EC2 CloudWatch Metrics Fetch Agent

@corpmember29

Hi There !! After reading your request, I found it to be rather intriguing. I can provide timely, high-quality assistance for your project as a senior full stack engineer. Let's talk further when we speak over the phone or chat. Awaiting for your positive response. Thanks christina

@kareemmaize

Hi there To build this CloudWatch metrics fetch agent reliably, the most critical part is resolving the correct CloudWatch namespace and dimensions for each ECS service, task, or instance before the agent is wired into RCA. I’ll approach this by creating a small Python boto3 collector that can fetch CPU utilization, memory usage, request count, response time, and error rate on demand after each test run. The implementation should support default ECS metrics, ALB/service metrics, and custom namespaces where memory, latency, or error rate are emitted through CloudWatch Agent, Container Insights, or application instrumentation. This means I understand the goal is not a large monitoring platform. It needs a focused, repeatable agent with clear IAM permissions, configurable polling intervals, testable output, comments, Terraform or one-step deployment, and a README your team can maintain. My process starts with metric mapping, then moves into collector code, IAM/Terraform, scheduling setup, local testing, output validation, documentation, and code walkthrough. If it aligns with you, let’s discuss in detail via private chat.

@DeveloperStation

Hi, We’ve built similar agents that pull metrics from AWS and Azure, so we understand the nuances of creating lightweight, reliable solutions. For your project, we can use a serverless approach to minimize costs while ensuring the agent runs continuously and efficiently. We’ve also developed a CI/CD pipeline that automatically deploys code to multiple environments based on Git branch changes, which can be adapted for your use case. Let’s schedule a 10-minute call to discuss your requirements in detail and see if I’m the right fit for this project. I’m eager to learn more about your exciting project. Best regards, Adil

@jinufeb14

Drawing from my extensive experience in developing robust, lightweight agents like the one you require, I assure you that my skills are finely tuned to handle any tasks or updates your project might need. My AI and ML skills can be applied to optimize the agent's polling intervals, boosting data analysis, and ensuring precise metrics returns. As part of my overall service, I'll provide you with a detailed code walkthrough and an easy-to-follow README that doesn't leave you wondering how to operate the agent or test its outputs. As a certified AWS engineer and Python expert adept with boto3, I am capable of creating a small yet highly efficient code that returns exactly what you need: the specific metrics for chosen ECS instances IDs on demand. My highly disciplined approach to coding ensures that clarity is maintained throughout the project; this is reflected in my clear comments within the source code and my commitment to making the most out of every line. The process of deploying and running the agent shouldn't be burdened by complexity; that’s why I'll provide a one-step deployment script or Terraform module that automates all IAM role creation alongisde any policy configurations needed by the agent. My ability to understand complex systems and routinize disperate moving parts will ensure your Root Cause Strategy is realized smoothly and efficiently, exceeding expectations as only a top 1% talent such as myself can deliver.

@Muhammadzeesha59

Hello Sir/MAM I am a skilled full stack developer. Having rich experience in Java , C++ , C , C# , Python , Eclipse , Sql , Mysql , .Net ,Oracle , Object Oriented Programming , Data Structure , Algorithms . I have a perfect grip on “Artificial Intelligence” “Automation” , and work in “Machine Learning” Deep Learning ”. My track record as demonstrated in my 100% job completion and 5-star review rating showcases My ability to deliver exceptional results on time and with utmost quality I believe that my skill set makes me the ideal candidate for this project Please come on chat we will discuss more about this I will be waiting for your reply . Thanks and Best Regards

@gattes

Hi there, I have over 10 years work experience with AWS and python backend programmiing as well as Linux and server management. Ping me and I'll help you out. Cheers!

