- Optimizes the overall size of the Docker image
- Removes the burden of creating multiple Dockerfiles for different stages
- Easy to debug a particular build stage
- Able to use the previous stage as a new stage in the new environment
- Ability to use the cached image to make the overall process quicker
- Reduces the risk of vulnerabilities found as the image size becomes smaller with multi-stage builds
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𝐀𝐖𝐒 𝐬𝐞𝐫𝐯𝐢𝐜𝐞 𝐖𝐡𝐞𝐞𝐥⚠️
AWS offers an extended collection of services catering to different functionality and use cases. Below is a condensed summary of some of the main AWS services:
🔶 Compute:
✅ Amazon EC2 (Elastic Compute Cloud): Scalable virtual servers for running any application.
✅ AWS Lambda: Serverless computing, allowing code execution without managing servers.
✅ Amazon Lightsail: Simplified virtual servers for basic needs.
✅ AWS Elastic Beanstalk: Effortless deployment and scaling of web applications.
🔶 Storage:
Cloud storage that scales with Amazon S3.
✅ Amazon EBS: EC2 instance block storage volumes.
✅ Amazon Glacier: Economical, extended-duration storage.
🔶 Database:
Managed relational database service provided by Amazon RDS.
The managed NoSQL database service is offered by Amazon DynamoDB.
Scalable, rapid data warehousing offered by Amazon Redshift.
✅ Amazon Aurora: Managed relational database with high performance.
🔶 Networking & Content Delivery:
✅ Amazon VPC: Private cloud infrastructure.
✅ Amazon CloudFront: A worldwide network for content delivery (CDN).
✅ AWS Direct Connect: A network connection that is dedicated
🔶 Tools for developers:
✅ Amazon CodeCommit: A service for managed source control.
✅ AWS CodeBuild: Construct and evaluate code.
Automated code deployments using AWS CodeDeploy.
🔶 Identity, Security, and Compliance:
✅ AWS IAM: Controls encryption keys and user access.
User identification and data synchronization using Amazon Cognito.
✅ Amazon KMS: Handles keys for encryption.
🔶 Machine Learning:
Create, train, and implement ML models using Amazon SageMaker.
✅ AWS DeepLens: A video camera with deep learning capabilities.
✅ Amazon Rekognition: Video and image processing.
✈️ 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
AWS offers an extended collection of services catering to different functionality and use cases. Below is a condensed summary of some of the main AWS services:
Cloud storage that scales with Amazon S3.
Managed relational database service provided by Amazon RDS.
The managed NoSQL database service is offered by Amazon DynamoDB.
Scalable, rapid data warehousing offered by Amazon Redshift.
Automated code deployments using AWS CodeDeploy.
User identification and data synchronization using Amazon Cognito.
Create, train, and implement ML models using Amazon SageMaker.
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In this article, we will look at how to run Terraform in an Azure DevOps pipeline, step-by-step. We will go from the start of the process showing how to create an Azure DevOps instance and project, how to setup Terraform in Azure DevOps, and how to create Terraform configuration files for the infrastructure and pipelines using YAML, sharing some examples and best practices along the way.
