🔔 https://prodevopsguy.xyz/posts/devops/deploying-an-application-on-kubernetes-a-complete-guide/


😎 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

✡️ Terraform Interview Question
❓ What is a data block in Terraform, and how it differs from a resource block?

🌀 In Terraform, a data block is used to fetch and read information from a data source, such as AWS, Azure, or any other provider. It allows us to query existing resources or data from external systems without actually creating or modifying them. Data blocks are primarily used for retrieving information that is necessary for configuring resources but doesn't need to be managed by Terraform itself.

🌀 Here's a basic example of a data block querying an AWS AMI :

data "aws_ami" "example" {
most_recent = true
filter {
name = "name"
values = ["ubuntu/images/hvm-ssd/ubuntu-focal-20.04-amd64-server-*"]
}

owners = ["099720109477"] # Canonical
}

In the above example :
🔯 data "aws_ami" "example" declares a data block named "example" that retrieves information about an AWS AMI.
🔯 most_recent = true ensures that the most recent AMI matching the specified criteria is selected.
🔯 The filter block specifies criteria for filtering AMIs, in this case, by name and owner.
🔯 Finally, owners specifies the AWS account IDs that own the AMIs.

On the other hand, a resource block in Terraform is used to define the infrastructure components that Terraform manages.


😎 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

📌 https://harshhaa.hashnode.dev/devsecops-gitlab-cicd-amazon-app-deployment-on-aws-eks

🔗 More DevOps Blogs : HERE

🟩🟩🟩🟩🟩🟩🟩🟩🟩🟩🟩🟩

Follow 🍩 Like 👍 Share 👍 Comment Your thoughts 💬

⭐️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy & @devopsdocs 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

🚀 Excited to share some insights on Kubernetes architecture! 🌟

Kubernetes has revolutionized the way we deploy and manage containerized applications, but understanding its architecture can sometimes feel like navigating a complex labyrinth. Fear not! I've simplified it into bite-sized pieces for you. 🎉

🔍 Visual Breakdown: Check out the image below for a simplified visualization of Kubernetes architecture. It's like having a map to guide you through the Kubernetes landscape! 🗺

🧩 Key Components: Let's break it down:

Nodes: Think of them as the workers and managers in your application orchestra.

Pods: Your application's smallest building blocks, neatly packed containers.

Services: Gateways to your applications, ensuring seamless communication.

Controllers: The brains behind the operation, ensuring everything runs smoothly.

etcd: The reliable memory bank, storing all cluster data securely.

API Server, Scheduler, Controller Manager: The command center, orchestrating every move.

🔄 Interactions and Flow: Discover how these components interact with each other, forming a well-choreographed dance of scalability and resilience.

🌱 Continuous Learning: Kubernetes is a vast ecosystem, and there's always more to explore! Dive deeper into its intricacies to unlock its full potential.


✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy & @devopsdocs 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

🐬 Docker Networking:

When Containers Talk: Decoding the Secret Language of Docker Networking.

🔢: Bridge (Default):
➡️ The default, isolated network where containers get unique IP addresses and can communicate with other containers on the same host.

➡️Use Cases:
➡️ Ideal for most containerized applications that need network isolation and communication within the host.
➡️ Well-suited for development, testing, and staging environments.

🔢: None:
➡️ Disables networking entirely, isolating the container from any network.

➡️Use Cases:
➡️ Niche use cases where no network access is required (e.g., headless tasks, security-sensitive processes).
➡️ Not recommended for general-purpose container usage.

🔢: Host:
➡️ Shares the host's network namespace, allowing containers to directly use the host's IP address and ports.

➡️Use Cases:
➡️ Exposing container services to the host's network without complex port mappings.
➡️ Useful for testing and development, but exercise caution due to potential security risks in production.

🔢: Overlay:
➡️ Description: Creates a virtual network across multiple Docker hosts, enabling container communication regardless of their physical location.

➡️Use Cases:
➡️ Orchestrated deployments with Docker Swarm or Kubernetes where containers need to communicate across hosts.
➡️ Highly scalable network for distributed applications.


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

🎙 Lets talk about "lifecycle hooks in Kubernetes" and how you can use them to make your pods intelligent.

