2022: A Year of Significant QA Transformation at LoginRadius

In 2022 alone, LoginRadius CIAM platform has undergone major changes as we focused on re-engineering our platform to deliver cutting-edge performance, scalability, and throughput — which we needed to deliver for our customers who had large bases of end users for whom seamless experiences supported by lightning performance was mostly non-negotiable.

The changes and upgrades in 2022 were needed due to the challenges we faced in 2019 and later; for which, by 2021, we did root cause analysis, thorough research, and strategically planned high-quality upgrades.

In this process, we needed to transform our QA systems, processes, and workflows.

I wrote earlier about this engineering transformation at LoginRadius: 2022 - A Year of Engineering Resilience at LoginRadius.

Here, I write about how we transformed QA to support engineering efforts and deliver a more robust and efficient platform free of production issues for our customers.

Reworking Test Coverage

While doing the root cause analysis in 2021, we also identified that work on test coverage was required to meet the increased demand and ultimately lead to better user experience and customer satisfaction. Additionally, we planned test coverage extension to ensure that APIs movement from .Net Core to Go Lang does not introduce regressions.

In phase one, we enhanced test coverage across all LoginRadius components, including HPA, IDX, and Admin-Console. And we then added new test cases for the identified gaps and new scenarios. This improvement provided optimal test coverage and helped us reduce the risk of issue leakage.

Advancing Automation

Automation testing has always been part of quality assurance at LoginRadius. However, increased demand and the need for faster release cycles called for the advancement of existing automation capabilities.

We made notable improvements in automating testing for customers' sites and various product components like webhooks, auth APIs, and audit logs for HPA APIs. Also, to remarkably reduce manual efforts and cumbersome maintenance, we migrated customer site automation from Katalon Studio to Cucumber BDD. This advancement enhanced the automation capabilities and reduced the product’s release time.

Executing Parallel Pipeline

Earlier, our test cases ran in parallel, but we executed jobs in CI/CD pipelines sequentially. Thus, the time involved in release verification was higher.

In the year 2022, we added more runners and separate apps for every job in test suites and reduced CI/CD pipeline execution time by more than 50%.  This execution improved our testing efficiency and helped us deliver faster product releases.

Streamlining Test Case Management

While planning and executing the above strategies, we realized that existing test case management and cross-browser testing solutions required an upgrade for better performance and scalability. To fulfill these requirements, we opted for our new tools - Testmo and LambdaTest after extensive research and POCs.

These changes have brought several benefits to the product, including more effective test case management that streamlines the overall testing process and enables geo-location execution for test scripts.

The Results

All of our continuous efforts, strategic rethinking, gap-finding analysis, and deeper involvement in optimizing the quality assurance of our platform have resulted in the following:

• Significant reduction in the number of product PIs in 2022 compared to the previous years. In-depth planning, brainstorming, and gap findings have contributed to the product PI graph trending close to zero.
• Notable reduction in issue leakage risk with better test coverage ensuring through testing of all LoginRadius components.
• Remarkable reduction in product release time, regression, and overall QA verification time led to the faster and more efficient delivery of product releases.

In Conclusion

In conclusion, 2022 was a year of significant transformation in quality assurance at LoginRadius. These changes have helped to deliver a more robust and efficient platform for customers, ultimately contributing to their satisfaction and success.

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Originally published at LinkedIn

2022: A Year of Significant QA Transformation at LoginRadius

In 2022 alone, LoginRadius CIAM platform has undergone major changes as we focused on re-engineering our platform to deliver cutting-edge performance, scalability, and throughput — which we needed to deliver for our customers who had large bases of end users for whom seamless experiences supported b

Deepak Gupta

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Can AI Write an Emotional Poem or Song?

The question of whether Artificial Intelligence (AI) can write an emotional poem or song is a complex one. AI has become increasingly influential in recent years and can perform various tasks, but can it create something as complex and personal as a poem or song? AI can certainly create lyrics and musical notes that fit together to create something resembling a song, but can it create something truly emotional?

