Sponsored Post
|
By David Bunting
Companies who develop software products generate massive quantities of product performance and user engagement data that can be analyzed to support decision-making about everything from feature planning and UX design to sales, marketing, and customer support. Leveraging product data throughout the enterprise represents a significant opportunity to achieve a competitive advantage, but challenges like siloed data systems, poor data literacy, and the complexity of data analytics in the cloud can prevent organizations from making full use of their raw data.
Sponsored Post
|
By David Bunting
A data lake is a centralized data repository where structured, semi-structured, and unstructured data from a variety of sources can be stored in their raw format. Data lakes help eliminate data silos by acting as a single landing zone for data from multiple sources. But what's the difference between a traditional data lake and a real-time data lake? Some traditional data lakes use batch processing, which involves processing and analyzing a collection of data that has been stored over a specific timeframe. For example, payroll and billing systems that are handled on a weekly or monthly basis might use batch processing.
Sponsored Post
|
By David Bunting
Access to data is critical for SaaS companies to understand the state of their applications, and how that state affects customer experience. However, most companies use multiple applications, all of which generate their own independent data. This leads to data silos, or a group of raw data that is accessible to one stakeholder or department and not another. Data silos also prevent information from different sources from being blended together to gain a more accurate picture of what's happening in your application.
Sponsored Post
|
By David Bunting
This year, Amazon Web Services (AWS), a leading cloud services provider, announced a comprehensive security solution called Amazon Security Lake. In this blog post, we will explore what Amazon Security Lake is, how it works, the benefits for organizations, and partners you can leverage alongside it to enhance security analytics and quickly respond to security events.
Sponsored Post
|
By David Bunting
Since the data lake concept emerged more than a decade ago, data lakes have been pitched as the solution to many of the woes surrounding traditional data management solutions, like databases and data warehouses. Data lakes, we have been told, are more scalable, better able to accommodate widely varying types of data, cheaper to build and so on. Much of that is true, at least theoretically. In reality, the way many organizations go about building data lakes leads to a variety of problems that undercut the value their data lakes are supposed to deliver.
Sponsored Post
|
By David Bunting
As organizations increasingly adopt serverless architectures and embrace the benefits of microservices, managing logs in this dynamic environment presents unique challenges. In this blog, we're taking a closer look at the differences between serverless and traditional log management, as well as 8 challenges associated with log management for serverless microservices.
Sponsored Post
|
By David Bunting
Managed Detection and Response (MDR) services occupy an important niche in the cybersecurity industry, supporting SMBs and enterprise organizations with managed security monitoring and threat detection, proactive threat hunting, and incident response capabilities. In this week's blog, we're taking a closer look at the role of MDRs in cybersecurity, the biggest challenges they face, and how integrating ChaosSearch is helping MDRs manage complexity, reduce data retention costs, and enable long-term security analytics use cases that are critical for customer success.
Sponsored Post
|
By David Bunting
Continuous monitoring is a crucial practice in the fields of DevOps, cybersecurity, and compliance. It involves the proactive and ongoing process of observing, assessing, and collecting data from various systems, applications, and infrastructure components in real-time or near real-time. Continuous monitoring is closely related to observability, which goes beyond simple monitoring to provide a deep understanding of complex and dynamic systems.
Sponsored Post
|
By David Bunting
A multi-cloud approach helps organizations avoid vendor lock-in, leverage the best available technologies, and reduce costs - but it can also result in added complexity when it comes to centralizing, securing, and analyzing data from cloud applications and services. This blog highlights 5 multi-cloud data management best practices that can help you make the most of your data in multi-cloud environments.
Sponsored Post
|
By Dave Armlin
SecOps teams at midsize companies face a unique set of challenges when it comes to managing organizational cybersecurity. Midsize companies (those with 100-999 employees and $50 million-$1 billion in annual revenue, according to Gartner) possess significant financial resources and valuable data that may be targeted by digital adversaries. But, unlike larger enterprise organizations, midsize companies can't always afford to invest heavily in the expensive security tools and dedicated IT security staff needed to prevent cyber attacks.
|
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.
|
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.
|
By ChaosSearch
Learn how ChaosSearch analyzes log and event gaming data from fictitious car racing game racing legends.
|
By ChaosSearch
Thomas Hazels talks to John Furrier, co-founder of SiliconANGLE on data: AI, LLM, and Chaos LakeDB.
|
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.
|
By ChaosSearch
Built from the ground up to transform your cloud storage into a Live Search+SQL+GenAI Analytics Database.
|
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.
- March 2026 (1)
- February 2026 (1)
- January 2026 (1)
- December 2025 (1)
- November 2025 (1)
- October 2025 (1)
- September 2025 (1)
- August 2025 (1)
- July 2025 (1)
- May 2025 (1)
- April 2025 (1)
- March 2025 (1)
- February 2025 (1)
- January 2025 (1)
- December 2024 (1)
- November 2024 (1)
- October 2024 (1)
- September 2024 (2)
- August 2024 (3)
- July 2024 (1)
- June 2024 (3)
- May 2024 (3)
- April 2024 (3)
- March 2024 (3)
- February 2024 (2)
- January 2024 (2)
- December 2023 (3)
- November 2023 (8)
- October 2023 (8)
- September 2023 (4)
- August 2023 (4)
- July 2023 (19)
- June 2023 (6)
- May 2023 (6)
- April 2023 (7)
- March 2023 (20)
- February 2023 (2)
- January 2023 (4)
- December 2022 (5)
- November 2022 (4)
- October 2022 (3)
- September 2022 (2)
- August 2022 (4)
- July 2022 (1)
- June 2022 (2)
- April 2022 (1)
- February 2022 (2)
- January 2022 (1)
- November 2021 (1)
- September 2021 (4)
- August 2021 (5)
- July 2021 (3)
- June 2021 (2)
- May 2021 (3)
- April 2021 (4)
- March 2021 (5)
- February 2021 (5)
- January 2021 (3)
- August 2020 (1)
- July 2020 (5)
- April 2020 (2)
- February 2020 (3)
- December 2019 (1)
- November 2019 (1)
- October 2019 (2)
- September 2019 (1)
- August 2019 (4)
- July 2019 (2)
- June 2019 (1)
- March 2019 (1)
- February 2019 (7)
- November 2018 (1)
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.