Pod lifecycle hooks, such as preStart and preStop, are features within Kubernetes that allow you to specify commands that should be executed at specific points in a container's lifecycle. Think of it like a subsystem that is monitoring and managing the task that you specify for these lifecycle stages.

➡️ postStart: Executed after a container has started. It can be used for tasks that need to be performed once the container is up and running. Initialization and Configuration, Dependency check, Health Checks are some common usecases that are configured here.

➡️ preStop: Executed just before a container is terminated. It provides an opportunity to perform cleanup tasks or gracefully shut down the application before the container stops. Graceful Shutdown, Connection Draining, Notification of Termination are all the things that can be configured here.

If your application needs customization for different environments like dev,stage, production, then you should definitely check these hooks out.


🔵 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

🐬 https://prodevopsguy.xyz/posts/devops/ultimate_docker_commands/


✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy & @devopsdocs 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

☄️ Real-world Prometheus Deployment: A Practical Guide for Kubernetes Monitoring ☄️

🔗 Source Link: https://github.com/NotHarshhaa/Learning-Prometheus

🔗 Blog Link: https://harshhaa.hashnode.dev/real-world-prometheus-deployment-a-practical-guide-for-kubernetes-monitoring


✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

🚀 𝗥𝗲𝗮𝗱𝘆 𝘁𝗼 𝘁𝗮𝗸𝗲 𝘆𝗼𝘂𝗿 𝗗𝗲𝘃𝗢𝗽𝘀 𝗲𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲 𝘁𝗼 𝘁𝗵𝗲 𝗻𝗲𝘅𝘁 𝗹𝗲𝘃𝗲𝗹?

Here are six cutting-edge software deployment strategies every engineer should have in their toolkit: 🖥

1️⃣ Shadow Deployment: Deploy new versions of software alongside existing production systems, directing a small portion of traffic to the new version for validation before full rollout.

2️⃣ Blue-Green Deployment: Mitigate downtime by maintaining two identical production environments, allowing seamless switchovers for updates.

3️⃣ Canary Deployment: Safely roll out changes by gradually introducing them to a subset of users, monitoring for any issues before full release.

4️⃣ Rolling Deployment: Update one server or a subset at a time, ensuring minimal disruption while continuously delivering new features.

5️⃣ Feature Toggle Deployment: Enable or disable specific features at runtime, providing flexibility to release updates without impacting users.

6️⃣ A/B Testing Deployment: Experiment with different versions of software simultaneously, gathering valuable insights into user preferences and behaviors to inform future development decisions.

Mastering these strategies empowers DevOps engineers to streamline processes, enhance reliability, and deliver value to users efficiently. Keep learning, keep innovating!


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy & @devopsdocs 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

Hola 👋,

We are thrilled to share that we have started our own website 😁 and you guys don't need to search 🔎 on WhatsApp channels or Telegram group every time what u required. On the website we can also post all things clearly and proper format just u can search the things wat need for u

🖥 Our website : https://prodevopsguy.tech

📱 Our Blogs/Articles :
https://blog.prodevopsguy.xyz


Thanks,
ProDevOpsGuy Team

📣 New to DevOps? 📣

Here are the most widely used tools in the industry along with their official documentation:

➡️ Source Code Management:

1. Git: https://git-scm.com/docs
2. GitHub: https://docs.github.com/en
3. Bitbucket: https://lnkd.in/dA2PcM_w

➡️ Ticketing Tools:

1. Service Now: https://lnkd.in/d69yubJF
2. Jira: https://lnkd.in/dD_WcXFQ
3. Trello: https://trello.com/guide

➡️ Public Clouds:

1. AWS: https://lnkd.in/dMa9XpMa
2. Azure: https://lnkd.in/dBsJtZHy
3. GCP: https://lnkd.in/d3hmN-Jr

➡️ Containerization and Orchestration Tools:

1. Docker: https://docs.docker.com/
2. Kubernetes: https://lnkd.in/dZXfQEqW
3. Mesos: https://lnkd.in/dqzvzJhY

➡️ Deployment Tools:

1. Terraform: https://lnkd.in/dM46h2_D
2. Octopus: https://octopus.com/docs
3. Heroku: https://lnkd.in/dCDuwvcj

➡️ Testing Tools:

