Confluent and Carahsoft have partnered to provide a series of self-guided tours for Confluent's enterprise-ready Artificial Intelligence and Cybersecurity solutions. Similar to a live demonstration, these in-depth walkthroughs explore Confluent's wide array of use cases that can help meet you and your organization’s unique IT needs.
Learn about Confluent’s Artificial Intelligence and Cybersecurity solutions by starting a self-guided tour below or schedule time with your dedicated Confluent representative for personalized insights.
Confluent’s platform is a full-scale, open source data event streaming platform that empowers agencies to easily access, store and manage data as uninterrupted, real-time streams. Confluent delivers a fully cloud-native experience, upgrading Kafka with enterprise-grade features to boost developer productivity and achieve efficient scalability. Confluent integrates real-time and historical data into a single, centralized source of truth, facilitating the creation of modern event-driven applications, instituting a universal data pipeline that enables robust scalability, performance and accuracy for a wide range of use cases.
Real-time data (RTD) denotes information processed, consumed, and/or acted upon immediately after generation, representing a newer paradigm in data processing that alters the way agencies operate. Data streaming is the continuous flow of data as it's generated, enabling real-time processing and analysis for immediate insights. Confluent's data streaming platform, allows agencies to take event-driven use cases
Data ingestion involves the extraction, transformation, and loading of data into a target system to enable further insights and analysis. Essentially, data ingestion tools play a vital role in automating and simplifying this process by importing data from diverse sources into systems, databases, or applications. Confluent specializes in automating secure and scalable data ingestion, offering services such as streaming data pipelines, real-time processing, and integration across more than 120 data sources. Users can initiate the streaming of data within minutes, irrespective of the cloud platform they choose.
Event-driven architecture (EDA) is a software design pattern designed to facilitate the creation of scalable and loosely connected systems. The flow in this architecture is driven by events, which represent occurrences or changes in the system. These events are generated from various sources, published to an event bus or message broker, and then asynchronously consumed by interested components. Emphasizing flexibility, scalability, and resilience, this approach is effectively implemented by Confluent. Recognized as the optimal solution for event-driven architecture, Confluent provides a comprehensive and scalable platform centered around Apache Kafka. This platform delivers high-performance, fault-tolerant event streaming capabilities and boasts a rich ecosystem of tools, connectors, and management features. As a result, organizations can efficiently build, manage, and scale their event-driven systems with Confluent's empowering solutions.
Legacy solutions are often designed with a focus on storage-centric and batch-oriented workloads, making them ill-suited for addressing the requirements of data governance in robust streaming data and event-driven architectures. This limitation prompts the need for a specialized solution. Confluent's Stream Governance empowers agencies to seamlessly amalgamate both current and historical business data, enabling the creation and management of event-driven, real-time solutions. The process of bringing together data from various facets of the organization, maintaining its continuous flow, and unlocking its inherent value demands the right set of tools. These tools cater to the visualization and communication needs of data stewards and governors, facilitating their role in overseeing and managing changes in the data landscape.
Confluent empowers agencies to combine and process all of your data at scale for faster and smarter context to detect malicious behavior. Our event-driven architecture delivers a continuous flow of data, chosen by you, and streamed to whichever application or team needs to see it. We provide real-time context to each interaction, each transaction, each anomaly, so your fraud detection systems have the intelligence to get ahead of compromises.
Data mesh is a data architecture framework designed to enhance data management and scalability within organizations. It is designed to make data connectivity fast and efficient. Connectivity within the data mesh naturally lends itself to event streaming with Apache Kafka, where high-quality data streams of data products can be consumed in real-time, at scale. As a fully managed, cloud-native Kafka service with the most complete offering that’s available everywhere in the cloud, across clouds, or on-premises, Confluent empowers agencies to build an enterprise data mesh.
Confluent revolutionizes cybersecurity by merging real-time streaming data infrastructure with cutting-edge technologies, overcoming the constraints of traditional SIEM systems in scale, speed and cost. This integration empowers agencies to dismantle data silos and extract contextually rich insights, enhancing situational awareness in the face of evolving threats. With Confluent, agencies gain access to unparalleled data ingestion, real-time analytics and cost-effective scalability, equipping them with the tools needed to navigate complex cybersecurity landscapes with agility and efficiency. By seamlessly integrating diverse tools and analytic destinations, Confluent enables InfoSec teams and SOCs to optimize their cybersecurity posture. The platform’s holistic approach not only addresses current cybersecurity challenges but also provides the flexibility to adapt to emerging threats. With Confluent, agencies can stay ahead of the curve, confidently managing cybersecurity risks while optimizing resources for sustained resilience in an ever-changing digital landscape.
Legacy solutions are often designed with a focus on storage-centric and batch-oriented workloads, making them ill-suited for addressing the requirements of data governance in robust streaming data and event-driven architectures. This limitation prompts the need for a specialized solution. Confluent's Stream Governance empowers agencies to seamlessly amalgamate both current and historical business data, enabling the creation and management of event-driven, real-time solutions. The process of bringing together data from various facets of the organization, maintaining its continuous flow, and unlocking its inherent value demands the right set of tools. These tools cater to the visualization and communication needs of data stewards and governors, facilitating their role in overseeing and managing changes in the data landscape.
Confluent empowers agencies to combine and process all of your data at scale for faster and smarter context to detect malicious behavior. Our event-driven architecture delivers a continuous flow of data, chosen by you, and streamed to whichever application or team needs to see it. We provide real-time context to each interaction, each transaction, each anomaly, so your fraud detection systems have the intelligence to get ahead of compromises.
Data mesh is a data architecture framework designed to enhance data management and scalability within organizations. It is designed to make data connectivity fast and efficient. Connectivity within the data mesh naturally lends itself to event streaming with Apache Kafka, where high-quality data streams of data products can be consumed in real time, at scale. As a fully managed, cloud-native Kafka service with the most complete offering that’s available everywhere in the cloud, across clouds, or on-premises, Confluent empowers agencies to build an enterprise data mesh.
Confluent's RTDR leverages high-throughput data streaming from various government security sources, including network activity logs, endpoint detection and response (EDR) systems, and user access logs. This allows for continuous analysis of data streams to identify suspicious activity in real-time. Machine learning algorithms can be integrated to detect anomalies and potential breaches, enabling government agencies to respond swiftly and mitigate cyberattacks before significant damage occurs.
Confluent acts as a central hub for consolidating and enriching data feeds relevant to security. It integrates with existing Security Information and Event Management (SIEM) solutions, streamlining data ingestion and filtering. Confluent can transform raw data streams into actionable insights by correlating events from various sources and adding context for better threat hunting and forensic analysis. This enriched data empowers security teams to make faster and more informed decisions during incident response.
Confluent offers robust data security features to protect classified data throughout its lifecycle within the platform. Dynamic data masking allows for the real-time anonymization of sensitive information in data streams. This ensures that only authorized users with proper access controls can view the complete data. Confluent's role-based access control (RBAC) system further restricts data visibility and processing based on user permissions. This granular control minimizes the risk of unauthorized access to classified data, even for authorized users with access to the Confluent platform.