July 2023 Summaries

Software supply chains are increasingly difficult to secure and manage because products contain numerous direct and transitive dependencies, making it challenging to identify affected systems when vulnerabilities emerge. Software Bills of Materials (SBOMs) address this by providing detailed, relationship-preserving inventories of components and dependencies, supporting vulnerability management, compliance, and transparency. Confluent began providing SBOMs for every major, minor, and patch Confluent Platform release starting with version 7.4, generating them during build and packaging stages with Trivy, CycloneDX CLI, and Dependency Track while excluding non-shipped test and development components. The SBOMs are published in CycloneDX and SPDX formats with cryptographic checksums in the Confluent Packages Repository for RPMs, community distributions, and container images. Users can inspect component inventories, determine whether products include vulnerable dependencies, and analyze SBOMs with software composition analysis tools or a Confluent-preconfigured local Dependency Track image, although its vulnerability analyzer is currently disabled. Confluent also plans to extend SBOM coverage to additional products and provide Vulnerability Exploitability Exchange advisories to clarify the practical impact of known vulnerabilities.

Confluent announced it has obtained ISO 27701:2019 certification as both a processor and controller, covering Confluent Platform, Confluent Cloud, and the assets, technologies, and processes used to deliver customer services. Issued after an independent audit by Moss Adams that reported no nonconformities or improvement opportunities, the certification indicates that Confluent’s privacy information management system meets the international ISO 27701 standard, an extension of ISO 27001 designed to support personal-data protection and alignment with privacy regulations including GDPR. Confluent states that the multiyear preparation and months-long audit assessed its privacy policies, procedures, controls, and risk-management practices. The company says the certification can help customers evaluate vendor privacy practices and support their own compliance assessments, while Confluent Cloud also provides controls such as encryption, role-based access, configurable data retention, stream governance, multizone replication, and auditing features.

Confluent's event streaming platform was adopted by ACERTUS to integrate data from its multiple databases in real-time, enabling the development of microservices such as real-time order notifications. Prior to adopting Confluent, ACERTUS relied on batch processing and manual processes, which were inefficient and error-prone. The adoption of Confluent's event streaming platform allowed ACERTUS to build a centralized data warehouse and integrate its databases in real-time, resulting in improved customer experience, operational efficiencies, and reduced costs. With Confluent, ACERTUS was able to deploy microservices faster and use AI to analyze customer needs and find a good price for cars in real time.

Richard Nwankwo, Confluent’s Global Cloud SDR Manager, describes joining the company as an opportunity to help build an experimental Cloud SDR team that combined technical expertise with traditional sales development skills. With a psychology degree, self-taught software engineering experience, and tech sales training, he became the team’s second hire before moving into management. His team supports new Confluent Cloud users by helping them overcome obstacles, understand product capabilities, and adopt valuable features within their streaming architectures. Nwankwo’s work includes reviewing performance metrics, coaching representatives, advancing strategic projects, and collaborating across teams, and he characterizes Confluent’s culture as strongly collaborative under its #OneTeam value. He also highlights the company’s smart, humble, and empathetic employees while advocating for broader communal career-development opportunities, such as the communication training he has received through Confluent’s Toastmasters club.

The text discusses when and why it might be necessary to set up additional Apache Kafka clusters, despite the capability of a typical five-to-six node Kafka cluster to handle large volumes of data efficiently. A single cluster can manage up to 200,000 partitions, but high-end infrastructure can push this limit. The reasons for deploying multiple clusters include compliance requirements, geographic distribution, disaster recovery, and independent scaling for different business lines. While multiple clusters may introduce integration challenges, a single cluster offers advantages like simpler event correlation, cost efficiency, and reduced operational complexity. Confluent Cloud and tools like Confluent ksqlDB, KStreams, and Apache Flink enhance Kafka's data streaming capabilities, enabling real-time business insights by processing data in motion. The text also highlights best practices for federated service governance for large Kafka deployments, emphasizing security, capacity management, and self-service operations to optimize Kafka's use as a central data platform.

