In this latest installment of Channel Insider: Partner POV, host Katie Bavoso sits with Ozan Unlu, CEO and founder of Edge Delta, to discuss how his startup is leveraging expertise and AI to create a next-generation observability platform.
This conversation delves into the explosive growth of data and the innovative solutions Edge Delta offers to manage and analyze this data efficiently.
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The genesis of Edge Delta
Unlu begins by explaining the origins of Edge Delta, which entered the market over four years ago. He shares his extensive experience in the observability space, noting that data volumes have increased significantly over the years. “When I think about 20 years ago, the data volumes that were being created compared to today were obviously minuscule,” Unlu says, highlighting the exponential growth in machine data, which includes logs, metrics, events, and traces.
He explains that companies that used to generate 5-10GB of data per day are now producing terabytes, some even reaching petabytes, worth of data. This growth demands innovative solutions to handle the increasing complexity of data. Unlu emphasizes the need for a brand-new architecture to manage this data explosion, focusing on distributed preprocessing and pre-aggregation of data sets.
The driving forces behind data explosion
Bavoso inquires about the reasons behind the data explosion. Unlu attributes it to the changing architectures and the rise of cloud-based infrastructures. He reflects on his time at Microsoft, where access to virtual and physical resources was a privilege. Today, companies born in the cloud, often called “cloud babies,” can quickly scale their infrastructure, contributing to the vast amounts of data generated.
Unlu clarifies that combining cloud technologies and containerization tools like Kubernetes results in multiple components creating data simultaneously. This multi-vector data growth requires new strategies to manage and analyze it all.
The explosion of data
Unlu begins by discussing the dramatic increase in company data over the past few years. This exponential growth necessitates a new approach to data architecture.
He attributes the surge in data to changing architectures and technological advancements, such as cloud computing and containerization. Today, even small startups can leverage powerful cloud-based tools and technologies like Kubernetes, leading to an unprecedented increase in data generation from multiple sources.
Traditional databases, data stores, and streaming platforms like Kafka are no longer sufficient. He asks, “How do you have distributed preprocessing and pre-aggregation of your data sets? And also, how do you use pipelines to fully understand and control your dataset?” This is where Edge Delta steps in, providing an observability platform that starts with observable pipelines and ends with the ability to curate data for continuous AI-driven insights.
He advises that businesses demand adaptable and forward-thinking data management strategies. The explosive growth in data requires solutions that can manage and derive value from the information being generated. Companies must adopt flexible and scalable data processing methods to keep up with this rapid expansion.
Edge Delta’s approach to observability
Unlu describes Edge Delta as a pioneer in intelligent pipelines, offering unmatched flexibility and scalability. The company’s approach focuses on distributed preprocessing and data pre-aggregation, allowing for efficient and comprehensive data control. This methodology ensures that even massive data sets can be managed effectively, providing continuous insights and inferencing capabilities.
Edge Delta distinguishes itself in the observability space through its approach to data pipelines. “We are the original player in this space doing intelligent pipelines that are the most flexible and scalable,” states Unlu.
Edge Delta’s focus on edge computing and observable pipelines sets it apart, starting with data at the edge and enabling detailed, continuous analysis.
Unlu highlights the importance of effectively managing AI and data processing costs. He notes that efficient data curation, preprocessing, and pre-aggregation are vital in an industry where massive data sets are the norm. This approach ensures that only valuable data is processed, optimizing the use of AI for continuous inferencing.
Real-world applications of AI in Edge Delta
Bavoso probes deeper into how AI is integrated into Edge Delta’s products. Unlu introduces OnCall AI, their latest AI feature designed to enhance observability. This feature acts as a first responder to alerts, analyzes issues, and reduces the need for manual intervention.
“When there’s an issue, even if it’s three in the morning, the person has to wake up, open their laptop, and as their eyes are adjusting, they’re trying to figure out what’s going on with the infrastructure,” Unlu explains, illustrating the typical SRE’s or DevOps engineer’s reality.
Unlu emphasizes the practical impact of OnCall AI in reducing the workload and improving the response time for IT professionals. By automating initial diagnostics, OnCall AI allows teams to address issues more efficiently and maintain system reliability, reducing the burden on human resources.
Collaborations with hyperscalers
The conversation shifts to Edge Delta’s collaborations with major cloud providers. Unlu, drawing from his background as a software developer on the Azure team, discusses their partnerships with the big three hyperscalers: Azure, AWS, and GCP. He explains that Edge Delta maintains a cloud-agnostic stance to support their customers’ multi-cloud strategies, ensuring their solutions are available across various platforms.
By staying cloud-agnostic, Edge Delta can cater to diverse customer needs and ensure scalable solutions.
Tune in to the video or podcast above for more insights from Katie Bavoso and Edge Delta CEO Ozan Unlu — and be sure to like and subscribe for future interviews with solution providers and thought leaders, plus special episodes and opportunities!
