DevOps & Cloud (AWS, AZURE, GCP) Tech Free Learning
https://projects.prodevopsguytech.com // https://blog.prodevopsguytech.com • We post Daily Trending DevOps/Cloud content • All DevOps related Code & Scripts uploaded • DevOps/Cloud Job Related Posts • Real-time Interview questions & preparation guides
Show more📈 Analytical overview of Telegram channel DevOps & Cloud (AWS, AZURE, GCP) Tech Free Learning
Channel DevOps & Cloud (AWS, AZURE, GCP) Tech Free Learning (@prodevopsguy) in the English language segment is an active participant. Currently, the community unites 16 318 subscribers, ranking 7 977 in the Technologies & Applications category and 25 792 in the India region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 16 318 subscribers.
According to the latest data from 07 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 166 over the last 30 days and by 0 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 0%. Within the first 24 hours after publication, content typically collects N/A% reactions from the total number of subscribers.
- Post reach: On average, each post receives 0 views. Within the first day, a publication typically gains 0 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 0.
- Thematic interests: Content is focused on key topics such as devops, docker, terraform, kubernete, git.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“https://projects.prodevopsguytech.com // https://blog.prodevopsguytech.com
• We post Daily Trending DevOps/Cloud content
• All DevOps related Code & Scripts uploaded
• DevOps/Cloud Job Related Posts
• Real-time Interview questions & preparation guid...”
Thanks to the high frequency of updates (latest data received on 08 July, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
1-3 years of exp in DevOps (AWS/ Azure/ GCP). Hands-on exp in deploying Kubernetes cluster using ELK/ GKE environment. Creating a CI/CD pipeline using Jenkins. Using Monitoring tools like Prometheus/ Grafana/ Stack drivers. Docker Infra Automation scripting💬 Share cv : supraja@codcores.com
In the kingdom of container orchestration, Kubernetes reigns supreme, empowering developers and DevOps engineers to deploy, manage, and scale their applications with unparalleled efficiency. To truly harness the power of Kubernetes, understanding the complicated interplay of its various components is paramount.➡️ 𝐏𝐨𝐝 The Building Block of Kubernetes Applications, It is the fundamental unit of Kubernetes, that encapsulates one or more containers, enabling a cohesive environment for your applications. ➡️ 𝐑𝐞𝐩𝐥𝐢𝐜𝐚𝐒𝐞𝐭𝐬 Maintaining the Desired State of Pods they ensure continuous availability by maintaining the specified number of identical Pods ➡️ 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭𝐬 Directing Pod creation and updates, ensuring consistent application state. With a Deployment at the end, you can effortlessly define the desired number of replicas, image versions, and other configurations. ➡️ 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬 It acts as a stable network endpoint, providing access to your application from the outside world. It abstracts away the nitty-gritty details of individual Pods, allowing clients to seamlessly connect to your application without the hassle of managing IP addresses. ➡️ 𝐈𝐧𝐠𝐫𝐞𝐬𝐬 Routing Traffic with Precision It stands as a traffic light, intelligently routing external requests to the appropriate services within your cluster. ➡️ 𝐂𝐨𝐧𝐟𝐢𝐠𝐌𝐚𝐩 𝐚𝐧𝐝 𝐒𝐞𝐜𝐫𝐞𝐭 Keeping Configuration and Secrets Secure. These two essential components safeguard your application's configuration and sensitive information. ➡️ 𝐍𝐚𝐦𝐞𝐬𝐩𝐚𝐜𝐞𝐬 Provide order and clarity in multi-tenant environments, while Service Accounts empower Pods with access privileges. ➡️ 𝐒𝐞𝐫𝐯𝐢𝐜𝐞 𝐀𝐜𝐜𝐨𝐮𝐧𝐭 Empowering Pods with Access Privileges. They empower your application components to interact with the broader Kubernetes ecosystem, enabling them to perform their tasks seamlessly. ➡️ 𝐇𝐨𝐫𝐢𝐳𝐨𝐧𝐭𝐚𝐥 𝐏𝐨𝐝 𝐀𝐮𝐭𝐨𝐬𝐜𝐚𝐥𝐞𝐫𝐬 Horizontal pod Autoscalers dynamically scale Pods based on demand, ensuring optimal performance. Scaling with Demand. ➡️ 𝐃𝐚𝐞𝐦𝐨𝐧𝐒𝐞𝐭𝐬 They are the backbone of system-wide services, ensuring that a designated Pod runs on every node in the cluster. They are the unsung heroes of log collection, monitoring agents, and other critical services. ➡️ 𝐂𝐫𝐨𝐧𝐉𝐨𝐛 Scheduling Recurring Tasks..
