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Writing SQL queries is straightforward, but creating a reliable system for running them efficiently is complex and often results in poor data quality and operational inefficiencies. Transitioning from ad-hoc scripts to a structured, spec-driven architecture enhances reproducibility, validation, and observability of SQL jobs, ultimately leading to better management of data and costs.
Grafana Assistant is an AI-powered tool now available in public preview for Grafana Cloud users, designed to streamline the onboarding process for teams using the platform. It aids users in learning observability concepts, comparing features from different tools, and providing context-aware answers to enhance their experience. By offering tailored guidance and interactive tutorials, Grafana Assistant aims to help users quickly and effectively adopt Grafana for their observability needs.
Explore the essential tools and technical guidance for enhancing observability and application performance monitoring (APM) on AWS. The article highlights free-to-try observability tools that integrate seamlessly with AWS workflows, emphasizing the importance of monitoring capabilities in Site Reliability Engineering (SRE) and offering a pay-as-you-go pricing model for scalable use.
Durable queues enhance the reliability of distributed task processing by checkpointing tasks in a persistent store, allowing recovery from failures without data loss. They provide built-in observability and are particularly beneficial for larger, critical tasks, despite potential performance tradeoffs compared to traditional in-memory message brokers. As their popularity grows, durable queues are becoming essential for robust workflow orchestration in applications like Reddit.
Implementing usage and security reporting for Amazon ECR enhances observability of container registries by generating comprehensive reports that detail repository and image-level metrics. These reports help identify unused resources, track security vulnerabilities, and optimize costs through actionable insights. The article provides a hands-on walkthrough for generating these reports using sample code and AWS tools.
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 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.
AI delivery requires a well-structured approach akin to baking a cake, where each ingredient represents a crucial element such as CI/CD pipelines, observability, and governance. Real-world case studies illustrate the consequences of neglecting these components, emphasizing the importance of discipline and integration in developing reliable AI systems.
The article discusses the benefits of end-to-end observability in software systems, highlighting how it enhances performance monitoring, troubleshooting, and overall user experience. It emphasizes the importance of having a comprehensive view of application behavior across various components to improve operational efficiency and reduce downtime.
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.
Observability in applications comes with instrumentation overhead, which can impact performance and resource consumption. A benchmark of OpenTelemetry in a Go application revealed a CPU usage increase of about 35% and some additional memory usage, while still maintaining stable throughput. For teams prioritizing incident resolution, the tradeoff for detailed observability is often justified, though eBPF-based instrumentation offers a lighter alternative for monitoring without significant resource costs.
SolarWinds has launched a new incident response tool that enhances its observability platform with advanced AI capabilities. This development aims to improve the efficiency of IT teams in managing and responding to incidents, ultimately boosting operational resilience.
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.
Chronon simplifies data computation and serving for AI/ML applications by allowing users to define features from raw data and perform batch and streaming computations. It ensures low-latency serving, guaranteed correctness, and consistency, while providing tools for observability and monitoring, making it easier for ML practitioners to leverage organizational data without complex orchestration. The platform includes an API for real-time feature fetching and supports scalable backfills for model training and evaluation.
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.
Amazon ElastiCache now supports Valkey 8.1, introducing new features such as native Bloom filter support, enhanced hash table implementation, and the COMMANDLOG feature for improved performance and observability. These updates aim to enhance application responsiveness while reducing infrastructure costs. The new version is available at no extra cost and allows for easy upgrades without downtime.
eBPF (extended Berkeley Packet Filter) is emerging as a transformative technology for cloud-native applications, enabling developers to execute code in the kernel without modifying the kernel itself. This capability enhances performance, security, and observability in cloud environments, positioning eBPF as a critical component in the next phase of cloud-native development.
Grafana Labs is inviting participants to take part in their fourth annual Observability Survey, aimed at understanding the current state of observability in the industry. The survey will explore topics such as AI's role, open standards, and community satisfaction, with participants having a chance to win swag as a thank you for their input. Results will be shared transparently, allowing for community interaction with the data.
