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Salesforce Commerce Cloud successfully transitioned from a self-hosted Prometheus monitoring system to Amazon Managed Service for Prometheus, achieving a 40% reduction in AWS costs while enhancing system reliability and reducing maintenance overhead. This migration allowed the team to focus more on innovation and customer service rather than managing infrastructure. The new solution scales seamlessly across multiple Amazon EKS clusters and regions, consolidating metrics effectively and improving operational efficiency.
Pinterest encountered a significant performance issue during the migration of its search infrastructure, Manas, to Kubernetes, where one in a million search requests experienced latency spikes. The investigation revealed that cAdvisor’s memory monitoring processes were causing excessive contention, leading to these delays. The team resolved the issue by disabling a specific metric in cAdvisor, allowing them to continue their migration efforts without compromising performance.
Patchman is a Django-based tool designed for monitoring patch statuses on Linux systems via a web interface. It allows users to track available package updates, categorize them as normal or security updates, and identify potential issues with installed packages. The system does not perform installations but provides detailed reporting and filtering options for hosts, packages, and repositories.
A slow database query caused significant downtime for the Placid app, highlighting the importance of monitoring and quickly addressing performance issues. The incident illustrates how rapid identification and resolution of such issues can minimize disruption and improve user experience. Implementing effective alerting systems and performance tracking can be crucial in preventing similar occurrences in the future.
The article discusses the integration of AWS VPC endpoints with AWS CloudTrail, highlighting how this setup enhances security and monitoring by enabling users to log and audit VPC endpoint activity. It also provides insights into the benefits of using CloudTrail for tracking API calls made by VPC endpoints, ensuring compliance and better resource management.
The article discusses best practices for deploying Python applications in production environments, emphasizing the importance of proper configuration, monitoring, and performance optimization. It highlights various tools and techniques that can enhance the reliability and scalability of Python applications in real-world scenarios.
The article provides an overview of Datadog's AI Ops solution, highlighting its capability to enhance operational efficiency through advanced analytics and machine learning. It emphasizes the importance of proactive monitoring and automated incident response in modern IT environments. The solution aims to empower teams with real-time insights and predictive capabilities to manage their systems effectively.
The article discusses the automation rules feature in Datadog, which allows users to streamline monitoring and alerting processes by automating responses to specific conditions. These rules can help teams manage their infrastructure more efficiently, reducing manual intervention and improving overall system reliability. By setting up automation rules, users can focus on more strategic tasks while ensuring that critical alerts are handled promptly.
The article discusses the complexities of optimizing observability within AI-driven environments, highlighting the unique challenges these systems present. It also offers potential solutions to enhance monitoring and analysis to ensure effective performance and reliability in such contexts.
The article outlines the capabilities of Datadog's cloud cost management solutions, focusing on various aspects of infrastructure, security, and application monitoring. It highlights features such as vulnerability management, compliance, and support for multiple cloud platforms, emphasizing its applicability across various industries. Additionally, it addresses the integration of AI and DevOps practices to enhance operational efficiency.
Grafana Alloy, the OpenTelemetry Collector distribution launched a year ago, has seen significant adoption and development, now supporting over 525,000 active instances. The article highlights Alloy's unique capabilities, including native pipelines for both OpenTelemetry and Prometheus, live debugging features, and Fleet Management for centralized control in Grafana Cloud. Future enhancements are focused on aligning with OpenTelemetry standards and improving user experience for debugging and configuration.
The article discusses best practices for achieving observability in large language models (LLMs), highlighting the importance of monitoring performance, understanding model behavior, and ensuring reliability in deployment. It emphasizes the integration of observability tools to gather insights and enhance decision-making processes within AI systems.
The article discusses the importance of observability in the context of retrieval-augmented generation (RAG) agents, emphasizing how effective monitoring can enhance their performance and reliability. It explores various strategies and tools that can be employed to achieve better insights and control over RAG systems, ultimately leading to improved user experiences.