𝑓𝑜𝑟 𝑚𝑜𝑟𝑒 𝑖𝑛𝑓𝑜, 𝑦𝑜𝑢 𝑐𝑎𝑛 𝑐ℎ𝑒𝑐𝑘 𝑡ℎ𝑖𝑠 𝑙𝑖𝑛𝑘:
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Several key components of Kubernetes are important to understand:
𝗣𝗼𝗱
𝗦𝗲𝗿𝘃𝗶𝗰𝗲
𝗡𝗮𝗺𝗲𝘀𝗽𝗮𝗰𝗲
𝗡𝗼𝗱𝗲
𝗖𝗹𝘂𝘀𝘁𝗲𝗿
𝗥𝗲𝗽𝗹𝗶𝗰𝗮𝗦𝗲𝘁
𝗟𝗮𝗯𝗲𝗹
𝗞𝘂𝗯𝗲𝗹𝗲𝘁
𝗞𝘂𝗯𝗲𝗰𝘁𝗹
𝗞𝘂𝗯𝗲-𝗽𝗿𝗼𝘅𝘆
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Are you searching for ways to harness the formidable capabilities of AWS to transform your organization's network? Look no further than AWS Transit Gateway, a game-changing solution designed to simplify and elevate your network architecture, especially in scenarios involving intricate setups of multiple AWS accounts and Amazon Virtual Private Clouds (VPCs). Here's a closer look at how AWS Transit Gateway can revolutionize your business:
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𝑓𝑜𝑟 𝑚𝑜𝑟𝑒 𝑖𝑛𝑓𝑜, 𝑦𝑜𝑢 𝑐𝑎𝑛 𝑐ℎ𝑒𝑐𝑘 𝑡ℎ𝑖𝑠 𝑙𝑖𝑛𝑘:
https://prodevopsguy.site/100-Kubernetes-Errors-With-Solution
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However, managing load balancers can be overwhelming, given the various types and configuration options available.
In today's multi-cloud landscape, mastering load balancing is essential to ensure seamless user experiences and maximize resource utilization, especially when orchestrating applications across multiple cloud providers. Having the right knowledge is key to overcoming these challenges and achieving consistent, reliable application delivery.
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When you host your system in 𝗔𝘇𝘂𝗿𝗲, there are many things to monitor. Obviously, your system's metrics. But not only. You should also keep an eye on
➡️ planned maintenance
➡️ service health
➡️ resource health
➡️ recommendations
One of the options would be checking this in the portal. However, this approach is time-consuming, as there is not always something to look for.
🔣 What else could we do?
We can configure alerts for this kind of event and be notified via our preferred channel.
With Terraform, all that we need is 𝗮𝘇𝘂𝗿𝗲𝗿𝗺_𝗺𝗼𝗻𝗶𝘁𝗼𝗿_𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝘆_𝗹𝗼𝗴_𝗮𝗹𝗲𝗿𝘁 where we can configure criteria for being alerted, like:
➡️ event category
➡️ event type
➡️ locations
➡️ services
This saves you valuable time and increases your level of confidence in platform health.
📱 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
One of the options would be checking this in the portal. However, this approach is time-consuming, as there is not always something to look for.
We can configure alerts for this kind of event and be notified via our preferred channel.
With Terraform, all that we need is 𝗮𝘇𝘂𝗿𝗲𝗿𝗺_𝗺𝗼𝗻𝗶𝘁𝗼𝗿_𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝘆_𝗹𝗼𝗴_𝗮𝗹𝗲𝗿𝘁 where we can configure criteria for being alerted, like:
This saves you valuable time and increases your level of confidence in platform health.
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www.prodevopsguy.site
𝐏𝐫𝐨𝐃𝐞𝐯𝐎𝐩𝐬𝐆𝐮𝐲 ♾️ 𝐅𝐫𝐞𝐞 𝐃𝐞𝐯𝐎𝐩𝐬/𝐂𝐥𝐨𝐮𝐝 𝐖𝐨𝐫𝐥𝐝
Free DevOps/Cloud World
𝑓𝑜𝑟 𝑚𝑜𝑟𝑒 𝑖𝑛𝑓𝑜, 𝑦𝑜𝑢 𝑐𝑎𝑛 𝑐ℎ𝑒𝑐𝑘 𝑡ℎ𝑖𝑠 𝑙𝑖𝑛𝑘:
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ReplicaSet and Deployment are both Kubernetes resources used for managing and scaling application instances, but they serve different purposes and have distinct features:
It is a lower-level controller in Kubernetes.
It does not support declarative updates or rollback strategies.
It is often used directly only in advanced scenarios where finer control over scaling and updates is required.
It is a higher-level abstraction built on top of ReplicaSets.
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If you want to become a Certified Kubernetes Administrator, or you want to become an EXPERT in Kubernetes, learn Kubernetes from scratch and understand everything, this repo is a good choice.
1. Kubernetes
2. Helm
3. Operator
4. Prometheus
5. EKS
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