1. Selenium: https://lnkd.in/dTnFN8bT
2. Cucumber: https://lnkd.in/dpmD4A9C
3. Postman: https://lnkd.in/d3xERi6c

➡️ Build Tools:

1. Maven: https://lnkd.in/dfgBnrZj
2. Gradle: https://lnkd.in/dv6rQczZ
3. Ant: https://lnkd.in/dQgMsgef

➡️ Pipeline Tools:

1. Jenkins: https://lnkd.in/dPmA6-ff
2. TravisCI: https://lnkd.in/dxxFaK_X
3. Argo CD: https://lnkd.in/dK5eXbYi

➡️ Monitoring Tools:

1. Grafana: https://lnkd.in/dX5anVq9
2. Prometheus: https://lnkd.in/ddxjc9bV


🚀 Follow for more DevOps content, tips and tricks, and Hands-On Project Implementation.


🔵 Follow for more: @prodevopsguy

🔣 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗖𝗼𝗺𝗺𝗼𝗻 𝗘𝗿𝗿𝗼𝗿𝘀 🔣

1️⃣.𝙄𝙢𝙖𝙜𝙚𝘽𝙖𝙘𝙠𝙋𝙪𝙡𝙡𝙊𝙛𝙛 :-
We face this issue when the image is not present in registry or the given image tag is wrong.
Make sure you provide correct registry url, image name and image tag.

We might face authentication failures, when image is being stored in a private registry, make sure to create secret with private registry credentials and add created secret in Kubernetes Deployment File to pull docker image.

2️⃣.𝘾𝙧𝙖𝙨𝙝𝙇𝙤𝙤𝙥𝘽𝙖𝙘𝙠𝙊𝙛𝙛 :-
We face this issue when the process deployed inside container not running then the POD will be moved to CrashLoopBackOff.
POD might be running out of CPU or memory, POD should get enough resources allocated that’s cpu and memory for an application to be up and running, to fix that check in Resources Requests and Resources Limits.

3️⃣.𝙊𝙊𝙈 𝙆𝙞𝙡𝙡𝙚𝙙 - 𝙊𝙪𝙩 𝙊𝙛 𝙈𝙚𝙢𝙤𝙧𝙮 :-
We face this issue when PODs tries to utilise more memory than the limits we have set.
We can resolve it by setting appropriate resource request and resource limit.

4️⃣.𝙋𝙊𝘿 𝙎𝙩𝙖𝙩𝙪𝙨 – 𝙋𝙚𝙣𝙙𝙞𝙣𝙜 :-
When nodes might not be ready and required resources like CPU and Memory may not be available in nodes for the PODs to be up and running.

5️⃣.𝙋𝙊𝘿 𝙎𝙩𝙖𝙩𝙪𝙨 – 𝙒𝙖𝙞𝙩𝙞𝙣𝙜 :-
POD will be scheduled to a node but POD won’t be running in scheduled node.
We can fix this by providing correct image name, image tag and authentication to registry.

6️⃣.𝙋𝙊𝘿 𝙬𝙞𝙡𝙡 𝙗𝙚 𝙪𝙥 𝙖𝙣𝙙 𝙧𝙪𝙣𝙣𝙞𝙣𝙜 𝙖𝙣𝙙 𝙖𝙥𝙥𝙡𝙞𝙘𝙖𝙩𝙞𝙤𝙣 𝙞𝙨 𝙣𝙤𝙩 𝙖𝙘𝙘𝙚𝙨𝙨𝙞𝙗𝙡𝙚.
We can fix this by creating appropriate service.
If service is already created and application is still not accessible, make sure application and service are deployed in same namespace.

7️⃣.𝙋𝙊𝘿 𝙎𝙩𝙖𝙩𝙪𝙨 – 𝙀𝙫𝙞𝙘𝙩𝙚𝙙 :-
We can resolve this by setting appropriate resource requests and resource limits for the PODs and having enough resources in worker nodes.