Learn how to build a fully functional Generative AI chatbot using Docker Model Runner, integrating observability tools like Prometheus, Grafana, and Jaeger for real-time monitoring. This guide addresses common challenges in AI development and provides a step-by-step process to create a local chatbot with a modern interface and comprehensive performance metrics.
The article discusses the integration of OpenAI's capabilities with Datadog's AI DevOps agent, highlighting how this collaboration enhances monitoring and performance optimization for cloud environments. It emphasizes the potential for improved incident response and proactive management through AI-driven insights.
The blog post introduces Apache Kafka 4.1, highlighting its new features and improvements aimed at enhancing performance and usability. Key updates include better support for schema evolution, improved monitoring capabilities, and optimizations for streaming applications. The article emphasizes Kafka's role in real-time data processing and its growing importance in modern data architectures.
The article explains Kafka consumer lag, which refers to the delay between data being produced and consumed by Kafka consumers. It highlights the significance of monitoring consumer lag to ensure efficient data processing and system performance, and discusses various methods to measure and manage this lag effectively.
Grafana 12 introduces a new feature that allows users to import Prometheus-style alerts and recording rules into Grafana-managed alerts directly through the UI, streamlining the migration process without the need to rewrite existing rules. This functionality enhances compatibility with existing workflows and provides access to Grafana's additional alerting features while preserving the original behavior of Prometheus alerts. Users can easily manage and control the import process, making it easier to transition to Grafana's alerting system.
Amazon CloudWatch now supports resource tags for monitoring vended metrics, allowing DevOps engineers to create dynamic monitoring views aligned with their organizational structure. This tag-based telemetry experience simplifies the management of alarms and metrics, enabling faster insights and reducing manual overhead after deployments. The feature is available in multiple AWS regions and can be enabled easily through the CloudWatch Settings or AWS CLI.
Effective cross-agent communication in agentic AI applications, particularly those built on Amazon Bedrock, relies on standardized telemetry and observability practices. By implementing OpenTelemetry solutions and monitoring mechanisms, organizations can enhance AI agent performance, ensure compliance, and streamline debugging processes. Best practices for observability, including secure communication and continuous feedback, are essential for optimizing the functionality of AI agents at scale.
A significant AWS outage on October 19-20, 2025, caused by a DNS failure in the DynamoDB API, led to widespread disruptions across over 140 AWS services, affecting major platforms and clients. The incident highlights the importance of observability in quickly detecting and resolving such failures, emphasizing that organizations using Full-Stack Observability can mitigate financial losses and improve response times during outages. Effective monitoring and real-time visibility into service impacts are crucial for managing risks in cloud environments.
Setting up a local Langfuse server with Kubernetes allows developers to manage traces and metrics for sensitive LLM applications without relying on third-party services. The article details the necessary tools and configurations, including Helm, Kustomize, and Traefik, to successfully deploy and access Langfuse on a local GPU cluster. It also provides insights on managing secrets and testing the setup through a Python container.
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AWS Lambda requires careful consideration for observability due to its serverless nature, which complicates monitoring and debugging. This guide explores the challenges of implementing OpenTelemetry with AWS Lambda, offers insights into instrumentation methods like AWS Distro for OpenTelemetry (ADOT) and custom SDKs, and discusses deployment options for telemetry data collection, all while emphasizing the importance of understanding the Lambda execution lifecycle.
The Anthropic integration for Grafana Cloud allows users to monitor Claude large language model usage and costs by connecting directly to the Anthropic Usage and Cost API. This integration offers real-time insights, pre-built dashboards, customizable alerts, and no need for additional collectors, enabling organizations to optimize performance and manage expenses effectively.
The blog post discusses the integration of Prometheus and OpenTelemetry, emphasizing the importance of user experience research in observability tools. It highlights the benefits of leveraging OpenTelemetry to enhance monitoring capabilities and improve user satisfaction in software development and operations.
Octopus has introduced the Kubernetes Live Object Status feature to enhance its Kubernetes agent, enabling simplified deployments and robust post-deployment monitoring for applications running on Kubernetes. This feature allows users to view the status of Kubernetes resources in real-time and provides detailed insights for troubleshooting, aiming to streamline the continuous delivery process.
