Linux, Debian, and Ubuntu are the Kirk, Spock, and McCoy of modern application development. The Captain Kirk, Linux, is the open-source central code for directing and talking to hardware. Debian sits as the trio’s Spock, the original distro that can be seen as more complex to install and use. As a Debian child distro, Ubuntu is the McCoy, helping to heal the challenges that people have when trying to use Debian.

We’ve been steadily building strong momentum with Microsoft over the past year, and the latest step forward is a significant one: Cribl solutions are now available on the Microsoft Azure Marketplace. But why this focus on Microsoft Azure? The answer lies in what customers are prioritizing and discussing with us.

As a trusted partner in the Microsoft ecosystem, Elasticsearch has achieved another significant milestone by becoming a Certified Software Solution for Microsoft Azure. This certification not only underscores our commitment to excellence but also reflects our dedication to delivering seamless data solutions for our customers.

In previous discussions about Managed Security Service Providers (MSSPs), I’ve looked into the architectural benefits and product-level advantages of integrating Cribl. Today, let’s explore why Cribl isn’t just technically sound—it’s also a smart business decision that can help MSSPs like you manage and lower egress costs, creating a significant impact on the financial efficiency of your operations.

Our production services run on a Linux machine using Docker Compose, keeping our infrastructure simple and manageable. Docker Compose allows us to easily define and manage multi-container applications, providing a straightforward way to orchestrate services, which helps reduce complexity in our infrastructure. Recently, we decided to switch to SigNoz to gain more flexibility and control over our observability stack. Following the SigNoz setup guide, we used logspout to collect and forward logs.

Every day, telemetry data is emitted, processed, and then either stored or deleted from services. Unfortunately, understanding and then optimizing the telemetry data can be difficult. These difficulties lead to higher MTTR/D, burnout, and unwanted overage bills.

As public sector organizations adapt to the exponential growth of data, there is a pressing need for powerful, adaptable solutions to manage and process large, complex data sets. Artificial intelligence (AI) and machine learning (ML) have become essential tools with the potential to transform data into actionable intelligence for government agencies. However, deploying these advanced solutions requires a robust infrastructure capable of handling the demands of data processing, storage, and analysis.

Business operations are now almost completely digitalized, this means with the appropriate tools timely data and reporting of key performance indicators can be utilized to assist in driving accurate business decision-making. With these tools, organizations can begin monitoring and analyzing extensive amounts of data that offer significant advantages to them.

As we gear up for AWS re:Invent this December, we’re excited to share some of the latest innovations that make our platform stand out. Coralogix continues to evolve with powerful new capabilities designed to simplify observability, improve performance monitoring, and deliver actionable insights across your systems. From advanced visualization tools to AI-powered troubleshooting, these updates reflect our commitment to empowering teams with smarter, faster ways to solve complex challenges.

Prometheus is an open-source monitoring solution, it offers efficient, scalable, and flexible monitoring practices and has emerged as a trusted tool for organizations seeking insights into their systems. It’s written in Go, gathers metrics data, and stores it in a time series database. Also, Prometheus employs a robust query language, PromQL, to manipulate and analyze collected time series data, offering versatile monitoring capabilities for various systems and services.