Modern observability is essential for developers, enabling them to understand code behavior in production and improve performance and reliability. By integrating observability into development workflows, developers can gain real-time insights, trace issues efficiently, and enhance collaboration across teams. The right observability tools help streamline the debugging process and reduce the cognitive load on developers.
Understanding Prometheus labels is crucial for enhancing observability in systems, as they provide essential context to metrics, enabling better filtering, aggregations, and insights. Best practices for using labels effectively include filtering metrics by attributes, aggregating by status codes, and implementing multi-dimensional monitoring to assess application and infrastructure health.
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.
The article discusses how to visualize distributed traces using Datadog's tracing capabilities, particularly focusing on the integration of distributed maps with AWS Step Functions. It emphasizes the importance of monitoring complex workflows and how these visualizations can enhance observability and troubleshooting in microservices architectures.
Grafana has updated its Prometheus data source to better align with specific cloud services, deprecating AWS and Microsoft Azure authentication in favor of dedicated plugins for Amazon and Azure. This move reflects Grafana's commitment to a "big tent" philosophy, emphasizing interoperability and tailored solutions for diverse observability tools while continuing to support the open-source community.
Observability is increasingly recognized as essential not only for Site Reliability Engineers (SREs) but for all teams involved in software development and operations. By integrating observability practices across various roles, organizations can enhance collaboration, improve system performance, and enable proactive problem-solving. This shift helps teams respond more effectively to issues and fosters a culture of continuous improvement.
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.
Observability in software development should prioritize error tracking over traditional logs, metrics, and traces, as exceptions provide the clearest indication of failures in the code. By focusing on capturing detailed context around errors, developers can gain invaluable insights that are often lost in the noise of standard observability practices. The author argues that the current approach to observability tends to downplay the importance of errors, which should be treated as first-class signals when diagnosing issues.
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.
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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.
Grafana Cloud Traces now supports the Model Context Protocol (MCP), enabling users to leverage LLM-powered tools like Claude Code for enhanced analysis of tracing data. This integration simplifies the exploration of service interactions and helps in diagnosing issues by providing actionable insights from distributed tracing data. A step-by-step guide is included for connecting Claude Code to Grafana Cloud Traces.
Consolidating observability tools can significantly enhance the effectiveness of site reliability engineers by reducing cognitive overload, training overhead, and budget bloat associated with tool sprawl. While challenges exist, such as conflicting team requirements and resource constraints, practical steps like auditing current tools, prioritizing integration, and leveraging unified platforms can lead to a more efficient observability approach. Ultimately, a well-consolidated toolkit not only improves incident response times and collaboration but also facilitates innovation in system management.
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.
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.
TELUS transformed its IT operations by adopting Dynatrace's observability tools, enabling a shift from reactive to proactive monitoring of customer experiences. This approach improved application performance and resilience, particularly during critical sales events like Black Friday, allowing teams to visualize and address issues in real time, ultimately enhancing customer satisfaction and driving business success.
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.
Northflank simplifies the deployment of applications and databases by providing a powerful platform that eliminates the need for complex integrations and DevOps management. It offers built-in CI/CD pipelines, environment orchestration, and observability features, allowing developers to focus solely on writing code while managing workloads across various cloud providers. With enhanced security and user experience features, Northflank is positioned as an ideal solution for modern development needs.
The article discusses the financial aspects of implementing observability tools and strategies within organizations. It emphasizes the importance of balancing cost with the value derived from observability in enhancing system performance and reliability. The content is segmented into multiple parts, with this entry focusing on initial considerations for spending on observability solutions.
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.
Grafana Labs has introduced new data sources to enhance its observability platform, allowing users to visualize and analyze data from various applications and databases, including Amazon Aurora, Zendesk, and Azure CosmosDB. These updates, showcased at GrafanaCON 2025, aim to unify data querying and visualization from disparate systems within a centralized Grafana dashboard.
