Technology Category
- Application Infrastructure & Middleware - Event-Driven Application
- Cybersecurity & Privacy - Application Security
Applicable Industries
- Glass
- National Security & Defense
Applicable Functions
- Maintenance
Use Cases
- Tamper Detection
- Traffic Monitoring
Services
- Cloud Planning, Design & Implementation Services
About The Customer
Datadog is a leading monitoring and security platform service for cloud applications. Founded in 2010, the company has rapidly scaled to serve its global customers by embracing the value of modern engineering and architecture practices. Thousands of customers rely on Datadog to see metrics and events from software across their DevOps stack, such as cloud and security monitoring, alerts, logs, and more. As a leader in the DevOps space, Datadog champions cloud-native applications built with the latest tools and best practices. The company pushes code dozens of times per day to meet customer needs.
The Challenge
Datadog, a monitoring and security platform service for cloud applications, faced a significant challenge as it continued to grow. The company's homegrown application security tools were not scalable enough to support its rapidly expanding customer base. The organization needed to adopt a Web Application Firewall (WAF), but it had specific requirements. The WAF needed to provide flexibility in modern cloud architectures, support rapid code changes and deployments in a CI/CD pipeline without extensive tuning, and not consume unnecessary resources across security, SRE, and development teams. The challenge was finding a solution that could meet these requirements while keeping up with the pace of Datadog's growth.
The Solution
Datadog found its solution in Signal Sciences, the only vendor that could keep up with their pace while filling their gaps. Signal Sciences offered flexible deployment options that allowed Datadog to quickly and easily install their patented technology exactly where they needed it. This solution was particularly beneficial for Datadog as it allowed them to continue delivering on their value proposition of providing a single pane of glass for all app monitoring needs. Signal Sciences protected Datadog by immediately filtering and blocking attacks without extensive or ongoing rules tuning. This gave Datadog's security team the breathing room they needed to focus on high-priority tasks and projects. Furthermore, Signal Sciences had no performance impact on the application or the organization. After deploying Signal Sciences, Datadog reported zero performance issues across the board.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Data Capture for Afghanistan Forces
Electronic equipments on the field of Afghanistan provided information on the status of the vehicle and to identify potential threats surrounding it to the British Force. The monitoring and interpretation of this data requires robust and sophisticated digitization for data capture and communication.
Case Study
Enhancing Security and Compliance in Remitly's Global Money Transfer Service with Fastly
Remitly, an online remittance service, was faced with the challenge of securing its proprietary global transfer network. The company needed a security solution that could meet PCI requirements and protect customers' sensitive transactions through its mobile application. The solution had to be capable of defending against new and emerging attack types without impacting performance. Remitly also had to deal with irregular traffic patterns, such as a sudden spike in account transfers from a small network segment on the Pacific coastline of South America. The company needed to determine in real time whether such traffic indicated an attack or valid requests. A traditional web application firewall (WAF) would not be able to distinguish this traffic, potentially leading to customer frustration if the IP was blacklisted.
Case Study
Discrete Manufacturing Industries (Fiberglass Pipe)
The implementation of ERP software in a Discrete Manufacturing organization needs to be strategic, irrespective of its size and capacity. The client had already implemented an ERP system which fulfilled their requirements but was not efficient enough. Efficiency here meant Synchronized Planning, Updating and Multisite Planning. Planning at client’s place was done outside the ERP system. Lack of proper synchronization to the ERP system paved way to huge delays in the changes getting updated in the system. These delays caused disruption in achieving delivery schedules. Multisite Planning is a solution to an organization which has multiple production units (may or may not be geographically separated) and thus needs planning across these units to synchronize production activities within them. The client also has multiple factories and hence Production Planning control is very essential in their case. Since Multisite planning was not possible with Baan ERP system, this was another bottleneck for the client.
Case Study
Major Aerospace Company Automates Asset Management
The O&M division of an aerospace and global security company was using spreadsheets to manually track more than 3,000 assets assigned to students and staff. Maintaining audit trails for this high volume of equipment became increasingly time-consuming and challenging. The chore involved knowing precisely what equipment was on hand, what had been issued, its location and the name of the custodial owner of each item. Every aspect of this task was carried owner of each item. Every aspect of this task was carried out by individuals with spreadsheets. Manually documenting the full lifecycle of each asset added to the burden. This included tracking maintenance requirements and records, incidents and damages, repairs, calibrations, depreciation, and end-of-life data.
Case Study
Securing a Large Data Center in the EMEA Region: An IoT Case Study
A leading data-center operator in the EMEA region, with multiple facilities spanning over 25,000 square meters, faced significant security challenges. The operator experienced interruptions in their internal IT network due to unsupervised work of third-party technicians. Despite having a high-end building control system that provided 24x7 monitoring and control to all the building’s infrastructure, the data center was vulnerable from a cyber perspective as it was connected to the IT network infrastructure. The operator launched an urgent OT cyber security project that included both IT-OT network segmentation and OT network asset mapping and anomaly detection. The main objectives were to harden the security of the server systems, secure the facility’s power supply and server cooling system, strengthen the segmentation between building and operational systems, create a visual OT network map, and set up a system for presenting supply-chain attacks that may threaten the data center through equipment vendors’ maintenance activities.
Case Study
Leveraging Graph Technology for Enhanced Cybersecurity: A Case Study on MITRE's CyGraph
MITRE, a federally-funded, not-for-profit company that manages seven national research and development laboratories in the United States, was grappling with the challenge of managing an influx of cybersecurity data. The constant changes in network environments were impacting the security posture of U.S. government agencies. Intrusion alerts, anti-virus warnings, and seemingly benign events like logins, service connections, and file share access were all potentially associated with adversary activity. The cybersecurity researchers at MITRE needed to go beyond rudimentary assessments of security posture and attack response. This required merging isolated data into higher-level knowledge of network-wide attack vulnerabilities and mission readiness. The challenge was not the lack of information, but the ability to assemble disparate pieces of information into an overall analytic picture for situational awareness, optimal courses of action, and maintaining mission readiness. The team also struggled with fully comprehending a given security environment and mapping all known vulnerabilities.