Buluttan, a leading provider of weather intelligence, transforms raw weather data into valuable insights for clients across various sectors, making data both an end product as well as the raw material of their SaaS offerings. With data at the core of its offerings, Buluttan faced significant challenges in scaling and optimizing its data infrastructure, primarily due to a lack of standardized process when it comes to processing data. The introduction of Bruin brought about a transformative change in the company's data-related operations, enabling rapid growth and improved efficiency.

Challenges Before Bruin

As a startup, Buluttan's data infrastructure relied on in-house tools, services, and servers to manage data pipelines. Effectively, Buluttan did not have an active data pipeline / workflow processes; instead, there were various systems that worked in isolation: a system that does data extraction, a VM that runs a dbt pipeline, manual quality checks on their data. This setup led to several issues, including slow development and deployment processes. Without a standard deployment methodology and any orchestration, the team struggled to ensure consistency and efficiency in their data and DevOps pipelines.

Some of the key challenges were:

• Slow deployment: One of the primary issues was the slow deployment processes. Without a streamlined system, deploying new features and updates was time-consuming and inefficient, hindering the company’s ability to respond quickly to market demands.
• Lack of dependencies between tasks and pipelines: Another significant challenge was the lack of support for creating dependencies between tasks and pipelines. This limitation made it difficult to build complex workflows and ensure that different components of the data pipeline interacted seamlessly.
• Limited automation abilities: Automation in pipeline management was limited, meaning many tasks had to be performed manually. This manual intervention increased the risk of errors and consumed valuable time and resources that could have been better spent on innovation and development.
• Limited quality checks: The absence of robust quality control mechanisms meant that data pipelines were prone to errors and inconsistencies, affecting the accuracy and reliability of the weather intelligence provided to clients.
• Tooling that does not work with each other: Buluttan was using dbt as the transformation tool, and they had built their own extraction setup. These components were being executed in different systems, which required a lot of effort to connect to each other. The data lineage was being lost, and not being able to ensure quality across the stack was causing a lot of issues. In addition, dbt was getting slower and slower as the number of models were growing.

These challenges collectively impeded Buluttan’s ability to scale and optimize its data operations, necessitating a more robust and comprehensive solution to streamline and enhance its data infrastructure.

“Bruin allows us to concentrate fully on our pipelines without the hassle of managing infrastructure. It simplifies our workflow, giving us more time to focus on optimizing data processes and improving overall efficiency.“

Choosing Bruin

Buluttan evaluated Bruin as a comprehensive solution to address its pain points. The platform offered a unified solution for monitoring, debugging, and development, which was a significant improvement over the fragmented tools previously used.

One of the critical factors was Bruin's unified orchestration, deployment, and secrets management. This streamlined platform integrated these essential functions, significantly reducing complexity and boosting efficiency in Buluttan's data operations. Additionally, Bruin served as a one-stop shop for monitoring, debugging, and quality control. This centralized solution replaced the need for multiple tools, making it much easier for Buluttan to maintain and manage their data pipelines effectively.

As part of the trial period, the Buluttan team deployed various workloads on Bruin, testing the abilities of the platform. This ensured that the overall capabilities of the platform matched with Buluttan’s needs, and provided an easy migration path.

• Scalable from day zero: Scalability was another crucial factor. Bruin's design allowed for seamless handling of growing data volumes and complexity, ensuring that Buluttan could continue to scale its operations without encountering performance issues
• Cost efficient: the cost efficiency of Bruin compared to maintaining multiple in-house solutions was a significant benefit, reducing operational expenses. In addition, the cost of onboarding new people as well as knowledge transfer is greatly reduced.
• Zero lock-in: Bruin's agnostic features and zero lock-in components enabled seamless and fast integration with Buluttan's existing systems. This flexibility was critical in ensuring that the transition to Bruin was smooth and did not disrupt ongoing operations.

Moreover, Bruin’s design principles and best practices encouraged the development of scalable and maintainable data pipelines, further enhancing Buluttan’s data infrastructure.

Impact of Bruin on Buluttan

The implementation of Bruin had a transformative impact on Buluttan's data operations. One of the most notable improvements was the significant enhancement in their capacity to develop new pipelines more rapidly. This newfound efficiency allowed Buluttan to scale its products to a broader customer base and introduce new product offerings at a much faster rate. The Data Engineering team, previously bogged down by infrastructure management, could now focus more on what truly mattered—the data itself. This shift not only improved team productivity but also enabled more innovative and data-centric projects.

Additionally, the efficiencies gained through Bruin allowed Buluttan to postpone the hiring of DevOps personnel. This delay in hiring not only saved costs but also allowed the company to allocate resources more strategically.

The key benefits the rollout of Bruin unlocked for Buluttan are:

• More capacity: Enhanced capacity to develop new pipelines rapidly thanks to Bruin enabled product scaling and new offerings for Buluttan. Focusing on domains instead of infra: Bruin enabled the Data Engineering team to focus more on data rather than infrastructure.
• Seamless development & deployment: Development and deployment processes became faster and more frequent, thanks to Bruin’s streamlined approach. This improvement reduced the time to market for new features and updates, keeping Buluttan competitive in the fast-paced weather intelligence industry.
• Better troubleshooting: Bruin unlocked a proactive and streamlined troubleshooting process, along with a simpler and quicker issue resolution process for Buluttan.
• More data without more people: Buluttan observed a significant increase in data pipeline size within six months, a growth rate that would have taken much longer without Bruin
• No need for DevOps: Buluttan postponed hiring of DevOps personnel for their data pipelines.

These impacts collectively underscored the transformative role Bruin played in optimizing Buluttan's data operations, driving efficiency, and supporting scalable growth.

“Bruin's product has effectively addressed all the challenges my team faced in developing, orchestrating, and monitoring our pipelines.“

Conclusion

With Bruin, Buluttan successfully overcame its data infrastructure challenges, driving rapid growth and innovation in its weather intelligence services. The comprehensive solutions provided by Bruin enabled Buluttan to enhance its data capabilities, improve operational efficiency, and scale its offerings to meet the growing demands of its clients.