Matthew Miller

NAB Collaborates with Databricks to Revolutionize SIEM Design

Matthew Miller on March 30, 2026

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Quick Read

NAB collaborates with Databricks to jointly develop a new SIEM solution, Lakewatch.
Lakewatch is presently in a private preview stage, with no public release timeline announced.
NAB intends to consolidate more than 30TB of daily security data with larger datasets to enhance cybersecurity.
This partnership signifies Databricks’ entry into the security market.
The platform is set to integrate data from 15 security vendors and provide customized security agents.

NAB Teams Up with Databricks for SIEM Development

National Australia Bank (NAB) has made a pivotal advancement in the cybersecurity field as one of the five design partners for Databricks’ new security information and event management (SIEM) platform, Lakewatch. This partnership denotes Databricks’ first step into the security industry, generating significant excitement within the technology community.

Lakewatch: A New Era in Security

Lakewatch is now in a “private preview” stage, with details regarding its public launch still undisclosed. NAB’s chief security officer, Sandro Bucchianeri, emphasized the bank’s daily processing of over 30TB of security data, conveying a goal to merge these signals with larger enterprise datasets to enhance its cybersecurity framework.

Utilizing Current Infrastructure

NAB already employs Databricks on AWS as a fundamental aspect of its enterprise data platform, Ada. The existing partnership between NAB and Databricks sparked conversations about extending Databricks technology into security solutions, which led to NAB’s role in the design of Lakewatch.

The Future of Cybersecurity

Bucchianeri expressed enthusiasm for the collaboration, mentioning, “Collaborating with Databricks to shape a product tailored to the needs of cyber defenders moving forward … is exciting for us.” The platform is designed to address both present and future security requirements.

Integration and Advancement

Databricks has disclosed that Lakewatch will facilitate data integration from 15 security vendors, offering an “agentic” SIEM where customized security agents can be created for incident detection and resolution. This adaptability is a crucial advantage for organizations seeking bespoke security solutions.

Conclusion

NAB’s alliance with Databricks to create Lakewatch represents a significant development in the cybersecurity landscape. By harnessing Databricks’ technological expertise and NAB’s substantial data capabilities, this collaboration promises to deliver a powerful SIEM platform. With its ability to integrate extensive security data and provide customizable security agents, Lakewatch stands as a promising asset for future cybersecurity efforts.

Q&A Section

Q: What is Lakewatch?

A: Lakewatch is an emerging security information and event management (SIEM) platform under development by Databricks, with NAB serving as a primary design partner.

Q: Why is NAB participating in this initiative?

A: NAB aims to unify its vast daily security data with larger datasets to strengthen its cybersecurity capabilities, utilizing its existing partnership with Databricks.

Q: What distinguishes Lakewatch from other SIEM offerings?

A: Lakewatch is promoted as an “agentic” SIEM, permitting the creation of custom security agents for incident detection and response, offering enhanced flexibility in security operations.

Q: When will Lakewatch be publicly available?

A: Lakewatch is currently in a private preview phase, with no definitive date established for its general release.

Q: How many other organizations are participating in the co-development of Lakewatch?

A: NAB is among five design partners; however, the names of the other four have not been revealed.

Q: Does Databricks have prior experience in the security domain?

A: Lakewatch signifies Databricks’ initial entry into the security market, broadening its scope from data management to cybersecurity.

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Telstra Upgrades Event Streaming through Flink Integration

Matthew Miller on March 28, 2026

Telstra’s Latest Integration: A Major Advancement in Event Streaming Technology

Telstra will incorporate Apache Flink into its current Kafka-powered event streaming framework.
This integration is designed to bolster network observability and improve customer service standards.
Flink’s rapid in-memory processing capabilities will facilitate real-time data evaluation.
Managed services for both Flink and Kafka will be provided by Confluent.
Event streaming is essential for AI and analytics in Telstra’s activities.

The Integration of Apache Flink

Telstra is preparing to improve its event-oriented network observation framework, which has been in place for four years, by integrating the Apache Flink data processing engine. This integration, slated to commence in the upcoming months, aims to enhance Telstra’s capacity to process and analyze streaming data in real-time.

Utilizing Managed Services from Confluent

Telstra plans to combine Flink with its current Kafka-focused event stream processing functionalities, both of which will be utilized through managed services offered by Confluent. This strategic initiative is anticipated to increase the speed and efficiency of data processing, enabling Telstra to swiftly tackle network challenges.

Improving Network Observability

With Flink’s integration, Telstra intends to monitor significant changes in its network, facilitating early problem identification and faster restoration of complete services. The enhanced observability will ensure that customers receive the promised service levels, leading to greater overall satisfaction.

Enhancing Product Development and Customer Benefit

Telstra leverages network data to guide service innovation and ensure customers achieve the expected value from performance-related service enhancements. By investigating trends and customer demands, Telstra can create customized products, improving the selections available on its network.

Strengthening AI and Analytics Initiatives

The addition of Flink is also perceived as a move towards fortifying Telstra’s AI and analytics capacities. High-quality, accessible data from the network is essential for informed decision-making, vital for progressing AI initiatives.

Summary

Telstra’s incorporation of Apache Flink into its existing Kafka-based platform signifies a notable improvement in its event streaming proficiencies. This action is poised to enhance network observability, stimulate product development, and bolster AI and analytics endeavors, ultimately improving service for customers.

Q&A

Q: What is the primary goal of integrating Apache Flink into Telstra’s platform?

A: The primary goal is to improve real-time data processing and analytical capabilities, thereby enhancing network observability and customer service standards.

Q: In what way does Flink enhance Telstra’s event streaming proficiencies?

A: Flink’s in-memory processing speeds facilitate quicker data analysis, enabling earlier problem identification and faster service restoration.

Q: What is Confluent’s role in this integration?

A: Confluent supplies managed services for both Apache Flink and Kafka, aiding the integration and functioning of these systems.

Q: How will this integration influence Telstra’s customers?

A: Customers can anticipate enhanced service standards, as improved observability enables Telstra to address network problems more efficiently and quickly.

Q: Why is data vital for Telstra’s AI and analytics projects?

A: High-quality, available data is crucial for informed decision-making, laying the groundwork for effective AI and analytics initiatives.

Q: What advantages does event-driven observability provide for Telstra?

A: It empowers Telstra to monitor significant network changes, leading to quicker problem detection and resolution, ensuring superior service delivery.