The article discusses the OpenTelemetry Protocol (OTLP) Metrics API, which provides a unified way to collect, transmit, and manage metrics data across various systems. It highlights the benefits of using OTLP for observability and monitoring, emphasizing its role in enhancing application performance and reliability. Additionally, the article outlines implementation details and best practices for leveraging the API effectively.
Understanding and troubleshooting NGINX errors is crucial for maintaining web server performance and security. The guide outlines common causes of NGINX errors, methods to check and fix them, and best practices for preventing future issues. It also emphasizes the importance of monitoring and updating NGINX for optimal performance.
Building a cloud security roadmap is essential for organizations to effectively manage and mitigate risks associated with cloud environments. The article outlines key components of such a roadmap, including risk assessment, compliance considerations, and the importance of continuous monitoring and improvement. It emphasizes the need for a strategic approach to ensure robust cloud security practices are in place.
GitHub engineers address platform challenges by leveraging a range of engineering practices and tools, ensuring system reliability and performance. They implement proactive monitoring, systematic troubleshooting, and scalable solutions to enhance user experience while maintaining platform integrity. Continuous improvement and collaboration among teams are key aspects of their approach to tackling complex issues.
OpenCVE is a powerful Vulnerability Intelligence Platform that streamlines the monitoring and management of CVEs by aggregating data from various sources. Users can filter, track, and organize vulnerabilities efficiently, receive alerts, and collaborate with their teams through a user-friendly interface. It offers features like customizable tags, reusable views, and the ability to generate reports and dashboards for better oversight.
The Amazon Product Search team shares their journey of transitioning from traditional threshold-based monitoring to Service Level Objectives (SLO) monitoring using CloudWatch Application Signals. Part 1 focuses on the limitations of conventional monitoring methods and the benefits of SLOs in detecting significant issues while reducing false alarms, leading to improved system observability and reliability.
Somo is a user-friendly alternative to netstat for monitoring sockets and ports on Linux and macOS, offering features like filtering, sorting, and JSON output. It provides interactive capabilities to kill processes and can be installed using various package managers or built from source. The tool supports shell completions and allows customization via config files for repeated commands.
The article discusses Datadog's datastore capabilities, highlighting its ability to monitor, analyze, and visualize data from various sources. It emphasizes the importance of real-time data insights for improving application performance and user experience in cloud environments. Key features and integration options are also outlined to showcase how Datadog can enhance observability.
The Okta Security Detection Catalog is a comprehensive repository of detection rules and log field descriptions aimed at enhancing security monitoring for Okta customers. It includes YAML files for security detections, threat hunting queries, and templates for incident response workflows. The catalog emphasizes the importance of using the System Log for tracking events and recommends strategies for optimizing detection effectiveness.
The article discusses the risks associated with unmonitored JavaScript in web applications, highlighting how it can lead to security vulnerabilities and exploitation by malicious actors. It emphasizes the importance of monitoring and controlling JavaScript usage to safeguard user data and maintain the integrity of web platforms.
Microsoft has introduced container network logs in the public preview of Advanced Container Networking Services for Azure Kubernetes Service, providing detailed insights into network traffic. This feature enhances troubleshooting, security enforcement, and operational efficiency by monitoring various traffic layers and offering two modes of log storage. Users can visualize logs through Azure managed Grafana dashboards for better analysis and monitoring.
The article discusses the importance of understanding network paths for optimizing application performance and reliability. It emphasizes how monitoring and analyzing network routes can help identify issues and improve overall network health. Practical insights and tools for tracking these pathways are also highlighted.
The article discusses the development of a monitoring tool for Bash's readline function using eBPF CO-RE, which allows for portability across kernel versions without recompilation. It details the architecture of the eBPF program, its user-space loader, and the handling of telemetry data, highlighting how LLMs facilitated the coding process. The end result is a robust solution for tracking Bash commands with flexible output options.