The Cloud Native Computing Foundation (CNCF) has announced the Open Observability Summit, a one-day event scheduled for June 26, 2025, in Denver, aimed at advancing open source observability tools and practices. The summit will facilitate collaboration among observability leaders and practitioners, highlighting innovations, scalability challenges, and community-driven development in the field. Proposals for talks are currently being accepted until May 11, 2025.
Organizations are struggling with the high costs of traditional log management solutions like Splunk as data volumes grow, prompting a shift towards OpenSearch as a sustainable alternative. OpenSearch enhances log analysis through its Piped Processing Language (PPL) and Apache Calcite for enterprise performance, while unifying the observability experience for users. The platform aims to empower teams with advanced analytics capabilities and community-driven development.
The article discusses the integration of Claude AI with OpenTelemetry for enhanced code monitoring and observability. It explores how this combination can improve performance insights and debugging capabilities in software development environments. The benefits of using OpenTelemetry with Claude include better tracking of application behavior and issues in real-time.
The article discusses how to enable the display of a million spans in the trace details page of an observability tool, enhancing the user experience by providing comprehensive insights into system performance. It highlights the technical challenges faced and the solutions implemented to efficiently manage and visualize large amounts of trace data.
The article discusses the importance of data lineage in enhancing strategic decision-making beyond mere observability. It emphasizes how understanding data flow and transformations can improve data governance, compliance, and overall data quality within organizations. Additionally, it advocates for integrating data lineage into broader business strategies to leverage data effectively.
DigitalOcean has introduced three key advancements to enhance observability for its Managed Databases, including integration with Datadog for log forwarding, default resource alerts for critical thresholds, and advanced cluster event notifications. Additionally, a new feature for labeling trusted IP sources improves database management and security. These updates aim to simplify monitoring and enhance operational awareness for users.
Observability in applications introduces instrumentation overhead that can impact performance, particularly when using OpenTelemetry with Go. A benchmark comparing a Go HTTP server's performance with and without OpenTelemetry revealed a notable increase in CPU and memory usage, but maintained stable throughput. The choice of observability method should balance the need for detailed tracing against resource costs, with eBPF-based instrumentation offering a more lightweight alternative for high-load environments.
Effective data quality evaluation is essential for making informed decisions and involves a six-step framework. By defining clear goals, ensuring appropriate data sources, identifying anomalies, and using data observability tools, individuals can enhance the trustworthiness of their data and avoid the pitfalls of poor data quality.
KubeCon EU 2025 in London attracted over 13,000 attendees and highlighted significant advancements in cloud-native technologies, observability, and security. Key trends included the integration of AI and large language models with Kubernetes, the rise of platform engineering to manage complexity, and an emphasis on making observability more accessible. Dynatrace showcased its contributions to the cloud-native community, reinforcing its commitment to innovation in this rapidly evolving field.
Banks are increasingly unifying observability and security to enhance operational resilience and reduce risks associated with downtime and security breaches. By integrating system monitoring and threat detection, institutions like Wells Fargo and Bank Leumi have significantly improved their threat response times and reduced monitoring costs. This approach enables deeper insights and faster responses, ultimately benefiting customer trust and regulatory compliance.
The article discusses how to monitor agentic AI applications using Amazon CloudWatch, highlighting the importance of observability for ensuring reliability and performance. It details the setup of a sample Weather Forecaster application built with Strands Agents SDK, which utilizes CloudWatch to collect telemetry data, including metrics, traces, and logs, for comprehensive analysis. Additionally, it provides a step-by-step guide for deploying the application and analyzing the generated telemetry data in the CloudWatch console.
New Relic introduces Fleet Control and Agent Control, two capabilities designed to streamline the management of instrumentation across Kubernetes clusters. These tools provide centralized operations, enabling teams to easily monitor, configure, and update agents, minimizing manual work and eliminating telemetry blind spots. Users can create and manage fleets, ensuring consistent and up-to-date instrumentation with a simplified interface.
Goutham Veeramachaneni discusses how Beyla, an open-source eBPF-based instrumentation tool, simplifies monitoring in homelabs by providing consistent observability across diverse applications without requiring extensive manual coding. By leveraging eBPF and OpenTelemetry, Beyla enables users to collect telemetry data effortlessly, making it easier to address challenges in observability for both personal and production environments.
