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How to Get Started with a Security Data Lake

Modern, data-driven enterprise SecOps teams use Security Information and Event Management (SIEM) software solutions to aggregate security logs, detect anomalies, hunt for security threats, and enable rapid response to security incidents. SIEMs enable accurate, near real-time detection of security threats, but today's SIEM solutions were never designed to handle the large amounts of security log data generated by modern organizations on a daily basis.
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5 ELK Stack Pros and Cons

Is your organization currently relying on an ELK cluster for log analytics in the cloud? While the ELK stack delivers on its major promises, it isn't the only search and analytics engine - and may not even be your best option for log management. As cloud data volumes grow, ELK monitoring can become too costly and complex to manage. Fast-growing organizations should consider innovative alternatives offering better performance at scale, superior cost economics, reduced complexity and enhanced data access in the cloud.

8 Challenges of Microservices and Serverless Log Management

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.

Understanding Amazon Security Lake: Enhancing Data Security in the Cloud

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. Image source: Amazon.

Six Most Useful Types of Event Data for PLG

The success of businesses like Zoom, DropBox, and Slack demonstrates the power of product-led growth (PLG) as a strategy for scaling software companies in 2023. Central to this approach is event analytics, the practice of analyzing event data from a software product to unlock data-driven insights. Companies following a PLG strategy (“PLG companies”) use this data to inform product development decisions to enhance user experiences and drive revenue.
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Logs vs. Events: Exploring the Differences in Application Telemetry Data

What is the difference between logs and events in observability? These two telemetry data types are used for different purposes when it comes to exploring your applications and how your users interact with them. Simply put, logs can be used for troubleshooting and root cause analysis, while events can be used to gain deeper application insights via product analytics. Let's review some application telemetry data definitions for context, then dive into the key differences between logs and events and their use cases. Knowing more about these telemetry data types can help you more effectively use them in your observability strategy.

Data-Led Growth: How FinTechs Win with App Event Analytics

In the rapidly shifting world of financial technology (FinTech), acquiring and retaining new customers to achieve long-term business growth requires a proactive approach to user experience and application performance optimization. As FinTech companies compete against rivals to grow a user base and revolutionize how consumers manage their finances, they increasingly depend on data-driven insights to optimize their mobile applications and deliver exceptional user experiences.

Data Lake Architecture & The Future of Log Analytics

Organizations are leveraging log analytics in the cloud for a variety of use cases, including application performance monitoring, troubleshooting cloud services, user behavior analysis, security operations and threat hunting, forensic network investigation, and supporting regulatory compliance initiatives. But with enterprise data growing at astronomical rates, organizations are finding it increasingly costly, complex, and time-consuming to capture, securely store, and efficiently analyze their log data.

10 AWS Data Lake Best Practices

A data lake is the perfect solution for storing and accessing your data, and enabling data analytics at scale - but do you know how to make the most of your AWS data lake? In this week’s blog post, we’re offering 10 data lake best practices that can help you optimize your AWS S3 data lake set-up and data management workflows, decrease time-to-insights, reduce costs, and get the most value from your AWS data lake deployment.
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What is an Internal Developer Platform (IDP) and Why It Matters

In today's evolving technological landscape, enterprises are under increasing pressure to deliver high-quality software at an accelerated pace. Internal Developer Platforms (IDPs) provide a centralized developer portal that empowers developers with self-service capabilities, standardized development environments, and automation tools to accelerate the software development lifecycle. In this week's blog, we're taking a closer look at internal developer platforms and how implementing IDPs is helping organizations overcome the complexity of modern software development and increase developer efficiency to accelerate the delivery of software products.