Memory usage in Prometheus can escalate dramatically in enterprise Kubernetes environments due to high-cardinality metrics and labels. This article details methods to analyze and reduce memory consumption effectively, including identifying redundant metrics and employing scripts to optimize monitoring without losing essential data.
By implementing a php-fpm-exporter in a Kubernetes environment, the author identified severe underutilization of PHP-FPM processes due to a misconfigured shared configuration file. After analyzing the traffic patterns and adjusting the PHP-FPM settings accordingly, memory utilization was reduced by over 80% without sacrificing performance. The article emphasizes the importance of customizing configurations based on specific application needs rather than relying on default settings.
Tail latency, or high-percentile latency, significantly impacts user experience in modern architectures with multiple service calls. As the number of parallel calls increases, the likelihood of encountering high-latency responses rises, making it crucial to monitor and understand latency statistics beyond just the mean. Effective monitoring should include awareness of high percentiles and consider customer use cases to capture the full picture of service performance.
Uptime Labs shares insights from a recent incident caused by a framework patch that led to a platform outage. The team emphasizes the importance of maintaining a fast delivery rhythm while learning from failures to improve monitoring, testing, and incident response processes.
The article discusses strategies for implementing safe changes in large-scale systems, highlighting the importance of testing, monitoring, and gradual rollouts to minimize disruption. It emphasizes the need for robust processes to ensure reliability and maintain user trust during updates.
Security Onion 2.4 has been released, providing users with updated features and improvements for enhanced security monitoring. The release includes comprehensive documentation covering installation, hardware requirements, and community support resources. Users can access the release notes and download the latest version through the provided links.
Stay updated with real-time tracking of AWS documentation changes and security updates. This service allows users to monitor modifications across all AWS services to remain informed about critical security developments.
Continuous profiling is emerging as a critical practice in software development, complementing established pillars like monitoring, alerting, and logging. By providing detailed insights into application performance in real-time, it helps developers identify and resolve performance bottlenecks efficiently. This approach fosters a deeper understanding of application behavior, enhancing overall system reliability and user experience.
Maltrail is a malicious traffic detection system that utilizes various blacklists and heuristic mechanisms to identify and report suspicious activities such as malware and unauthorized access attempts. It operates on a sensor-server-client architecture, allowing for real-time monitoring and logging of network traffic, and can be set up easily on Linux systems or via Docker. The system supports extensive customization through user-defined lists and integrates various data sources for comprehensive threat detection.
The article discusses optimizing AI proxies using Datadog, highlighting how Datadog's monitoring tools can enhance performance and reliability in AI systems. It emphasizes the importance of observability in managing AI workloads and provides insights into best practices for effective monitoring and troubleshooting.
MCP Snitch is a macOS application designed for security monitoring and access control of Model Context Protocol (MCP) servers, enabling users to intercept and analyze server communications. It offers features like automatic server discovery, risk assessment, granular control over tool calls, and audit logging, while leveraging AI for threat detection and response monitoring. The application supports secure key storage and compliance through detailed logging of all interactions with MCP tools.
Organizations can enhance their cloud network management by using AWS Transit Gateway Flow Logs and Amazon Managed Grafana for centralized monitoring and visualization. This setup allows users to analyze traffic patterns, troubleshoot issues, and ensure compliance through detailed insights into network traffic stored in Amazon S3. The article provides a step-by-step guide for deploying a Grafana dashboard to visualize these logs effectively.
Errors in modern distributed systems can lead to significant business losses due to prolonged downtimes. A structured approach to error analysis, leveraging observability tools like New Relic, enables teams to transition from symptom-driven responses to effective root cause investigations, ultimately reducing mean time to recovery (MTTR) and improving system reliability.
The article discusses a memory regression issue encountered during the development of a Go application, highlighting the steps taken to identify and resolve the problem. It emphasizes the importance of monitoring memory usage and provides insights into debugging techniques used to tackle the regression effectively.