Grafana Beyla, an open source eBPF-based auto-instrumentation tool, can be integrated with Amazon ECS to enhance application observability without modifying application code. The article details the configuration steps necessary to run Beyla as a sidecar in ECS tasks, specifically leveraging Grafana Alloy for telemetry data management, enabling deep visibility into containerized workloads.
Grafana Cloud introduces a new approach to observability by shifting from traditional pillars of logs, metrics, and traces to interconnected rings that optimize performance and reduce telemetry waste. By combining these signals in a context-rich manner, Grafana offers opinionated observability solutions that enhance operational efficiency, lower costs, and provide actionable insights. The article also highlights the integration of AI to further improve observability workflows and decision-making.
OpenTelemetry is an open-source observability framework designed to provide a standardized way to collect, process, and export telemetry data such as traces, metrics, and logs. It aims to help developers and organizations gain insights into their systems' performance and behavior, facilitating better monitoring and troubleshooting. By integrating with various backend systems, OpenTelemetry enhances observability across diverse environments and applications.
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.
Dynatrace's video discusses the challenges organizations face when adopting AI and large language models, focusing on optimizing performance, understanding costs, and ensuring accurate responses. It outlines how Dynatrace utilizes OpenTelemetry for comprehensive observability across the AI stack, including infrastructure, model performance, and accuracy analysis.
The article discusses a user story related to Tetragon, a security observability tool for cloud-native applications. It highlights how Tetragon enhances security and monitoring capabilities in a social networking application, demonstrating its effectiveness in real-world scenarios. Key features and integrations of Tetragon are also explored, emphasizing its role in maintaining application integrity and compliance.
The article discusses the escalating costs associated with observability in software systems, highlighting the challenges organizations face in managing these expenses effectively. It emphasizes the need for balance between gathering insights and maintaining budgetary constraints to avoid financial strain. Solutions and strategies for optimizing observability costs are also explored.
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.
OpenAI utilizes ClickHouse for its observability needs due to its ability to handle petabyte-scale data efficiently. The article highlights the advantages of ClickHouse, such as speed, scalability, and reliability, which are crucial for monitoring and analysis in large-scale AI operations. It discusses how these features support OpenAI's goals in data management and performance monitoring.
Data and AI leaders are prioritizing three key challenges for 2025: enhancing team productivity through AI adoption, ensuring the reliability of AI applications, and driving overall AI adoption within organizations. Addressing these issues involves operationalizing incident management, creating AI-ready data, and fostering trust in AI systems to ensure their successful integration into business processes.
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.
Knock AI offers an advanced customer engagement platform that utilizes natural language for seamless interaction across various channels. The Knock Agent Toolkit enables developers to build efficient agent-to-user messaging workflows, ensuring safety and visibility through features like human-in-the-loop processes, observability, and version control. It is designed to integrate with major SDKs, allowing for streamlined migration and AI-assisted operations.
Grafana Beyla 2.5 introduces significant updates built on OpenTelemetry eBPF Instrumentation, including support for MongoDB protocols, JSON-RPC for Go applications, manual span capabilities, enhanced NodeJS distributed tracing, and a new survey mode for service discovery. These features aim to improve observability and maintain compatibility within the OpenTelemetry ecosystem while allowing community contributions.
Arc is a high-performance time-series database capable of ingesting 2.4 million metrics per second, along with logs, traces, and events using a unified MessagePack columnar protocol. Currently in alpha release, it features a stable core with ongoing developments, including advanced SQL analytics via DuckDB, flexible storage options, and built-in token-based authentication, making it suitable for development and testing environments. The system is designed for high-throughput ingestion, low latency, and efficient data management, aiming to support observability across various telemetry types.
The Octopus Datadog integration enhances the visibility and observability of CI/CD pipelines by allowing users to monitor Octopus deployments through the Datadog Agent. This integration enables teams to correlate data across their entire software delivery stack, improving troubleshooting and recovery times while supporting both modern and legacy systems. It provides a centralized view of performance metrics, logs, and alerts, facilitating faster issue resolution and more efficient deployments.
