A blog site on our Real life experiences with various phases of DevOps starting from VCS, Build & Release, CI/CD, Cloud, Monitoring, Containerization.
Welcome to the first part of our blog on GitHub Actions!
This blog will delve into fundamental concepts essential for understanding GitHub Actions. Get ready to embark on a journey through the basics, paving the way for the upcoming implementation part of our blog. Stay tuned for hands-on demonstrations and practical applications in the next blog. Let’s dive in!
Recently while trying to set up Apache Nifi in cluster mode manually, I faced the challenge of performing same tasks on all nodes manually. In addition configuring the right cluster configurations was not easy. In my last blog here, I have covered the advantages of having nifi cluster over standalone and the manual steps to configure a Nifi cluster with external zookeeper.
In this article, I will show you how you can set up a three-node Zookeeper and Nifi cluster with terraform which will minimize the steps we have to perform with manual setup.
Apache NiFi is an open-source data integration and automation tool that enables the automation of data flow between different systems. NiFi provides a user-friendly interface to design, control, and manage the flow of data between various sources and destinations. The tool is particularly useful in handling data from different sources, applying transformations, and routing it to different systems in real-time.
Advantage of Using Terraform for Nifi
Terraform allows you to define your NiFi cluster infrastructure as code, making it easily versioned, shareable, and easy to understand. This ensures that your infrastructure is consistent across different environments. This helps in maintaining consistency and reducing the chances of configuration drift. As your NiFi cluster requirements evolve, Terraform makes it simple to scale your infrastructure up or down by adjusting the configuration.
Setting Up Apache Nifi Cluster with External Zookeeper
Continue reading “Nifi and Zookeeper Cluster Setup with Terraform”
The Cloud Intelligence Dashboards represent an open-source framework crafted and nurtured by a dedicated community of AWS enthusiasts. These dashboards are designed to deliver actionable insights and scalability for organizations, with a focus on customer satisfaction. The functionalities of these dashboards extend to fostering financial accountability, optimizing costs, monitoring usage goals, implementing governance best practices, and attaining operational excellence across all Well-Architected pillars. It includes multiple dashboards: Continue reading “Navigating AWS FinOps: Harnessing Cloud Intelligence Dashboards for Strategic Cost Optimization”
Before we dive into the technicalities, let’s understand the core benefits of agentless monitoring. It’s like having a silent guardian for your application, one that doesn’t require the extra resources or management overhead that traditional agents do. This means less complexity, less maintenance overhead, and better accuracy in your monitoring.
TLDR; If you have a service exposing prometheus compatible endpoint, then you can scrape those metrics directly with services like Grafana Cloud without needing any intermediate agent.
Supabase is making waves as a top pick for developers needing a backend service, thanks to its solid PostgreSQL base and ease of use.
Grafana Cloud brings a lot to the table, with its easy-to-use features like drag-and-drop dashboards, smart alerts, and even some clever machine learning tricks to help you spot and fix problems before they blow up. In short, Grafana Cloud doesn’t just make monitoring simpler; it makes it smarter, helping developers keep their apps running smoothly and their users happy.
Continue reading “Agentless Monitoring: Integrating Supabase Metrics with Grafana Cloud”
What is Kernel Patching?
The operating system kernel is the central component that controls system resources and enables hardware and software connection. Kernel patching is the act of changing or maintaining the kernel’s source code.
When to choose this type of patching?
Organizations that are thinking about kernel patching usually assess how well the available solutions work with the particular kernel version they are using, test extensively in a non-production setting, and set up reliable backup and rollback procedures to reduce risks in the production environment.
It’s critical to thoroughly evaluate the organization’s particular requirements and risks, as well as the advantages and disadvantages of kernel patching. Other considerations that might impact the choice include the organization’s overall risk tolerance, regulatory requirements, and how critical the systems are.