Kafka Summit London 2023 made more than 60 recorded sessions available online and highlighted its audience-rated top 10 talks, which expanded to 14 sessions because of several ties. The selections focused heavily on Apache Kafka and Kafka Streams operational and architectural topics, including decomposing monoliths into microservices, using flamegraphs for performance analysis, introducing event streaming into legacy environments, managing Kafka Connect with kcctl, and running high-throughput financial applications. Other highly rated sessions covered cloud performance and cost optimization, troubleshooting Kubernetes memory failures, speeding Kafka Streams state restoration, migrating between Kafka platforms, creating custom state stores, and automatically restarting unhealthy Kafka consumers. The top three included an Xbox-data demonstration of Kafka Connect and Streams, an explanation of versioned state stores and temporal joins introduced through KIP-889, and a detailed walkthrough of the Kafka producer request lifecycle, including relevant configurations and monitoring metrics. The post encourages viewers to explore the full conference catalog and follow future streaming events such as Current 2023 and Kafka Summit London 2024.

The Connect with Confluent (CwC) partner program is designed to enhance the global data streaming ecosystem by allowing technology partners to integrate Confluent directly into their platforms, providing a fast path to support end-to-end real-time use cases. As enterprises increasingly demand real-time data access for improved customer experiences, the program offers partners access to Confluent’s extensive data stream network, which processes over an exabyte of data annually, as well as expert resources across engineering, marketing, and sales to maximize integration and consumption. The program addresses the challenges of modular application development where critical business data is often dispersed across disconnected systems by facilitating low-latency data movement without the costs and complexities associated with traditional cloud storage. Through partnerships with Confluent, companies can leverage a cloud-native data streaming platform that offers built-in stream processing, governance, and security, enabling them to rapidly deploy new use cases securely and reliably across multiple environments. This collaboration not only enhances customer innovation but also accelerates market adoption and expands sales opportunities by offering a superior experience in managing real-time data streams.

The text discusses how data streaming with Apache Kafka® can support the distribution of real-time data for AI applications. It highlights that effective AI requires continuous learning and adaptation through continuous data ingestion, which is enabled by data streaming. Confluent, powered by Apache Kafka®, offers a massive ecosystem of connectors to tap into existing data stores and curate them for consumption by AI tools. Data streaming provides AI applications with the ability to perform continuous training on data streams, efficient and constant data synchronization from source systems to machine learning platforms, real-time application of AI models, and access to high volume data processing. The text also emphasizes the importance of democratizing data across organizations to enable AI teams to find and tap into data sets in a frictionless manner without setting up point-to-point integrations. Additionally, it mentions that Confluent's data streaming architecture is deployed with role-based access control (RBAC) and attribute-based access control (ABAC) at a granular level to ensure secure and trusted access to data. The text concludes by encouraging readers to reach out to a Confluent expert for more information on how to securely feed AI systems with data.

Ivan Cahuana describes his progression at Confluent from initially being rejected for an SDR role in 2020 to becoming an Account Executive on the Digital Native and Growth Businesses team. After seeking interview feedback, improving his skills through a boot camp, and reapplying, he joined as the company’s first Commercial SDR, supporting Central, Canadian, and Latin American markets before advancing to an AE role in 2022 and earning a President’s Club award. He was drawn to Confluent’s Kafka-based technology, growth prospects, exposure to engineering leaders, and supportive sales leadership. His work involves customer support, prospecting, meetings, mentoring, and ongoing product learning, while remote collaboration relies on Slack and regular video check-ins. Cahuana characterizes Confluent’s culture as diverse, flexible, and fast-paced, with remote-first work and in-person events such as Growth Kick-Off helping employees build cross-functional connections.

Ankit Garg, a Senior Software Engineer on Confluent’s Trust, Security, and Reliability organization, joined the company to work on scalable, resilient systems and collaborate with engineers who shared his interest in Apache Kafka and cloud infrastructure. Based in Bengaluru, he works on the Audit Logs team, which generates and delivers cloud audit records that help customers track interactions with Confluent Cloud clusters and the control plane. His current work includes replacing static API keys with dynamic access tokens through a secure internal vault, private network connections, Kubernetes secrets, and automated token rotation, reducing the need for disruptive cluster rolls. Garg’s daily responsibilities include code reviews, technical guidance, support requests, and cross-team work on ambiguous security, quality, and customer-experience challenges. He describes Confluent’s culture as collaborative and responsive, and values its remote-first approach for supporting work-life balance, while hoping the company further simplifies its cloud product through improved guidance, tutorials, and more unified user interactions.