deployed in containers and connected through APIs in a microservices-based application. The containers have a communication mechanism based on contracts. QA methodology for cloud-based applications is very different from that adopted for monolith applications and therefore requires detailed understanding.

Security, compliance, and privacy

In typical multi-cloud and hybrid cloud environments, the application is hosted in a 3rd party environment or multiple 3rd party environments. Such environments can also be geographically distributed, with data centers housing the information residing in numerous countries. Regulations that restrict data movement outside countries, service models that call for multi-region deployment, and corresponding data storage and access without impinging on regulatory norms need to be understood by QA personnel.QA practitioners also need to be aware of the data privacy rules existing across regions.

The rise of the cloud has given way to a wide range of cybersecurity issues – techniques for intercepting data and hacking sensitive data. To overcome these, QA teams need to focus on vulnerabilities of the application under test, networks, integration to the ecosystem, and third-party software deployed for complete functionality. Usage of tools to simulate Man In The Middle (MITM) attacks helps QA teams identify and overcome any sources of vulnerability through countermeasures.

Building action-oriented QA dashboards need to extend beyond depicting quality aspects to addressing security, infrastructure, compliance, and privacy.

Scalability and distributed ownership

Monolithic architectures depend on vertical scaling to address increased application loads, while in a cloud setup, this is more horizontal in nature. Needless to say that in a cloud-based architecture, there is no limitation to application scaling. Performance testing in a cloud architecture need not consider aspects like breakpoint testing since they can scale indefinitely.

With SaaS-based models, the QA team needs to be mindful that the organization may own some components that require testing. Other components that require testing may be outsourced to other providers, and some of these providers may include cloud providers. The combination of on-premise components and others on the cloud by the SaaS provider makes QA complicated.

Reliability and Stability

This entirely depends on the needs of the organization. An Amazon that deploys 100,000 times a day – features and updates of its application hosted in cloud vis-a-vis an aircraft manufacturer that ensures the complete update of its application before its aircraft is in the air, have diverse requirements for reliability stability. Ideally, testing done for reliability should uncover four categories – what we are aware of and understand, what we are aware of but do not understand, what we understand but are not aware of, and what we neither understand nor are we aware of.

Initiatives like chaos testing aim to uncover these streams by randomly introducing failures through automated testing and scripting and seeing how the application reacts/sustains in this scenario.

QA needs to address the below in a hybrid cloud setup are –

  • What to do when one cloud provider goes down
  • How can the load be managed
  • What happens to disaster recovery sites
  • How does it react when downtime happens
  • How to ensure high availability of application

Changes in organization structure

Cloud-based architecture calls for development through pizza teams, smaller teams fed by one or two pizzas, in common parlance. These micro product teams have testing embedded in them, translating into a shift from QA to Quality Engineering (QE). The tester in the team is responsible for engineering quality by building automation scripts earlier in the cycle, managing performance testing strategies, and understanding how things get impacted in a cloud setup. Further, there is also increased adoption of collaboration through virtual teams, leading to a reduction in cross-functional QA teams.

Tool and platform landscape

A rapidly evolving tool landscape is the final hurdle that the QA practitioner must overcome to test a cloud-based application. The challenge becomes orchestrating superior testing strategies by using the right tools and the correct version of tools. Quick learning ability to keep up with this landscape is paramount. An open mindset to adopt the right toolset for the application is needed rather than an approach steeped with blinders towards toolsets prevailing in the organization.

In conclusion, the QA or QE team behaves like an extension of customer organization since it owns the mandate for ensuring the launch of quality products to market. The response times in a cloud-based environment are highly demanding since the launch time for product releases keeps shrinking on account of demands from end customers and competition. QA strategies for cloud-based environments need to keep pace with the rapid evolution and shift in the development mindset.

Further, the periodicity of application updates has also radically changed, from a 6-month upgrade in a monolith application to feature releases that happen daily, if not hourly. This shrinking periodicity translates into an exponential increase in the frequency of test cycles, leading to a shift-left strategy and testing done in earlier stages of the development lifecycle for QA optimization. Upskilling is also now a mandate given that the tester needs to know APIs, containers, and testing strategies that apply to contract-based components compared to pure functionality-based testing techniques.

