Save 90% of time searching and browsing logs with Logdy, a tool that provides a powerful and secure UI for log management, supporting any format and offering a low-code TypeScript log parser.
Elasticsearch’s latest innovation in log management cuts the storage footprint of log data by up to 65%, enabling observability and security teams to expand visibility without exceeding their budget while keeping all data accessible and searchable.
Key features of LogsDB Index Mode include:
- Improved indexing speed and efficiency for log data, which is typically unstructured and high volume.
- Enhanced storage efficiency by utilizing a columnar storage format, which is better suited for log data analysis.
- Simplified configuration and tuning, making it easier to manage and optimize log data workflows.
Key features of LogsDB Index Mode include:
- Improved indexing speed and efficiency for log data, which is typically unstructured and high volume.
- Enhanced storage efficiency by utilizing a columnar storage format, which is better suited for log data analysis.
- Simplified configuration and tuning, making it easier to manage and optimize log data workflows.
Learn about tldr, a command that simplifies Linux command help with concise, accessible pages and key examples. Install tldr using npm or Homebrew, then use commands like 'tldr grep' to quickly access command help.
Find and experiment with AI models for free, then switch to a paid Azure account when you're ready to bring your application to production.
- GitHub Models allows users to find and experiment with AI models for free.
- To find AI models, users can go to GitHub Marketplace and click on Models in the sidebar.
- The playground, available in the GitHub Marketplace, allows users to adjust model parameters and submit prompts to see the model's response.
- Users can compare two models simultaneously and are rate-limited.
- GitHub provides free API usage for experimenting with AI models in your own application.
- GitHub Models allows users to find and experiment with AI models for free.
- To find AI models, users can go to GitHub Marketplace and click on Models in the sidebar.
- The playground, available in the GitHub Marketplace, allows users to adjust model parameters and submit prompts to see the model's response.
- Users can compare two models simultaneously and are rate-limited.
- GitHub provides free API usage for experimenting with AI models in your own application.
GitHub Models now allows developers to retrieve structured JSON responses from models directly in the UI, improving integration with applications and workflows. Supported models include OpenAI (except for o1-mini and o1-preview) and Mistral models.
Explore various open-source tools for monitoring your home network, including Grafana, Zabbix, PRTG, Pi.Alert, Cacti, Nagios Core, Icinga 2, Prometheus, NetXMS, and Ntopng. These tools help manage network traffic, identify performance bottlenecks, and enhance security.
The article discusses the use of AI agents for automating and optimizing tasks in the networking industry, including network deployment, configuration, and monitoring. It outlines a workflow with four agents that collectively achieve the setup and verification of network connectivity within a Linux and SR Linux container environment.
The author demonstrates a workflow involving four AI agents designed to deploy, configure, and monitor a network:
Document Specialist Agent: This agent extracts installation, topology deployment, and node connection instructions from a specified website.
- Linux Configuration Agent: Executes the installation and configuration commands on a Debian 12 UTM VM, checks the health of the VM, and verifies the successful deployment of network containers.
- Network Configuration Specialist Agent: Configures network IP allocation, interfaces, and routing based on the network topology, including detailed BGP configurations for different network nodes.
- Senior Network Administrator Agent: Applies the generated configurations to the network nodes, checks BGP peering, and verifies end-to-end connectivity through ping tests.
The author demonstrates a workflow involving four AI agents designed to deploy, configure, and monitor a network:
Document Specialist Agent: This agent extracts installation, topology deployment, and node connection instructions from a specified website.
- Linux Configuration Agent: Executes the installation and configuration commands on a Debian 12 UTM VM, checks the health of the VM, and verifies the successful deployment of network containers.
- Network Configuration Specialist Agent: Configures network IP allocation, interfaces, and routing based on the network topology, including detailed BGP configurations for different network nodes.
- Senior Network Administrator Agent: Applies the generated configurations to the network nodes, checks BGP peering, and verifies end-to-end connectivity through ping tests.
AWS announces S3 Tables, a new bucket type for data analytics using Apache Iceberg format, and S3 Metadata for fast query of data, at the Re:Invent conference.
Jaeger, a leading open-source distributed tracing platform, releases its version 2, which aligns with the OpenTelemetry framework, bringing improved performance, streamlined architecture, and native support for OTLP. The update includes advanced sampling techniques, expanded ecosystem access, and a more flexible storage implementation.
Observe, Inc. launched Kubernetes Explorer, a new observability experience designed to simplify visualizing and troubleshooting in Kubernetes environments, providing DevOps teams and engineers with a comprehensive view of K8s health and performance.