The CronJob, empowers you to automate recurring tasks, such as backups, cleanup, and data processing, ensuring that your application remains up-to-date and efficient. These components, each playing a pivotal role, form the complicated tapestry of Kubernetes deployment and management. By leveraging their capabilities, you can confidently navigate the complexities of container orchestration and unleash the true potential of your applications.✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!
A Kafka producer is an entity that publishes data to topics within the Kafka cluster. In essence, producers are the sources of data streams, which might originate from various applications, systems, or sensors. They push records into Kafka topics, and each record consists of a key, a value, and a timestamp.🔴 𝗖𝗼𝗻𝘀𝘂𝗺𝗲𝗿:
A Kafka consumer pulls data from Kafka topics to which it subscribes. Consumers process the data and often are part of a consumer group. In a group, multiple consumers can read from a topic in parallel, with each consumer responsible for reading from certain partitions, ensuring efficient data processing.🔴 𝗧𝗼𝗽𝗶𝗰:
A topic is a category or feed name to which records are published. Topics in Kafka are multi-subscriber; they can be consumed by multiple consumers and consumer groups. Topics are divided into partitions to allow for data scalability and parallel processing.🔴 𝗣𝗮𝗿𝘁𝗶𝘁𝗶𝗼𝗻:
A topic can be divided into partitions, which are essentially subsets of a topic's data. Each partition is an ordered, immutable sequence of records that is continually appended to. Partitions allow topics to be parallelized by splitting the data across multiple brokers.🔴 𝗕𝗿𝗼𝗸𝗲𝗿:
A broker is a single Kafka server that forms part of the Kafka cluster. Brokers are responsible for maintaining the published data. Each broker may have zero or more partitions per topic and can handle data for multiple topics.🔴 𝗖𝗹𝘂𝘀𝘁𝗲𝗿:
A Kafka cluster comprises one or more brokers. The cluster is the physical grouping of one or more brokers that work together to provide scalability, fault tolerance, and load balancing. The Kafka cluster manages the persistence and replication of message data.🔴 𝗥𝗲𝗽𝗹𝗶𝗰𝗮:
A replica is a copy of a partition. Kafka replicates partitions across multiple brokers to ensure data is not lost if a broker fails. Replicas are classified as either leader replicas or follower replicas.🔴 𝗟𝗲𝗮𝗱𝗲𝗿 𝗥𝗲𝗽𝗹𝗶𝗰𝗮:
For each partition, one broker is designated as the leader. The leader replica handles all read and write requests for the partition. Other replicas simply copy the data from the leader.🔴 𝗙𝗼𝗹𝗹𝗼𝘄𝗲𝗿 𝗥𝗲𝗽𝗹𝗶𝗰𝗮:
Follower replicas are copies of the leader replica for a partition. They replicate the leader's log and do not serve client requests. Instead, their purpose is to provide redundancy and to take over as the leader if the current leader fails.✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!
emptyDir, are tied to the pod's lifecycle, providing temporary storage.
2️⃣. Persistent Volumes (PVs), like nfs, offer long-term storage solutions, independent of any single pod's lifecycle.
