As the race for innovation continues, experts have flagged that how well an enterprise is able to leverage AI will be key to its competitive advantage.
To unlock a first mover edge, speed is key. However, this is something that even the biggest tech companies are finding challenging.
Jay Parikh is leading core AI work at Microsoft and recognizes that “it’s all about speed.” Yet the sheer scale of his task, coupled with the complexity of an organization like Microsoft, means that Parikh has been battling against organizations siloes and the vast number of distinct development teams.
AI-generated code is often touted as a solution to slow development speeds and engineering productivity. However, these tools are still far from perfect. For instance, one recent evaluation of Devin, a popular AI coding tool, found that it could only complete three out of 20 programming tests.
Further, even if the industry has access to a robust and reliable AI coding assistant, it won’t significantly increase the pace of software release cycles unless we address the underlying problem with microservice architectures and batch testing.
With microservices, the software development life cycle (SDLC) often flows through a patchwork of disconnected environments. Code moves from local development to integration through preproduction setups that don’t always test in the real environment.
Every step introduces drift, maintenance overhead, and more distance from the real production environment.
This batched approach to testing and release carries enormous hidden costs. Changes can take days or even weeks to reach production, greatly extending the overall lead time. In fact, engineers forced to revisit old code can suffer productivity losses of 20% to 40% with each switch. With less ownership over the release process, engineers invest less in test quality and automation.
Overall, this causes teams to become tightly coupled by release schedules and limits the ability of engineers to drive agile innovation that’s key to business competitiveness.
Engineers often develop code in isolation, run local tests, submit a pull request and get it approved. The request is merged to the main branch, where it joins dozens of other changes waiting to be deployed.
Here, Signadot enters the picture. The company is on a mission to give engineers control over testing changes much earlier in the development lifecycle with an optimal testing platform that cuts down wait times.
Signadot’s platform streamlines the testing process, allowing developers to quickly and reliably test their code changes early in the development cycle. This approach eliminates long waits for full-scale integration, enabling faster feedback and reducing the risk of issues later on. By improving both speed and reliability, the startup is helping companies accelerate their development workflows and deliver high-quality software more efficiently.
In 2022, this innovative approach helped Signadot raise a $4 million seed round led by Redpoint Ventures, along with participation from some of the industry’s top angel investors.
To achieve faster software development loops, one of Signadot’s offerings is a Kubernetes-based platform that allows developers to test their code without any potential impact on other developers in a shared staging environment.
The company also offers AI-powered testing to catch API contract breaks before they reach production. In essence, this automates contract validation across microservice environments.
The AI model and Smart Diff technology spot meaningful API changes, filtering out false positives to help developers focus only on the most important changes – those that affect service consumers.
To illustrate further, Signadot recently worked with fintech company Brex. With over 1,000 microservices in production, Brex’s engineering team faced a common challenge that comes with distributed architectures: how to enable developers to effectively test and validate changes across interconnected services.
With the use of Preview Environments, the fintech was able to save costs through improved resource utilization, boost developer satisfaction rates and slash development cycles from 60m to immediate availability.
Signadot was co-founded by Arjun Iyer (CEO) and Anirudh Ramanathan (CTO) and was part of Y-Combinator’s Winter 2020 batch.
The two founders were motivated to solve a common challenge they experienced managing large engineering teams, and the frustrations “of having these long feedback loops and discovering issues very late really hurt our ability to ship software fast.”
The company is also looking to revolutionize testing for cloud native applications and embody the “shift left” testing philosophy to not only speed up software development times but improve cohesion for engineers.
Prior to Signadot, Iyer led Engineering and Data Science teams at AppDynamics, and has decades of experience building Cloud Native Systems. As senior director at Data Science at AppDynamics, Iyer was responsible for building a next-gen data science platform to facilitate rapid iteration and delivery of Machine Learning based features into the product.
He also helped to evangelize Data Science within the company and worked closely with their product team to unleash innovative solutions within the AIOps market segment and grow a cross-functional team of data scientists and engineers.
For Ramanathan, his journey began at IIT BHU, one of India’s premier technical institutions.
After completing his undergraduate degree, he pursued a Master’s in Computer Science at Texas A&M University. He played a leading role in developing Kubernetes, evolving it from an emerging technology into a cornerstone of modern cloud infrastructure.
Following his groundbreaking work on Kubernetes at Google, Anirudh Ramanathan shifted his focus to the rapidly evolving field of artificial intelligence. At Google, he had already made significant contributions to AI through his work on Apache Spark, a powerful platform that laid the foundation for large-scale data processing.
This work established critical infrastructure that has become integral to the development and scaling of AI technologies worldwide.
The transformation not only revolutionized how organizations deploy and scale applications, but also set a new global standard for resilience and scalability in cloud computing across various industries.
For Iyer, Ramanathan and the team at Signadot, their work is far from finished. As the software industry continues to evolve and face new challenges, they remain dedicated to expanding the horizons of what’s possible in software development.
“My goal has always been to remove the barriers to innovation,” Ramanathan said in an earlier interview.
“At Signadot, we’re just scratching the surface. I see a future where development is exponentially faster, where testing accelerates progress, and where software evolves intelligently.”
With their expertise and relentless drive for innovation, the company is well-positioned to lead the industry into this new era of efficient, collaborative, and groundbreaking software development.
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