Micro outages can create blind spots in observability stacks, leading to undetected issues that affect user experience and system performance. Organizations need to enhance their monitoring strategies to identify and address these micro outages effectively, ensuring robust system reliability and user satisfaction.
New Relic has announced support for the Model Context Protocol (MCP) within its AI Monitoring solution, enhancing application performance management for agentic AI systems. This integration offers improved visibility into MCP interactions, allowing developers to track tool usage, performance bottlenecks, and optimize AI agent strategies effectively. The new feature aims to eliminate data silos and provide a holistic view of AI application performance.
COMmander is a lightweight C# tool designed to enhance defensive telemetry for RPC and COM by utilizing the Microsoft-Windows-RPC ETW provider to monitor system events based on user-defined detection rules. It operates by reading a configuration file to filter and detect specific RPC events, while logging relevant information in the Windows Event Viewer. Installation and uninstallation processes are straightforward, requiring administrator privileges for executing PowerShell scripts.
AI-powered metrics monitoring leverages machine learning algorithms to enhance the accuracy and efficiency of data analysis in real-time. This technology enables organizations to proactively identify anomalies and optimize performance by automating the monitoring process. By integrating AI, businesses can improve decision-making and resource allocation through better insights into their metrics.
Sentry provides comprehensive monitoring and debugging tools for AI applications, enabling developers to quickly identify and resolve issues related to LLMs, API failures, and performance slowdowns. By offering real-time alerts and detailed visibility into agent operations, Sentry helps maintain the reliability of AI features while managing costs effectively. With easy integration and proven productivity benefits, Sentry is designed to enhance developer efficiency without sacrificing speed.
Amazon CloudWatch Application Signals has introduced enhanced features that simplify monitoring of large-scale distributed applications. New capabilities include automatic service grouping based on relationships, contextual troubleshooting tools, and integration with CloudWatch Investigations, enabling faster root cause analysis and reducing operational maintenance time.
Learn how to monitor your Prusa 3D printer using Grafana by leveraging prusa_exporter and Prometheus to visualize printer metrics and set alerts. This setup allows for efficient offline monitoring, even in environments with network restrictions, and offers customization for both hobbyists and developers. The article also discusses challenges in data processing due to the limited resources of embedded systems.
Cloud Snitch is a powerful tool designed to enhance your understanding of AWS account activity, providing an intuitive interface for exploring and documenting AWS principals, IP addresses, and network activity. It helps users quickly identify errors and suspicious behavior, while also allowing for the generation and management of service control policies to enforce security compliance. Open-sourced under the MIT license, it can be deployed easily or used through cloudsnitch.io.
Monitor and visualize the performance of various LLM APIs over time to identify regressions and quality changes, particularly during peak load periods. By comparing different models and providers, users can proactively detect issues that may impact production applications.
The article discusses the importance of enhancing security and performance in Internet of Things (IoT) networks by analyzing decrypted Zigbee traffic data. It highlights the vulnerabilities in Zigbee protocols and offers insights into how improved monitoring and security measures can protect IoT devices from potential threats.
Atla is a unique evaluation tool designed for developers that not only identifies issues within agents but also provides detailed insights on how to resolve them quickly. It enables real-time monitoring, automatic clustering of failure patterns, and systematic improvements, ensuring enhanced user experiences without introducing new problems. Users can confidently deploy changes by comparing performance across different versions of their agents.
Monitoring the performance of LiteLLM with Datadog provides users with enhanced visibility into their machine learning models. By integrating Datadog's observability tools, developers can track key metrics and optimize the efficiency of their language models, leading to improved system performance and user experience. This setup enables proactive identification of issues and facilitates better decision-making based on real-time data insights.
The article provides a comprehensive guide on mastering Docker logs, detailing how to efficiently manage and analyze logs generated by Docker containers. It covers various logging drivers, commands for viewing logs, and best practices for log management to enhance troubleshooting and monitoring processes.
The article discusses the importance of effective spam filters in managing observability budgets. It highlights how a point-and-click approach can simplify the process of configuring filters, ensuring that organizations stay within their budget while effectively monitoring their systems. The content emphasizes practical strategies for optimizing spam filtering to enhance overall observability.