@mogsten

Hello, Creating a lightweight agent to fetch AWS CloudWatch metrics for your ECS cluster aligns well with my experience in cloud systems and AWS integration. The key challenge here is ensuring reliable data collection from the 15 microservices while handling both default and custom metrics efficiently. It's crucial to implement robust error handling and logging to facilitate root cause analysis, especially in a microservices architecture where dependencies can introduce complexity. In previous projects, I developed similar solutions that involved integrating AWS services with custom scripts, leveraging Python and boto3 for seamless data retrieval. I focused on ensuring that the scripts were lightweight and easily deployable, which aligns with your requirement for a one-step deployment script or Terraform module for IAM roles/policies. My approach would be to first establish the necessary permissions for the agent, then develop the script to fetch and handle the specified metrics, and finally create comprehensive documentation for ease of use and understanding. I look forward to the possibility of contributing to your project by delivering a reliable and efficient metrics fetch agent. Sincerely, Alexander

@bindmission

Hello, I have 10 years of experience in developing cloud infrastructure and monitoring solutions. I can develop a reliable AWS EC2 CloudWatch Metrics Fetch Agent to support your Root Cause Analysis process. This agent will efficiently retrieve CPU, Memory, Request count, Response time, and Error rate metrics across your ECS-hosted microservices. I propose using Python (boto3) or an AWS Lambda function for lightweight, efficient operations. I will deliver well-documented source code, a deployment script or Terraform module for IAM policies, and a comprehensive README. The solution will ensure on-demand metric retrieval as per your acceptance criteria, along with a code walkthrough. Regards, VishnuLal NB*

@riogushiken1114

Hi there, ❤️❤️❤️ I’ve reviewed your project and it aligns well with my experience in Python, boto3, AWS ECS, CloudWatch, and lightweight automation agents. I can help you build a reliable agent that runs after each test run and fetches the required ECS CloudWatch metrics for root cause analysis. How I can help: • Build a Python/boto3 or Lambda-based collector for CPU utilization, memory usage, request count, response time, and error rate • Support both default ECS/CloudWatch statistics and custom metrics via CloudWatch Agent or equivalent setup • Provide IAM/Terraform or one-step deployment, scheduling guidance, polling configuration, and local output testing Relevant experience: I’ve worked on similar AWS monitoring and automation workflows involving ECS, CloudWatch metrics, Lambda, IAM policies, Terraform, and post-test diagnostics, and I can start working immediately. Approach: I focus on clean, maintainable code, clear comments, a practical walkthrough, and a README that makes deployment and operation simple. I’d be happy to discuss your requirements in more detail and get started right away. Best regards,

@kumarashish99

As an AWS-certified professional with a solid background in backend development and DevOps, I am confident that my experience aligns perfectly with your project's requirements. Over the years, I have grown significantly skilled in Python, which is ideal for creating the lightweight agent you require for Root Cause Analysis of your 15 microservices hosted on ECS clusters. In addition to the technical aspects, I take pride in offering clean and well-commented code. This means that apart from delivering a comprehensive README file empowering you to handle polling intervals and test outputs locally, the source code will come with clear comments ensuing it remains easily understandable and maintainable over time. Given my background in backend development and Scalability as well as monitoring tools such as Prometheus and Grafana that ensure system reliability achieves optimal performance. My ultimate aim is to deliver exemplary work in accordance with your vision while adding value along the way. Choosing me means choosing a seasoned professional who can guarantee 100%atisfaction.

@ashinnd84

Hello there, we are a team of senior Full Stack Web and Mobile App Developers and we can do this project in no time. Thanks Ashish Kumar.

@AlexVydrin

Hi there, this feels very aligned with a lightweight AWS observability task where the important part is not just pulling metrics, but pulling the right metrics from the right namespaces so the agent can actually support root cause analysis after each test run. In ECS, CPU and memory are available as standard service or cluster metrics, while request count, latency/response time, and error rate often come from the load balancer layer or Container Insights/custom metrics, so the agent needs a small metric-resolution layer instead of assuming everything lives in one place. I’d keep this intentionally lean: Python with boto3 is a strong fit, and Lambda or a simple scheduled runtime both work well for polling CloudWatch and returning on-demand results. The cleanest approach is to let the agent accept a chosen ECS service or instance context, map each of the five required metrics to the correct namespace and dimensions, and then query them via CloudWatch GetMetricData, which is better suited for pulling multiple metrics together than one-by-one statistics calls. I can structure the delivery so you get source code, a walkthrough, a one-step deploy path with IAM roles or Terraform, and a README that covers scheduling, interval tuning, and local testing. That way you are not left with a fragile script, but with a small maintainable agent that can be dropped into your AWS environment and extended later if you want deeper RCA signals from logs or traces too.