The answer is yes, but only to a certain degree. While AI can generate words and musical notes that fit together to produce something resembling a poem or song, it cannot create something that conveys genuine emotion. For example, a computer may generate a poem with a specific structure and a certain rhythm but cannot capture the emotion and feel behind the words. AI can also generate musical notes that sound like a song but cannot create the emotion and feeling behind the notes.

For AI to create a genuinely emotional poem or song, it would need to understand and interpret the nuances of human emotion. This is a difficult task, as AI does not have the same level of understanding of the complexities of human emotion that we do. AI may be able to generate words and music that fit together to create something resembling a poem or song, but it will not convey the same level of emotion as a human can.

Can AI Write an Emotional Poem or Song?

Humans have been writing poems and songs for centuries, but could artificial intelligence (AI) ever be capable of producing something that has an emotional quality? This article will explore the potential of AI to write a poem or song with a humorous tone.

The Possibilities of AI

AI has come a long way in recent years, and it can now perform many tasks that were once thought impossible. AI can recognize objects, understand natural language, and play complex games. So, could AI be used to write a poem or song with a humorous tone?

AI and Creative Writing

AI is not yet capable of producing creative works on its own, but it can be used to help humans in the creative process. AI can be used to generate ideas, suggest word choices, and even provide feedback on the quality of a poem or song.

AI and Humor

Humor is one of the most challenging things for AI to understand and replicate. AI can recognize jokes and other forms of humor, but it cannot produce original jokes or humorous content. However, AI can help humans creatively by suggesting words and phrases that could add humor to a poem or song.

Conclusion

AI can, however, be used to assist humans in creating emotional poems and songs. AI can be used to generate words and musical notes that fit together to create something that resembles a poem or song, and then it can be up to the human to refine the poem or song and add emotion and feeling. AI can also suggest changes to the poem or song that may make it more emotionally powerful.

In conclusion, while AI cannot create a genuinely emotional poem or song, it can be used to assist humans in creating one. AI can generate words and music that fit together, and then it is up to the human to refine the poem or song and add emotion and feeling. AI can also suggest changes to the poem or song that may make it more emotionally powerful.

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2022 - An Year of Engineering Resilience at LoginRadius

Back in 2018, our product, engineering, infrastructure, and customer teams were a happy bunch — the LoginRadius CIAM platform has evolved a lot in the previous years. It is ready to scale, serve, and support the needs of some of the biggest retail and consumer-facing brands in the world.

From 2019, the strength and capabilities of the CIAM platform enabled us to onboard some of the biggest brands we have ever worked with.

From then, things got a bit complicated — like a plot twist in your favorite story: the platform was not performing as expected in terms of scalability and latency, and it was difficult to believe we weren’t delivering up to the standards I had set for ourselves.

2020: Why LoginRadius CIAM Struggled to Deliver Cutting-Edge Performance?

From the first day we started working on LoginRadius, we knew that performance was the Achilles heel for our customers who run consumer-facing applications.

In a world where brands like Amazon, Google, and Netflix have pushed the bar for end-user experience, we wanted to enable our customers’ brands globally to deliver similar experiences to their end users, which is so fundamental to LoginRadius.

After we onboarded some of the bigger brands, special business situations and use cases caused engineering issues we had never observed before, thanks to the scale and demands of the workloads and requirements we were dealing with.

We faced performance lags in terms of scalability and latency. To address this, firstly, we launched a comprehensive root cause analysis (RCA) that surfaced sub-optimal processes and mechanisms in terms of time-to-release, automation, and legacy complexities.

The finding from the RCA has challenged our assumptions and helped us remap our priorities: No matter what, our platform has to deliver excellence for our customers of all sizes.

2021: An Year of Engineering Resolve

We are a world-class engineering team. Since its inception, engineering problems have intrigued us — in fact, that’s how LoginRadius was born.

And the time has come again to test our resolve and dedication: how do we re-engineer the LoginRadius CIAM Platform delivers a high-throughput, low-latency, and lightning-fast end-user experience?

One discussion I had strikingly comes to mind: our platform is already the strongest technological offering in the market. So, we created the strongest platform — yet that isn’t meeting our standards. If we’re going to deliver something much better, our engineering team is the one to rebuild it.

