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By David Bunting
When it comes to managing AWS cloud security, a growing concern for security operations (SecOps teams) is the increasing sophistication of digital threats. While conventional cyber threats deploy widely known tools and techniques in crude, all-or-nothing attempts to breach enterprise security controls, sophisticated attacks known as Advanced Persistent Threats (APTs) employ more advanced technologies and methods to gain and maintain access to secure systems for long periods of time.
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By Kevin Petrie
Cloud computing shapes the ability of enterprises to transform themselves and effectively compete. By renting elastic cloud resources, enterprises can support new customer platforms, distributed workforces, and back-office operations. The cross-functional discipline of CloudOps helps enterprises manage cloud resources by optimizing applications and infrastructure.
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By Dave Armlin
Amazon CloudWatch is a great tool for DevOps engineers, developers, SREs, and other IT personnel who require basic Amazon Web Services (AWS) log processing and analytics for cloud services and applications deployed on AWS. However, most developer teams will ultimately need more logging functionality than a basic AWS log analyzer like Amazon Cloudwatch can provide. For example: That's why, although CloudWatch may be one tool in your log analytics strategy, it probably should not be the only one.
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By David Bunting
Cyber threats against AI systems are on the rise, and today's AI developers need a robust approach to securing AI applications that address the unique vulnerabilities and attack patterns associated with AI systems and ML models deployed in production environments. In this blog, we're taking a closer look at two specific tools that AI developers can use to help detect cyber threats against AI systems.
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By Dave Armlin
Enterprise data and analytics is a fast-evolving field in enterprise IT, where new technologies and solutions are creating revolutionary ways to extract insights from data. To keep pace with these changes and drive value creation through data analytics initiatives, organizations must be willing to adopt innovative solutions, embrace new and emerging best practices, and move beyond obsolete or outdated methods that are no longer effective. Our blog post this week is all about transforming your enterprise data architecture to elevate your data management and analytics capabilities.
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By Thomas Hazel
While data lakes make it easy to store and analyze a wide variety of data types, they can become data swamps without the proper documentation and governance. Until you solve the biggest data lake challenges — tackling exponential big data growth, costs, and management complexity — efficient and reliable data analytics will remain out of reach.
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By David Bunting
Managed Detection and Response (MDR) services play a critical role in cybersecurity. These technologies remotely monitor, detect, and respond to threats, blending threat intelligence with human expertise to hunt down and neutralize potential risks. However, one of the biggest challenges MDRs face is managing the sheer volume and variety of threat intelligence data they receive. This data comes from internal resources and the numerous security technologies their customers use, making it difficult to create a cohesive picture of the threat landscape.
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By David Bunting
Modern SecOps teams use Security Information and Event Management (SIEM) software to aggregate security logs, detect anomalies, hunt for threats, and enable rapid incident response. While SIEMs enable accurate, near real-time detection of threats, today's SIEM solutions were never designed to handle the volume of security data organizations generate daily. As daily log ingestion grows, so do the costs of data management.
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By David Bunting
Managed Detection and Response (MDR) is a cybersecurity service offered by a Managed Security Services Provider (MSSP) that combines human security expertise with modern security tools to deliver managed threat detection, security monitoring, and incident response capabilities for both SMBs and enterprise clients.
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By David Bunting
The 2024 Global Digital Trust Insights survey from PwC reports that 36% of businesses have experienced a data breach that cost more than $1 million to remediate. Cyber threats are clearly on the rise and in today’s volatile threat environment, it is a matter of when - not if - a cybersecurity incident will occur. Digital adversaries are becoming more sophisticated and relying on weak links to exploit company applications and infrastructure.
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By ChaosSearch
The leader in cybersecurity, Blackpoint Cyber, has teamed up with ChaosSearch, to create a next-generation data platform for log analytics for observability & security. We look forward to working with the Blackpoint team on tackling the rising costs & pain of ELK, while significantly increasing data retention, building a future-proof data platform for the increasingly challenging cybersecurity environment & AI-driven world.
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By ChaosSearch
In today's data-driven landscape, the ability to derive actionable insights from log data is more critical than ever. Among the plethora of log formats, JSON (JavaScript Object Notation) has emerged as a prevalent choice for logging due to its flexibility and readability.
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By ChaosSearch
Learn how ChaosSearch analyzes log and event gaming data from fictitious car racing game racing legends.
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By ChaosSearch
Thomas Hazels talks to John Furrier, co-founder of SiliconANGLE on data: AI, LLM, and Chaos LakeDB.
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By ChaosSearch
Built from the ground up to transform your cloud storage into a Live Search+SQL+GenAI Analytics Database. Ed Walsh shares details on the new Chaos LakeDB.
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By ChaosSearch
Built from the ground up to transform your cloud storage into a Live Search+SQL+GenAI Analytics Database.
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By ChaosSearch
CHAOSSEARCH is a fully managed Log Analysis SaaS solution built on our innovative architecture and revolutionary, patent-pending index technology. Our solution delivers log analysis at cloud-scale and eliminates data movement - the first SaaS solution to provide infinite data storage by accessing your data in your Amazon S3.
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ChaosSearch makes it simple for organizations to run cloud-scale log analytics in their own Amazon S3 cloud storage. It uniquely transforms your cheap, secure, and durable cloud object storage into a distributed analytic data lake where scale is infinite, cost is disruptive, and access is universal.
Traditional log analytics weren’t designed for today’s tsunamis of log data. They require brute force (adding more and more compute) to search and analyze huge stores of logs. This means businesses must continually choose between spending more money or reducing data retention.
ChaosSearch’s SaaS data platform was built for a data-entrenched world. It’s based on the company’s patent-pending index technology and architecture that remove the limits, cost, and complexity inherent in conventional solutions.
- Performance at Scale: Easily scales to petabytes and beyond so you can analyze what you need, whenever you need.
- Fully Managed Service: There’s no software or hardware for you to deploy, configure or maintain.
- All on Your Amazon S3: ChaosSearch stores and analyzes data directly in your own Amazon S3 cloud object storage. It does not hold or store any data.
- Disruptive Pricing: Costs up to 80% less than other solutions, thanks to Chaos Index’s unique properties that eliminate the need to manually shard data and enable unparalleled compression ratios.