With an Assist from Redis Enterprise, Malwarebytes Makes the Digital World a Safer Place
公司规模
Large Corporate
国家
- United States
产品
- Redis Enterprise
- Amazon ElastiCache for Redis
- DynamoDB
技术栈
- NoSQL
- In-memory processing
- Real-time streaming
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Customer Satisfaction
- Digital Expertise
技术
- 分析与建模 - 实时分析
- 应用基础设施与中间件 - 数据交换与集成
- 应用基础设施与中间件 - 数据库管理和存储
适用行业
- Software
- 安全与公共安全
适用功能
- 商业运营
- 质量保证
用例
- 实时定位系统 (RTLS)
- 网络安全
- 预测性维护
- 远程资产管理
服务
- 系统集成
- 软件设计与工程服务
- 云规划/设计/实施服务
关于客户
Malwarebytes is an industry-leading anti-malware and internet security software provider. The company’s innovative real-time security tools detect and prevent malware infections for customers across the globe. The Malwarebytes Data and AI team is able to provide interactive dashboards that trace the trajectories and velocities of detected threats as they spread around the world. Malwarebytes’ use of Redis Enterprise for fast data ingestion, session management, centralized stateful storage, time series analysis, and geospatial analysis allows the company to aggregate, correlate, and visualize data in a manner and speed it believes would not be possible without Redis Enterprise.
挑战
Before Redis Enterprise, Malwarebytes was struggling to harness the sheer enormity of data their systems were capturing. The company had access to a wealth of malware data, but leveraging that data with the speed and efficiency necessary to drive intelligence into global and local attack vectors was a daunting task. One of the challenges at hand was to create stateful storage for several of Malwarebytes’ lifeblood data streams. They received billions of records of malware detection information, and as malware was detected, threat details were streamed to a centralized data platform. Stateful environment information was also streamed and collected separately in stateful storage for streaming data joins. Understanding environment state as malware detections were found in real-time was game-changing, providing deep insights into malware proliferation, velocities, and attack vectors that were previously impossible. Additionally, Malwarebytes’ advanced visualizations posed another big storage challenge. The visualizations provided an analysis of outbreak geography, velocities, and even insights into gestational periods of early malware formation. However, they were built on vast amounts of data and required tremendous amounts of compute resources to generate, necessitating a database that could provide centralized stateful storage and perform real-time streaming joins at a massive scale.
解决方案
Since its implementation at Malwarebytes, NoSQL Redis Enterprise has become an essential part of the backbone of the company’s real-time streaming layer. Malwarebytes relies on several standout Redis features uniquely suited to its challenging use cases. In-memory processing Redis has been benchmarked to handle over one million read/write operations per second. The blazing fast performance of in-memory Redis is critical in addressing Malwarebytes’ incredibly high throughput, requirement for real-time streaming joins, and need to access massive amounts of data at caching speeds. They tried DynamoDB, but it wasn’t fast enough, and other options like Kafka’s K-tables were fast enough but problematic and difficult to debug and ensure data consistency. Redis’ built-in data structures were another big draw for Malwarebytes. The database’s Set, Hash, and Geo Set data structures optimize the complex time series and geospatial analyses that power Malwarebytes’ dashboards. Redis provided the much-needed real-time indexing and retrieval capability for creating joins on streaming data. Malwarebytes had originally been running Amazon ElastiCache for Redis but decided it needed true high availability, scalability, and reliability, as well as an expert support team. Redis Labs and its enterprise-grade Redis brought all of those things to the table and something else: an engineering mindset. Redis Labs was willing to help Malwarebytes architect and engineer the best solution before production, ensuring a high-performing production system.
运营影响
数量效益
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