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Tag: monitoring

  • Monitoring Apache Kafka infrastructure using New Relic

    One can effectively monitor Apache Kafka infrastructure using New Relic through several methods: 1. Kafka On-Host Integration (Recommended for most self-managed Kafka deployments): 2. Java Agent (for monitoring Java-based Producers and Consumers): 3. OpenTelemetry (for a vendor-agnostic approach): 4. Kafka Connect New Relic Connector (for sending data from Kafka Connect to New Relic): Choosing the… Read more

  • Monitoring Apache Kafka using the ELK stack

    One can effectively monitor Apache Kafka infrastructure using the ELK stack (Elasticsearch, Logstash, Kibana). Here’s a breakdown of how to achieve this: 1. Data Collection: You have a few primary ways to get Kafka-related data into your ELK stack: 2. Data Processing (Logstash – Optional but Powerful): 3. Data Storage (Elasticsearch): 4. Data Visualization and… Read more

  • Kafka Monitoring Tools

    Lets look at various tools to monitor your Apache Kafka deployments. Here’s a breakdown of some popular options, including both open-source and commercial solutions: Key Metrics to Monitor: Before diving into specific tools, it’s important to understand what metrics are crucial for Kafka monitoring: Open-Source Kafka Monitoring Tools: Commercial Kafka Monitoring Tools: Choosing the Right… Read more

  • Automating Customer Communication: Building a Production-Ready LangChain Agent for Order Notifications

    In the fast-paced world of e-commerce, proactive and timely communication with customers is paramount for fostering trust and ensuring a seamless post-purchase experience. Manually tracking new orders and sending confirmation emails can be a significant drain on resources and prone to delays. This article presents a comprehensive guide to building a production-ready LangChain agent designed… Read more

  • Intelligent Order Monitoring Langchain LLM tools

    Building Intelligent Order Monitoring: A LangChain Agent for Database ChecksIn today’s fast-paced e-commerce landscape, staying on top of new orders is crucial for efficient operations and timely fulfillment. While traditional monitoring systems often rely on static dashboards and manual checks, the power of Large Language Models (LLMs) and agentic frameworks like LangChain offers a more… Read more

  • Kafka Disk I/O Tuning Guide

    Disk I/O is a critical bottleneck for Kafka performance. Kafka relies heavily on the file system for storing and retrieving messages, and inefficient disk I/O can lead to increased latency, reduced throughput, and overall system degradation. Here’s a guide to help you tune Kafka for optimal disk I/O performance: 1. Understanding Kafka’s Disk I/O Patterns… Read more

  • Kafka Network Latency Tuning

    Network latency is a critical factor in Kafka performance, especially for applications requiring near-real-time data processing. High network latency can significantly increase the time it takes for messages to travel between producers, brokers, and consumers, impacting overall system performance. Here’s a guide to help you effectively tune Kafka for low network latency: 1. Understanding Network… Read more

  • Kafka CPU Tuning Guide

    Optimizing CPU usage in your Kafka cluster is essential for achieving high throughput, low latency, and overall stability. Here’s a comprehensive guide to help you effectively tune Kafka for CPU efficiency: 1. Understanding Kafka’s CPU Consumption 2. Monitoring CPU Usage 3. Tuning Strategies 4. Best Practices By following these guidelines, you can effectively tune your… Read more

  • Apache Spark

    Let’s illustrate Apache Spark with a classic “word count” example using PySpark (the Python API for Spark). This example demonstrates the fundamental concepts of distributed data processing with Spark. Scenario: You have a large text file (or multiple files) and you want to count the occurrences of each unique word in the file(s). Steps: from… Read more

  • MLOps pipeline

    While a full-fledged MLOps pipeline involves integrating various tools and platforms, here are some illustrative code snippets demonstrating key MLOps concepts using popular Python libraries and tools. These examples focus on individual stages and can be combined to build a more comprehensive pipeline. 1. Data Versioning with DVC (Data Version Control): This isn’t Python code,… Read more