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Fundamentals of microservices architecture testing

The importance of microservices architecture testing

Increased adoption of digital has pushed the need for speed to the forefront. The need to conceptualize, develop, launch new products and iterate to make them better, much ahead of the competition and gain customer mindshare, has become the critical driver of growth. Adoption of agile principles or movement towards scrum teams for increased agility are all steps in this direction. Disruptive changes have also taken place on the application front with the 3-tier architecture of the late 90s and subsequent 2 tier monolithic architecture giving way to one that is based on microservices.

Having a single codebase made a monolithic architecture less risky but slow to adopt changes, the exact opposite of a services-based architecture. Microservices architecture makes it easier for multiple development teams to make changes to the codebase in parallel. By transforming an application into a distributed set of services that are highly independent, yet interdependent, provides the ability to create new services/functionalities and modify services without impacting the overall application. These changes can be achieved by teams cutting across geographies or locations and makes it easier for them to understand functional modules rather than the humongous application codebase. However, the highly distributed nature of services also gives them a heightened ability to fail.

Breaking it down – Testing strategies in a microservice architecture

At the core, a microservices architecture comprises of 3 layers – a REST layer that allows the service to expose APIs, the database layer, and the service layer. A robust testing strategy needs to cover all these layers and ensure that issues are not leaked to production. The further an issue moves across stages, the impact increases on account of multiple teams getting affected. Hence the test plan must cover multiple types of testing like service testing, subsystem testing, client acceptance testing, performance testing, etc. Subsequent paragraphs outline key aspects of service level testing and integration testing in a microservices architecture-based application landscape.

In service level testing, each service forming a part of the application architecture needs to be validated. Each service has dependencies on other services and transmits information to others based on need. In a monolith architecture, since connections are being established from one class to the other within the same Java Virtual machine (JVM), chances of failure are far lower. However, in a services architecture, these are distributed, driving the need for network calls to access other services and makes it more complex.

Functional Validation: The primary goal in services testing is the functionality validation of a service. Key to this is the need to understand all events the service handles through both internal as well as external APIs. At times this calls for simulating certain events to ensure that they are being handled properly by the service. Collaboration with the development team is key to understand incoming events being handled by the service as part of its functionality. A key element of functional validation – API contract testing, tests the request and response payload along with a host of areas like pagination and sorting behaviors, metadata, etc.

Compatibility: Another important aspect is recognizing and negating backward compatibility issues. This happens during the launch of a changed version of the service that breaks existing clients running in production. Changes that happen to API contracts need to be evaluated in detail to understand if they are mandatory and capable of breaking clients in production. An addition of a new attribute or a parameter may not classify as a breaking change; however, changes to response payload, behavior, error codes, or datatypes have the ability to break. A change in value typically changes the logic behind it as well. They need to be uncovered much earlier in the service testing lifecycle.

Dependencies: Another aspect of focus is external dependencies, where one would test both incoming as well as outgoing API calls. Since these are heavily dependent on the availability of other services and hence other teams, there is a strong need to obviate dependency through the usage of mocks. Having conversations with developers and getting them to insert mocks while creating individual services will enable testing dependencies without waiting for the service to be available. It is imperative to make sure the mocks are easily configurable without needing access to the codebase. Usage of mocks also drives ease in automation giving teams the ability to run independently with no configuration.

Understanding Microservices Architecture Testing

Once each service is tested for its functionality, the next step is to move onto validate how the various collaborating services work together end to end. Known as subsystem testing or integration testing, it tests the whole functionality exposed together. Understanding the architecture or application blueprint by discussions with the development team is paramount in this stage. Further, there is a strong need to use real services deployed in the integration environment rather than mocks used for external dependencies.

As part of integration testing, there is a need to validate if the services are wired very closely and talking to each other. The event stream and inter-service API calls need to be configured properly so inter-service communication channels are proper. If the service functionality level testing is proper, the chances of finding errors are minimal in this stage, since the required mocks created in the functionality testing stage would have ensured that the services function properly.

Looking in-depth, we find that the testing strategies in a microservices architecture are not extremely different from those adopted for a monolith application architecture. The fundamental difference comes in the way the interdependencies and communication between multiple services forming a part of the larger application are tested to ensure that the application as a whole function in line with expectations.

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.

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QA outsourcing in the World of DevOps – Best Practices for Dispersed (Distributed) QA Teams

DevOps is the preferred methodology for software development and release, with collaborating teams oriented towards faster delivery cycles augmented by early feedback. QA is a critical binding thread of DevOps practice, with early inclusion at the story definition stage. Adoption of a distributed model of QA and QA outsourcing had earlier been bumpy, however, the pandemic has evened out the rough edges.