The Forrester Wave™: Customer Identity And Access Management, Q4 2020.

We initiated research and auxiliary processes to discover opportunities, analyze technologies, strategize platform re-engineering, and plan required upgrades.

In this phase, we focused and worked confidently with commitment yet cautiously. We knew, as with the stock investments corollary, past performance is not a precise indicator of future performance. Likewise, the technology world has changed so much, and our ability to unlearn, relearn, and solve complex engineering problems was put to the test.

2022: An Year of Engineering Resilience and High-Performance Outcomes

As we researched and planned a strategy to upgrade our CIAM platform, we focused on four key areas: platform architecture, underlying technologies, automation, and process improvements. For each focus area, we achieved the following outcomes.

Improving Scalability and Latency

APIs are fundamental to our CIAM platform and how we deliver core services to customers. In order to achieve breakthrough scalability and ultra-low latency, we started by focusing on upgrading the performance of our APIs.

The then-existing APIs were built with .NET Core, whose performance and infrastructure usage was not satisfactory with respect to the scale of requests. To solve this, we concluded through research that we must rebuild our APIs with Go Lang. Our lead architect Vijay Singh Shekhawat has written an excellent account of this transition: Why We Re-engineered LoginRadius APIs with Go?

In addition to the high-performance API upgrades, we made a lot of minor improvements to the platform and deprecated legacy technologies with modern, performance-focused technologies.

Optimizing Complexities in Our Processes and Platform

Previously, we employed a sequential development approach for individual components to create a specific feature. This approach often resulted in delays and hindered progress, as roadblocks or issues in any component would block each other and require multiple iterations to address missing or updated elements. This resulted in longer-than-anticipated development times and subpar quality.

However, we have now adopted a parallel development approach, where all components of a feature are developed simultaneously, and any missing or updated elements are addressed in real-time. This allowed us to release all components of a feature at the same time, ensuring greater efficiency and higher quality outcomes.

Leveraging Automation

The existing level of automation wasn’t enough for the speed at which we wanted to develop new features and address existing performance lags.

We rigorously worked on automation that resulted in 99% automation in our test cases for APIs and the LoginRadius platform, along with other minor workflows. It helped us deliver new releases and improvements faster, which also meant we could accommodate additional customer requirements on the fly within a defined scope.

The Results

All of our continuous efforts, strategic rethinking, and deeper involvement in re-engineering our platform have resulted in the following:

• Improved system stability and updates: Our customers have appreciated the upgrades in performance, latency, and throughput. And we haven’t faced reliability and performance issues so far.
• Our system throughput has generalized capabilities to serve 30k RPS (requests per second), which we can scale on-demand to 100k RPS or even much higher.
• Application startup time optimized from 120 seconds to 2 seconds — our biggest breakthrough yet in achieving superior on-demand scalability.
• We simplified system architecture complexity by 45%, making it more efficient to develop new capabilities and seamlessly accommodate special-case customer requirements.

All the engineering efforts have led to remarkable improvements in our identity platform, including increased concurrency and throughput, allowing us to quickly handle high volumes of end-user requests and traffic.

Another outcome of this re-engineering process has been a 40% reduction in infrastructure costs, showcasing our commitment to optimal engineering while delivering cutting-edge capabilities to our customers cost-efficiently.

As a testament to our progress, the latest analysis from Forrester on CIAM (Customer Identity And Access Management, Q4 2022) has reported, “[LogiRadius’s] scale of large deployments is ahead of the competition.”

In Conclusion

This transformation has resulted in numerous substantial improvements and has positively impacted our customers and their end users.

We continually strive to push the limits of technology and maintain a forward-thinking approach.

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Originally published on LinkedIn

2022 - An Year of Engineering Resilience at LoginRadius

Back in 2018, our product, engineering, infrastructure, and customer teams were a happy bunch — the LoginRadius CIAM platform has evolved a lot in the previous years. It is ready to scale, serve, and support the needs of some of the biggest retail and consumer-facing brands in the world.

An Year of Engineering Resilience at LoginRadiusDeepak Gupta

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