Dynatrace offers advanced observability solutions that enhance troubleshooting and debugging across cloud-native and AI-native applications. The platform utilizes AI for real-time analysis of logs, traces, and metrics, enabling developers to optimize workflows and improve performance with minimal configuration. Users can seamlessly integrate Dynatrace into their existing tech stack, significantly accelerating issue resolution and enhancing user experience.
Sentry has announced the general availability of its logging feature, which allows developers to collect, analyze, and manage logs seamlessly alongside their error tracking. This integration enhances observability and simplifies the troubleshooting process by providing a unified view of application health and performance. The new feature aims to improve developers' workflows and enhance their ability to monitor and respond to issues effectively.
Learn how to utilize OpenTelemetry tracing through an interactive grand strategy game called Game of Traces, designed to help engineers grasp observability concepts. Players capture villages and manage resources while tracking interactions between services, showcasing how traces reveal the state of operations within a microservice architecture. The game leverages the Grafana LGTM Stack to illustrate telemetry signals in action.
Running AI workloads on Kubernetes presents unique networking and security challenges that require careful attention to protect sensitive data and maintain operational integrity. By implementing well-known security best practices, like securing API endpoints, controlling traffic with network policies, and enhancing observability, developers can mitigate risks and establish a robust security posture for their AI projects.
Zeta, a core banking technology provider, improved its incident response times by over 80% by implementing a unified observability solution using Amazon OpenSearch Service. The new system, known as Customer Service Navigator (CSN), enhances operational visibility across their multi-tenant architecture, enabling faster troubleshooting and compliance with regulatory requirements. Key features include real-time monitoring and streamlined data ingestion from various AWS services, significantly reducing mean time to resolution for incidents.
Dynatrace has introduced the Live Debugger, a cloud-native tool designed to enhance debugging in production environments by providing real-time access to code-level data without disrupting operations. This tool allows developers to quickly troubleshoot issues by setting non-breaking breakpoints and collecting debug data, improving efficiency and reducing reliance on traditional debugging methods. Live Debugger is currently in preview and aims to support modern development challenges with a focus on security and observability.
Users are encouraged to retry later due to an invalid reference code. Additionally, an email notification will be sent once the user's environment is ready, and options for starting a free trial or requesting a demo of the Dynatrace platform are available.
Character.AI has transformed its fragmented logging system into a centralized one, significantly improving query speeds and enabling real-time visibility for developers. By selectively capturing logs and introducing new features like live tailing and keyword search, the company aims for metric unification to enhance observability and support future growth.
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.
Sentry streamlines the debugging process by providing clear insights and actionable solutions rather than overwhelming users with data. With features like error alerts, real user session playback, and automated issue assignment, it enhances developer productivity and accelerates incident resolution, allowing teams to focus on fixing problems quickly.
New Relic has announced the general availability of Fleet Control and Agent Control, designed to streamline the management of observability agents across various IT environments. This unified control plane aims to reduce operational overhead and security risks by automating the observability lifecycle, enabling consistent configurations and efficient deployments from a single interface. The platform also supports both Kubernetes clusters and host-based environments, enhancing its capabilities for enterprise-scale observability management.
Google Cloud has improved its Trace Explorer UI, enhancing the distributed tracing experience for developers and SREs. The new features include a comprehensive filter bar, interactive visualizations, and detailed span analysis tools that facilitate troubleshooting of application latency and errors. This update leverages BigQuery for advanced querying capabilities and is now generally available to all users.
Modern infrastructure complexity necessitates advanced observability tools, which can be achieved through cost-effective storage solutions, standardized data collection with OpenTelemetry, and the integration of machine learning and AI for better insight and efficiency. The evolution in observability is marked by the need for high-fidelity data, seamless signal correlation, and intelligent alert management to keep pace with scaling systems. Ultimately, successful observability will hinge on these innovations to maintain operational efficacy in increasingly intricate environments.