Why QA outsourcing is good for business

The underlying principle which drives DevOps is collaboration. With outsourced QA being expedited through teams distributed across geographies and locations, a plethora of 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.

As with everything in life, DevOps needs a balanced approach, 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 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; good automation skills (not necessarily in the same person). In addition, specialist skills related to performance, security, 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. As per a 451 research survey, 39% of respondents juggle 11 to 30 tools so as to keep an eye on their application infrastructure and cloud environment; 8% are even 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 towards the tool mix, ideally by influencing the team to adopt a common set of tools instead of making it mandatory.

Ensure a robust CI/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 identification of environment configurations. These can ultimately translate into failed tests and thereby failed delivery/deployment. A well-defined automated process ensures continuous deployment & monitoring throughout the lifecycle of an application, from integration and testing phases through to release & 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 fail or lack of infra support can hamper the productivity of distributed teams. When strengthened by remote alerts and 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 & deployment practices, as well as establishing a workflow for defect/issue management, are paramount in ensuring the effectiveness of distributed DevOps. 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 key 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. Recent research from 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 show that 63 percent start to test only after a new build and code is being developed. Just 40 percent test upon each code change or at the start of new software.

Devote equal attention to both manual and 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 with improving coverage for repeatable tasks. Planning for both during your early sprint planning meetings is important. In most cases, automation is usually given step-motherly treatment and falls at the wayside due to scope creep and repeated testing due to defects.

A 2019 state of testing report, shows that only 25 percent of respondents claimed they have more than 50 percent of their functional tests automated. So, the ideal approach would be to separate the two sets of activities and ensure that they both get equal attention from their own set of specialists.

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. In the 2020 DevSecOps Community Survey, 55 percent of respondents deploy at least once per week, and 18 percent claim multiple daily deployments. But when it comes to security, 45 percent of the survey’s respondents 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 the 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

In order 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. It is heartening to note that the recent pandemic situation has revealed a positive trend in terms of better acceptance of these practices. 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 responsible testing practices put process before convenience to delight stakeholders with an impressive industry rivaled Defect Escape Ratio or DER of 0.2.

Test our abilities. Contact us today.

Put The ‘Q’ Within Your DevOps

The recent industry report estimated worldwide software failure costs to be USD 1.1 Trillion. A 2018 study by the Consortium for IT Software Quality maintained that for the US alone, the cost of defective software was USD 2.84 Trillion. These relative costs of fixing errors post a software release is unarguably higher than if they were uncovered during the design phase.

The 2019 Accelerate State of DevOps report maintains, “DevOps will eventually be the standard way of software development and operations.”  This is indeed true as enterprises acknowledge three factors: increased demand for superior quality software, faster product launches, and better value for tech with optimized software delivery performance. However, in today’s competitive landscape, is this enough to succeed?

Enterprises need something extra—the strategic integration of QA (Quality Assurance) with DevOps. While DevOps brings speed, innovation, and agility, its success lies in adopting the right QA strategy.

Devising the optimal QA strategy – DevOps

The success of Dev-Q-Ops depends on a robust QA strategy and essential best practices to boost rapid development and deployment of DevOps applications.

Earlier, the interaction between developers and testers was minimal, and both groups relied largely on their interpretation of the written / implied requirements without largely validating their understanding amongst themselves. Consequently, this led to too many back and forth arguments, counter-arguments that compromised, not just the quality, but the speed of product deployment too.

Today, most good DevOps implementations include strong interactions between developers, rigorous, in-built testing that comprehensively covers every level of the testing pyramid–from robust unit tests and contracts to API tests and functional end-to-end tests. However, the shifting of lines between what is ‘tested’ by the testers and what is automated by the developers often blurs the test strategies and approaches; thereby according a false sense of good test coverage.

Testing, both automated and manual, are continuous processes that remain active throughout the software development cycles. A definite change in mentalities is required to adopt continuous testing and continuous delivery. The Dev-Q-Ops culture is expected to lay the foundations for this and serve as the much-needed value add to your business.