This flexibility in storage options ensures Kubernetes can handle a wide range of application requirements, from temporary cache storage to long-term data persistence.
🛒 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!Continuous integration is the practice of merging developer working copies to shared repositories multiple times per day. With CI, developers frequently commit their code changes to a shared version control repository. Each commit triggers an automated build and test process to catch integration errors as early as possible. CI helps teams avoid "integration hell" that can happen when developers work in isolation for too long before merging their changes.➡️ 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆 👇
Continuous delivery takes CI a step further with automated releases. CD means that at any point, you can push a button to release the latest app version to users. The CD pipeline deploys each code change to a testing/staging environment and runs automated tests to confirm the app is production ready. This ensures developers always have a releasable artifact that has passed tests. While CD enables releasing often, someone still needs to manually push the button to promote changes to production.➡️ 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁👇
Continuous deployment fully automates the release process. Every code commit that passes the automated tests triggers an immediate production deployment. This enables teams to ship features as fast as developers write code. However, the business may not want to release daily since this could overwhelm users with constant changes. Many teams use feature flags so developers can deploy new features, but limit their exposure until the business is ready for the public launch. Adopting CI, CD, and CD practices can accelerate a team's ability to safely deliver innovation. The key is automating repetitive processes to limit manual errors, provide rapid feedback, and reduce risk. This frees up developers to focus their energy on writing great code rather than building and deploying it. The outcome is faster time-to-market and more frequent delivery of customer value.✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!
1️⃣ Scripting and Automation Write scripts to automate tasks such as server provisioning, log rotation, or data migration. Use languages like Python or Bash.
2️⃣Collaborative Git Workflow Practice collaborative development using Git with a team or by yourself. Set up a Git repository, create branches, and simulate a workflow similar to what you'd experience in a real job.
3️⃣Dockerize an Application Containerization is an essential #DevOps practice. Dockerize an application of your choice, create an image, and then deploy it to a container orchestration platform like Docker Swarm.
4️⃣Container Orchestration with Kubernetes Learn Kubernetes basics and deploy a simple application on a #Kubernetes cluster. Explore features like pod scaling, rolling updates, and service discovery.
5️⃣Configuration Management Use tools like Ansible or Puppet to automate the configuration of multiple servers. Create playbooks or manifests to ensure consistency across your infrastructure.
6️⃣CI/CD Pipeline for a Web Application Set up a continuous integration and continuous deployment (CI/CD) pipeline for a simple web application. You can use tools like Jenkins, GitLab CI/CD, or #GitHub Actions. Automate the building, testing, and deployment processes.
7️⃣Infrastructure as Code (IaC) Learn and implement Infrastructure as Code using tools like #Terraform or #AWS CloudFormation. Create and manage cloud resources like EC2 instances VPCs in an automated and version-controlled manner.
8️⃣Monitoring and Alerting Setup Set up monitoring and alerting for your infrastructure and applications. Use tools like Prometheus and Grafana or a cloud-native solution like AWS CloudWatch. Create alerts for critical metrics.
9️⃣Log Management and Analysis Implement a log management system using tools like ELK Stack (Elasticsearch, Logstash, Kibana) or centralized logging on cloud platforms like AWS or Azure. Analyze logs to identify issues and trends.
🔟Automated Backup and Recovery Learn how to use a backup service like #Veeam to safeguard your critical data. Ensure that you can quickly recover from data loss or system failures or move your data from one place to another.
1️⃣1️⃣Multi-Environment Deployment Set up multiple environments (e.g., development, staging, production) and practice deploying your applications across these environments using automation.
1️⃣2️⃣Configuration Drift Detection Implement a system that detects and reports configuration drift in your infrastructure. Tools like AWS Config or custom scripts can help with this.➡️ Tackle one project at a time. ➡️ Share your wins and lessons on social media. ➡️ Write a blog about your project. ➡️ Ask for help if you need it. Doing these steps will make you stand out. 🛒 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!