@emilesd617

Hi, I am an AWS automation and AI agent developer with 8 years of rich experience. I am familiar with Python, boto3, CloudWatch, ECS and AI Agents. For this project, the most important issue is building a lightweight agent that can fetch CPU, memory, request count, response time, and error rate metrics from ECS after each test run. I'm an individual freelancer and can work on any time zone you want. Please contact me with the best time for you to have a quick chat. Looking forward to discussing more details. Thanks. Emile.

@krisk63

Hi, this is Kris from McKinney, Texas. I've reviewed your project requirements and understand that you need a small, reliable agent to fetch CloudWatch data from an ECS cluster hosting 15 microservices. The key challenge lies in ensuring the agent can pull both default and custom metrics, such as CPU utilization, Memory usage, Request count, Response time, and Error rate. My approach involves developing a lightweight Python script using boto3 to connect to your AWS account and retrieve the required metrics. I will ensure the code is well-documented and provide a one-step deployment script or Terraform module for easy setup. A few additional questions: Q1: Do you have specific preferences for the polling intervals of the agent? Q2: Are there any specific IAM roles/policies that the agent should adhere to? Q3: How would you prefer the walkthrough of the code to be presented? Best regards, Kris Kramer

@nemanjam61

Hello, I have experience with AWS, ECS, and Python, having built solutions for microservices monitoring and analysis. I can develop a lightweight agent using Python with boto3 to connect to your AWS account, accessing CloudWatch data to pull metrics like CPU utilization and error rates. For a technical scenario, I propose implementing a Lambda function to fetch statistics at regular intervals and store insights in a database for easier root cause analysis. Let's discuss!

@Srashtasoft

Hi there, I have read your project requirement, and you need a lightweight AI/monitoring agent hosted on AWS Agent Core Runtime that connects to ECS and CloudWatch to collect metrics for root cause analysis after each test run. I can help you with: • Python-based agent using boto3 and AWS SDKs • ECS and CloudWatch metrics collection for all required services • Retrieval of CPU, Memory, Request Count, Response Time, and Error Rate metrics • Support for default and custom CloudWatch metrics • Terraform/deployment scripts for IAM roles and setup • Clean documentation, walkthrough, and local testing instructions Quick questions: ============== Should the agent trigger automatically after CI/CD test runs or on a scheduled interval? Are custom metrics already being pushed via CloudWatch Agent? Do you want the RCA output stored in logs, a database, or sent to another system? Which Agent Core Runtime environment are you currently using? Best Regards, Srashtasoft Team

@Vsion2

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@johnedwardl

Hi, I will develop a lightweight agent hosted on the agent core runtime that efficiently pulls CloudWatch data from your ECS cluster. Using Python and boto3, I’ll ensure the agent retrieves the specified metrics—CPU utilization, Memory usage, Request count, Response time, and Error rate—alongside both default and custom statistics. My experience with AWS and ECS enables me to create a solution tailored to your requirements, ensuring it’s reliable and easy to integrate. I will provide clear source code comments, a comprehensive walkthrough, and a one-step deployment script or Terraform module to establish necessary IAM roles and policies. Additionally, the README will detail how to schedule the collector, adjust polling intervals, and test the output locally. This solution will fulfill your acceptance criteria, allowing on-demand retrieval of metrics for any ECS instance ID. Let’s discuss any additional details to get started on this project. Thank you.

@mojjammil

Hello, I am ready to dive into your project immediately. I’ve built lightweight AWS monitoring and RCA agents around ECS and CloudWatch using Python/boto3 and Lambda workflows, including collection of ECS service metrics, custom CloudWatch Agent metrics, and post-run diagnostic summaries for distributed microservice environments. I can deliver a modular agent with IAM/Terraform setup, configurable polling intervals, CloudWatch metric aggregation for all five KPIs, and a clean walkthrough so your team can easily trigger RCA flows after each test execution. I want to discuss with you in more detail. Kind regards, Mojjammil