It is then imperative to introduce a balance and adopt a QA strategy that not only ensures the right coverage and intent of testing, but also leverage automation to the maximum extent. The QA strategy should always be assessed on whether it helps attain vital DevOps metrics. Some examples of how the metrics can be effectively improved are:

  • Lead Time for Changes, where for example, the approach is on early identification of defects through testing early; leveraging the test pyramid, and undertaking improved impact analysis leading to better identification of ‘necessary’ coverage.
  • Deployment Frequency through facilitating the right automation spread throughout the test pyramid, deploying improved test environment and test data management and initiating parallel testing through rapid environment deployments and teardowns.
  • Time to Restore Services through shared monitoring of operational parameters and ensuring the ability to narrow down on change and impact, and thus regression, by leveraging AI.
  • Change Failure Rate by ensuring for example, risk identification, customer experience, and touchpoint testing and monitoring customer feedback and usage.

Effective execution of Dev-Q-Ops also enables Continuous Testing (CT) to easily zero-in on risks, resolve them, offer feedback and enhance quality.

Therein lies the importance of a structured QA strategy. It not only lays the foundations for a consistent approach toward superior quality but also enhances product knowledge while alerting enterprises to questions that would otherwise have remained unanswered. So, to release high-quality products without expensive rollbacks or staging, it is imperative to add the ‘Q’ to your DevOps.

In conclusion, new-age applications are complex. While DevOps can quicken their rollout, they may fail if not bolstered by a robust QA strategy. QA is integral to the DevOps process and without it continuous development and delivery are inconceivable.

Five Business Benefits of On-Demand Testing

Constantly shifting economic conditions has resulted in businesses tightening their IT budgets to control costs and remain competitive. However, while budgets are limited, expectations from IT managers are only growing larger. Most companies today have an online presence, and they need to frequently upgrade and innovate their offerings to stay competitive. This has led to new features, apps, and products being unleashed at a rapid space. There is also an uncompromising world of usability that requires released products and apps to be fault-free. However, the bottom line is, budgets remain controlled.

On-demand testing or Testing as a Service (TaaS) is a realistic option for stringent budgets and tight deadlines. Reliable service providers, who offer on-demand testing, have the capabilities for testing in cloud-based or on-premise environments. More often than not, these providers have a wide array of tools, assets, frameworks, and test environments.

End-to-end testing services that you need on on-demand basis.

On-demand testing is offered by companies that are confident of taking on the responsibility of transferred ownership. For QA and IT managers, the risks attached to testing and the costs for tools can be assigned to service providers thereby immediately diminishing both risk and added expenditures.

Unlike other services, on-demand testing is demanding in its expectations. Those offering this service cannot afford to escape, bugs, slipped deadlines, and, therefore, the advantages far outweigh the effort involved in sourcing the right partner.

Some of the benefits of On-Demand Testing are:

1. As costs are negotiated and finalized with the partner, the probability of unexpected expenses is brought down considerably. There is a commitment agreed upon and that helps in better budget allocation. There are instances where clients have experienced over 50 percent savings in costs. However, the savings are dependent on the choice of the service provider.

2. Dynamic and scalable testing requirements benefit from on-demand testing, where the partner’s team can depute several test engineers on to the job, reducing testing time drastically. For example, imagine a small number of 3-5 in house engineers who are caught up in multiple projects, to a dedicated team of any number of test engineers focused on a single project. The advantage in terms of time spent can itself become a key advantage.

3. On-demand testing is especially useful for load, performance, and last-mile testing where real-life scenarios need to be created. With real-life test environments at their disposal, service providers are capable of maximizing test coverage and results in limited time frames.

4. Time-to-market can be reduced when partners are involved, as they will help to plan and schedule test cycles without any delays. In such cases, the saved time can be at least 30 percent.

5. Reliable on-demand testing service providers offer standardized infrastructure, frameworks, and pre-configured environments to ensure that configuration errors do not creep in after release.

Trigent’s SwifTest is a pay-as-you-go software testing service that is best suited to gain instant access to qualified professional software testers without any long-term contracts. Trigent will perform end-to-end functional testing of your web or mobile applications. Our service is offered on inclusive environments of mobile devices, operating systems, and browsers – to help you validate your product at a pace faster than traditional outsourced testing service. Our certified testing specialists will ensure all user functions (links, menus, buttons, etc.) are working properly on target devices and browsers. We’ll perform exploratory testing and follow your specified test steps. This Development-QA follow-the-sun model reduces project duration and increases responsiveness. You pay only for the time that you engage our QA engineers/team-as little as one day (8 hours) / a week / or a month.
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