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Threat Hunting Frameworks and Methodologies: An Introductory Guide

Establishing an effective cyber threat hunting program is among the top priorities of enterprise security leaders seeking a proactive approach to detecting and counteracting potential threats. Furthermore, implementing a proactive threat hunting program, security teams that leverage formalized frameworks or threat hunting methodologies are far more likely to detect vulnerabilities or in-process malicious activities in their environments than those that do not. However, data from a 2023 threat hunting survey revealed that while 73% of organizations have adopted a defined threat hunting framework, only 38% actually follow it.
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5 Guiding Principles of Digital Business Observability

Modern data-driven organizations are synergizing operations observability, business intelligence, and data science with digital business observability programs that break down data silos, increase productivity, and drive innovation. Digital business observability combines IT and business data with cutting-edge data science techniques, enabling deeper analysis and unlocking valuable insights that propel innovation across use cases from sales and marketing to product design and financial operations.

3 Straightforward Pros and Cons of Datadog for Log Analytics

Observability is a key pillar for today’s cloud-native companies. Cloud elasticity and the emergence of microservices architectures allow cloud native companies to build massively scalable architectures but also exponentially increase the complexity of IT systems.

A Deep Dive into Multi-Model Databases: Hype vs. Reality

In 2009, as the world became increasingly data-driven, organizations began to accumulate vast amounts of data — a period that would later be characterized as the Big Data revolution. While most organizations were used to handling well-structured data in relational databases, this new data was appearing more and more frequently in semi-structured and unstructured data formats.
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3 Reasons Why You Need an Embedded, Modern Database

Today's applications demand efficient data handling to provide users with seamless experiences. One solution that has gained prominence is the use of embedded databases, which are integrated within applications rather than relying on external servers. Different from a database for embedded systems, databases embedded within applications offer several advantages for storing data and analyzing it, especially in scenarios where performance, deployment simplicity, and data security are important. Embedded databases, or an embedded database management system (DBMS), can serve a variety of use cases, but are especially valuable for applications that need to provide analytics capabilities.

Best Practices for Effective Log Management

Can following log management best practices help organizations with their overall observability, as well as troubleshooting issues and security analytics? Absolutely. In addition, following log management best practices can provide significant competitive advantages when it comes to understanding your users. Centralized log management can help your team accelerate time to insights, and make changes to your applications that improve the user experience.

5 Multi-cloud Data Management Best Practices You Should Follow

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.
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Buyer Beware! Three Challenges with Elasticsearch and OpenSearch

Elasticsearch and OpenSearch are powerful enterprise search and analytics engines that have become popular in the world of data management and telemetry analysis. Their ability to swiftly search, analyze, and visualize data has made them indispensable for businesses and organizations. However, in this blog, we will explore a few key challenges faced by companies using Elasticsearch and OpenSearch, shedding light on important considerations when selecting the right tool for your needs.

A Simplified Guide to Kubernetes Monitoring

The open-source Kubernetes platform has become the de facto standard for deploying, managing, and scaling containerized services and workloads. In fact, 83% of DevOps teams are using Kubernetes to deploy containerized applications in production, taking advantage of its workload orchestration and automation capabilities to optimize the software development process and reduce web server provisioning costs.

5 Elasticsearch Disadvantages You Should Know

Since its initial release in 2010, Elasticsearch has grown into the most popular enterprise search engine with use cases that range from web crawling and website search to application performance monitoring and security log analytics. But despite its widespread adoption and success, Elasticsearch does have some notable disadvantages that you should consider - especially if you’re envisioning a high-scale deployment with a large amount of daily ingestion.