Harvey's AI infrastructure effectively manages model performance across millions of daily requests by utilizing active load balancing, real-time usage tracking, and a centralized model inference library. Their system prioritizes reliability, seamless onboarding of new models, and maintaining high availability even during traffic spikes. Continuous optimization and innovation are key focuses for enhancing performance and user experience.
Devpush is an open-source platform that serves as a self-hostable alternative to services like Vercel and Netlify, enabling users to build and deploy applications in various languages with features such as zero-downtime updates, real-time logs, and team management. It supports Git-based deployments and customizable environments, making it suitable for developers looking for a flexible deployment solution on their own servers.
The article discusses the importance of securing Continuous Integration and Continuous Deployment (CI/CD) workflows using Wazuh, an open-source security monitoring platform. It highlights the key features and benefits of integrating Wazuh to enhance security in software development processes, ensuring compliance and protection against vulnerabilities.
The article discusses the need for a new approach to observability in the context of artificial intelligence (AI) systems. It emphasizes that traditional methods of monitoring and managing software are inadequate for the complexities introduced by AI, calling for innovative strategies to effectively track and understand AI behaviors and performance.
The article provides a comprehensive overview of file integrity monitoring (FIM), explaining its importance in cybersecurity and compliance. It outlines key features, benefits, and best practices for implementing FIM solutions to protect sensitive data and maintain system integrity.
Sharing a single Redis cache cluster across multiple services can lead to significant issues, such as key eviction affecting all services, complicating monitoring and debugging processes. While it may seem simpler initially, this approach can create confusion and performance problems as the system scales. In some cases, a shared cache is acceptable, but it's often better to maintain separate clusters for improved reliability and clarity.
The article focuses on core KPIs for tracking the performance of large language models (LLMs), emphasizing the importance of measuring metrics that reflect model efficiency, user engagement, and overall effectiveness. It outlines various methods and tools for monitoring these metrics to enhance the performance and usability of LLMs in different applications.
Falco is a cloud native runtime security tool for Linux that monitors real-time events and detects potential threats using custom rules. Originally developed by Sysdig and now maintained under the Cloud Native Computing Foundation, it integrates with container runtimes and Kubernetes, offering features like a command-line utility, plugins, and a structured codebase across multiple repositories. The project encourages community involvement and provides comprehensive documentation for setup and contributions.
The article discusses the importance of data lineage monitoring in Apache Airflow, emphasizing how it helps organizations track data flow and maintain data integrity throughout their workflows. It highlights the role of tools and best practices in implementing effective data lineage strategies to enhance visibility and compliance.
Developer environments are increasingly vulnerable to security risks due to the rise of agentic coding assistants, which interact with systems in complex ways that can introduce malicious code and escalate privileges. The lack of built-in security features in Model Context Protocol servers and rules files exacerbates these risks, leading to potential supply chain attacks. To mitigate these threats, organizations should implement traditional best practices such as sandboxing, supply chain scrutiny, and enhanced monitoring of coding assistant workflows.
The article discusses the process of monitoring an Uninterruptible Power Supply (UPS) using Network UPS Tools (NUT) along with Telegraf and Grafana for visualization and alerting. It details the installation and configuration steps for NUT and Telegraf, allowing users to collect metrics from their UPS and monitor their power supply effectively. The author shares personal experiences that led to setting up this monitoring system following a brief power outage.
Qriton's hopfield-anomaly package provides a production-ready Hopfield Neural Network designed for real-time anomaly detection with features like adaptive thresholds and energy-based scoring. The package supports various configurations for tuning detection to specific domains and includes performance profiling tools. It is suitable for diverse use cases, including IoT monitoring, network security, and financial data analysis.
The article describes the GitHub repository for the "monitoring-stack," a Docker Compose setup designed for monitoring planar applications using OpenTelemetry. It includes components like Grafana, Prometheus, and Loki for visualizing metrics and logs, and provides instructions for setting up and accessing the stack.