Expanding nature of products, need for faster releases to market much ahead of 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.
- Right Partner
- Right Process
- Right Communication
- Right Outcome
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 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 onboard 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 derails 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.
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 is 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.
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.
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 skill sets 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.
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