✈️ 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs

8 FREE💲Udemy Docker Courses from Beginner to Professional 🚀

➡️ Beginners

🔵 Docker for the Absolute Beginner
➡️ https://lnkd.in/eSDNg-Xv

🟡 Docker Tutorial for Beginners practical hands on -Devops
➡️ https://lnkd.in/eTGeQ_dW

🩷 Docker Essentials
➡️ https://lnkd.in/edTFpFxY

🔴 Docker Before Compose - Learn Docker by Example
➡️ https://lnkd.in/eq3_w-7N

🟤 Learn Docker Quickly: A Hands-on approach to learning docker
➡️ https://lnkd.in/ededr6U2


➡️ Professional

🟢 Are You a PRO Series - Docker & Swarm Real Challenges
➡️ https://lnkd.in/em48h_qK

🔵 Docker Swarm Courses
➡️ https://lnkd.in/emr6AaK8

🔴 Building Application Ecosystem with Docker Compose
➡️ https://lnkd.in/eaa43R2f


📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

🎙 What’s the difference between AWS NAT Gateway & Internet Gateway?

Both these components facilitate traffic flow for AWS infrastructure. Both are attached to Subnets using Route tables.

Here’s how they differ

🌐 Internet Gateway (IGW)
👉 Allows instances in a public subnet to initiate requests to the public internet. Also allows inbound requests initiated from internet to reach these instances using their public IP address.
👉 Used for public-facing instances that require outbound internet access and also allow inbound traffic from internet (eg- Load balancer servers like NginX, API/Frontend servers, etc)
👉 You’re only charged for data transfer. There’s no charge for the gateway itself.

🌐 Network Address Translation Gateway (NAT GW)
👉 Allows instances in a private subnet to initiate requests to the public internet. But doesn’t allow inbound requests initiated from the internet to reach these instances.
👉 Is more secure because it hides your servers from the outside world.
👉 Used for private instances requiring outbound internet access (eg- Database machines, internal application server, etc).
👉 In addition to data transfer costs, AWS charges you per hour for each NAT GW you provision.

❗️ When in doubt, use NAT Gateway for your subnets. Use IGW only if you’re sure you want your instances to be public-facing.


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy & @devopsdocs 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

🌐 https://prodevopsguy.xyz/posts/devops/new-to-devops


✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy & @devopsdocs 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

🌐 Confused by DevOps Monitoring & Logging Tools? ....

Ever felt overwhelmed by the sea of DevOps monitoring and logging tools? Don't worry, we've all been there!

Here's a quick guide to help you navigate!

🔍 Prometheus
Monitors system performance & resource utilization.

📊 ELK Stack
Collects, analyzes, and visualizes log data.

📈 Grafana
Creates beautiful dashboards for monitoring data.

🔔 Nagios
Monitors servers, applications, and network health.

👁 Zabbix
Keeps an eye on availability, performance, and configs.

💼 Datadog (Paid)
All-in-one monitoring for infrastructure, apps, and security.

💰 New Relic (Paid)
Optimizes app performance and user experience.

🔍 Dynatrace (Paid)
Provides deep insights into application performance.

🔒 Splunk (Paid)
Analyzes machine data for monitoring, security, and operations.

🖥 LogicMonitor (Paid)
Monitors infrastructure, applications, and cloud environments.


✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy & @devopsdocs 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

#️⃣ 𝐄𝐱𝐜𝐢𝐭𝐞𝐝 𝐚𝐛𝐨𝐮𝐭 𝐃𝐞𝐯𝐎𝐩𝐬?

🔣DevOps has revolutionised the way modern software is built, deployed, and managed. It's a culture, a set of practices, and a mindset that emphasizes collaboration, automation, and continuous feedback.

Whether you're a seasoned professional or just starting out, mastering DevOps principles and tools is essential for driving efficiency, reliability, and innovation in your projects.


✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

🚀 Excited to share the power of Prometheus in the world of 𝐃𝐞𝐯𝐎𝐩𝐬! 🌐

👉 𝐖𝐡𝐚𝐭 𝐢𝐬 𝐏𝐫𝐨𝐦𝐞𝐭𝐡𝐞𝐮𝐬?
Prometheus is an open-source monitoring and alerting toolkit designed for reliability and scalability. It's your go-to companion for gaining deep insights into your infrastructure and applications.

Here are some key points highlighting the advantages and applications of Prometheus:

🔢. 𝐑𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 📊:
➡️ Prometheus provides robust real-time monitoring, allowing DevOps teams to gain insights into system performance and quickly identify issues.