Observability is evolving into a crucial component for AI transformation, transitioning from reactive monitoring to a strategic intelligence layer that enhances AI's safety, explainability, and accountability. With significant budget increases and a strong focus on security, organizations are prioritizing AI capabilities in their observability platforms, yet a gap remains in aligning observability data with business outcomes.
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.
IT leaders are progressing along the observability maturity curve, shifting from fragmented tools to unified platforms that drive business outcomes. Key trends include the adoption of service level objectives (SLOs), AI-assisted insights, and a focus on measurable business impact, indicating a growing recognition of observability as essential for modern operations.
Designing effective AI agents requires a modular and role-based architecture, deep observability from the start, and robust feedback loops to ensure continuous improvement. Successful implementation of these principles transforms LLMs from static tools into dynamic, autonomous systems capable of adapting to real-world complexities. Understanding the foundational concepts of agent design can bridge the gap between basic AI applications and more sophisticated, self-improving AI agents.
Utilizing distributed tracing with OpenTelemetry can enhance visibility and performance monitoring in Kafka systems, which are inherently challenging due to their decoupled and asynchronous nature. The article compares zero-code and manual instrumentation approaches, detailing their pros and cons, and demonstrates how to effectively implement each to gain better insights into application performance.
Grafana has introduced new features in Adaptive Logs, including temporary pauses, exemptions, and per-service drop rates, to help users optimize log ingestion while addressing specific needs. These enhancements allow developers to retain critical logs during incidents and provide flexibility in managing log retention for compliance and troubleshooting. The features are currently available in public preview for Grafana Cloud customers, promoting more efficient log management.
k0rdent v1.0.0 has been released, marking a significant milestone with enhanced features for managing distributed infrastructure at scale using Kubernetes. This version focuses on unified observability, cost optimization, and improved operational capabilities through the k0rdent Cluster Manager and Observability & FinOps components, providing production-grade stability and advanced service management. Key highlights include automated IP management, multi-cluster support, and integration with popular observability tools for better resource tracking and financial accountability.
HyperDX is a powerful tool integrated with ClickStack that enables engineers to efficiently search and visualize logs, metrics, and traces on any ClickHouse cluster. It supports full-text search, alert setup, and real-time logging, while also offering compatibility with OpenTelemetry for various programming languages. The platform aims to simplify observability and improve the debugging process for production issues.
Grafana Traces Drilldown is now generally available, offering a queryless experience for tracing data that enables faster root-cause analysis in microservices environments. With features like seamless navigation between metrics and traces, built-in investigative tools, and real-time analysis capabilities, it streamlines the process for incident responders and developers to quickly identify and resolve issues. Recent updates include integrated exemplars and TraceQL streaming for improved user experience and efficiency.
The article critiques the current state of observability in tech, highlighting confusion around metrics, logs, and traces, largely attributed to OpenTelemetry's complex presentation. It advocates for the use of "Wide Events," as exemplified by Meta's Scuba system, which simplifies data collection and analysis, enabling deeper insights into system performance without the need for extensive terminology.
The article discusses the evolution of Cloudflare Radar since its launch in 2020, emphasizing its role in enhancing Internet observability by providing insights into security, performance, and usage trends. It highlights key developments, including the introduction of new data sets related to Certificate Transparency, connection tampering detection, and post-quantum encryption, while maintaining user-friendly access through improved information architecture and APIs.
The article discusses the potential of lakehouses utilizing open table formats like Apache Iceberg and Delta Lake for observability, highlighting their benefits for managing large datasets with improved scalability, cost-effectiveness, and reduced vendor lock-in. It also addresses the challenges and innovations in telemetry at scale, suggesting that these formats could significantly enhance observability workloads in the future.
The Workflow DevKit allows developers to create durable, reliable, and observable asynchronous JavaScript applications using TypeScript. It simplifies the process of building workflows that can suspend and resume tasks, manage state, and integrate seamlessly with existing frameworks. The DevKit emphasizes ease of use with a declarative API and provides out-of-the-box observability features for tracking workflow execution.