🔢. 𝐒𝐜𝐚𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲 🚀:
➡️ Its scalable architecture makes Prometheus suitable for both small-scale setups and large, complex environments, ensuring adaptability as your infrastructure grows.

🔢. 𝐌𝐮𝐥𝐭𝐢-𝐝𝐢𝐦𝐞𝐧𝐬𝐢𝐨𝐧𝐚𝐥 𝐃𝐚𝐭𝐚 𝐌𝐨𝐝𝐞𝐥 🔄:
➡️ Embrace the flexibility of Prometheus' multi-dimensional data model, which simplifies querying and reporting, providing a comprehensive view of your system.

🔢. 𝐀𝐥𝐞𝐫𝐭𝐢𝐧𝐠 𝐚𝐧𝐝 𝐍𝐨𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 🚨:
➡️ Enjoy proactive alerting capabilities that empower teams to detect anomalies and potential issues before they impact users, enabling a more reliable and resilient infrastructure.

🔢. 𝐒𝐞𝐫𝐯𝐢𝐜𝐞 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲 🌐:
➡️ Prometheus seamlessly integrates with service discovery mechanisms, making it an excellent choice for dynamic environments where instances and services may change dynamically.

🔢. 𝐑𝐢𝐜𝐡 𝐐𝐮𝐞𝐫𝐲 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 💬:
➡️ Leverage Prometheus Query Language (PromQL) to perform complex queries and obtain meaningful insights, enabling a deep dive into the performance metrics of your applications.

🔢. 𝐎𝐩𝐞𝐧 𝐒𝐨𝐮𝐫𝐜𝐞 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲 🤝:
➡️ Engage with a vibrant and supportive open-source community that continually contributes to Prometheus' development, ensuring a cutting-edge and evolving monitoring solution.

🔢. 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐰𝐢𝐭𝐡 𝐆𝐫𝐚𝐟𝐚𝐧𝐚 📈:
➡️ Combine the power of Prometheus with Grafana for visually appealing and interactive dashboards, providing a user-friendly interface for monitoring and analysis.

🔢. 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 🐳:
➡️ Prometheus natively supports containerized environments, making it an ideal choice for organizations embracing container orchestration platforms like Kubernetes.

🔢🔢. 𝐂𝐥𝐨𝐮𝐝-𝐍𝐚𝐭𝐢𝐯𝐞 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 ☁️:
➡️ Seamlessly adapt Prometheus to your cloud-native ecosystem, gaining visibility into distributed architectures and microservices.


💬 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

🖥 https://prodevopsguy.xyz/new-to-devops/


✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy & @devopsdocs 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

👨‍💻 HashiCorp Certified: Terraform Associate – Hands-On Labs

👉 Source -
https://www.udemy.com/course/terraform-hands-on-labs/

👉 Download link -
https://drive.google.com/drive/u/0/mobile/folders/1GhcXYuHd72K0uXscjqVnQ3ltNqJWZV2N?usp=sharing


🎄 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

🔔 Securing DevOps: Pre-Release Best Practices

In the DevOps dynamic landscape, ensuring application security before release is crucial. By implementing proactive measures during the pre-release stage, organizations can mitigate risks and foster a culture of secure software development.

The Pre-Release Security Pillars:

1⃣. Code Quality Assurance: Integrating linting and code quality tools into VCS and CI processes to enforce best practices and organizational policies.

2⃣. Static Application Security Testing (SAST): Analyzing source code and binaries to scan for known vulnerabilities, enabling early threat detection and remediation.

3⃣. Secrets Scanning: Ensuring sensitive information like credentials and API keys are not exposed in the codebase, promoting secure handling through dedicated secrets management systems.

4⃣. Software Composition Analysis (SCA): Identifying and scanning third-party libraries and dependencies to mitigate vulnerabilities in underlying open-source components.

5⃣. Container Scanning: Analyzing pre-built container images to identify vulnerabilities in the underlying operating systems and software releases.

Modern DevOps platforms like GitLab Secure, JFrog Xray, Snyk, Palo Alto Prisma Cloud, and CrowdStrike offer comprehensive pre-release security tools, enabling organizations to address vulnerabilities and deliver secure applications proactively.


😎 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs