Posts

Here is a great python toolkit to generate #multicloud or custom cloud architecture diagrams from code.

The diagrams as a code tool supports all cloud providers like #AWS, #Azure, #GoogleCloud, #AlibabaCloud, #IBM and their respective services/components. If some of the services are not available, you can create one using the custom node feature.

Link to Github repo – https://lnkd.in/djSaBwaT

I used the custom extensions node to develop my own constructs for a Google Cloud CI/CD process using Cloud Code, Cloud Build, Google Cloud Deploy, and GKE. You can use this tool for rapid prototyping.

The code and details are available on my blog - https://lnkd.in/d73aRYhq

Optimization is an important consideration for many solutions. If you are looking for Python toolkit for solving optimization problems like vehicle routing, linear programming, scheduling, assignment, constraint programming, .. checkout OR-Tools for Python from Google

For instance, if you are doing Graph programming and what to find shortest paths in graphs
based on cost flows, you can use this toolkit

Checkout the blog and examples at https://lnkd.in/dfmvQhzw

Generate #multicloud or custom cloud architecture diagrams from code. The diagrams as a code tool supports all cloud providers like #AWS, #Azure, #GoogleCloud, #AlibabaCloud, #IBM and their respective services/components. If some of the services are not available, you can create one using the custom node feature.

Link to Github repo – https://lnkd.in/djSaBwaT

I used the custom extensions node to develop my own constructs for a AWS CI/CD process using AWS CodeCommit, AWS CodePipeline, AWS CodeDeploy and AWS CodeBuild. You can use it for rapid prototyping and generating your own custom constructs as part of your process.

The code and details are available on my blog - https://lnkd.in/dU7T3—9

AWS version of the CI/CD pipeline, created using the diagrams code tool. In my last post, I shared the Google Cloud CI/CD process.

For the AWS CI/CD process, I used custom extensions for AWS CodeCommit, AWS CodePipeline, AWS CodeDeploy and AWS CodeBuild, along with custom actions, like approvals as part of the process. You can also use the tool for rapid prototyping and generating your own custom constructs as part of your process.

Link to Github repo – https://lnkd.in/djSaBwaT

The code and details are available on my blog - https://lnkd.in/dU7T3—9

Here is the AWS version of the CI/CD pipeline, created using the diagrams code tool. In my last post, I shared the Google CI/CD process.

For the AWS CI/CD process, I used custom extensions for AWS CodeCommit, AWS CodePipeline, AWS CodeDeploy and AWS CodeBuild, along with custom actions, like approvals as part of the process. You can use this tool for rapid prototyping and generating your own custom constructs as part of your process.

Link to Github repo – https://lnkd.in/djSaBwaT

The code and details are available on my blog - https://lnkd.in/dU7T3—9

Generate #multicloud or custom cloud architecture diagrams from code. The diagrams as a code tool supports all cloud providers like #AWS, #Azure, #GoogleCloud, #AlibabaCloud, #IBM and their respective services/components. If some of the services are not available, you can create one using the custom node feature.

Link to Github repo – https://lnkd.in/djSaBwaT

I used the custom extensions node to develop my own constructs for a Google Cloud CI/CD process using Cloud Code, Cloud Build, Google Cloud Deploy, and GKE. You can use it for rapid prototyping.

The code and details are available on my blog - https://lnkd.in/d73aRYhq

Here is a great python toolkit to generate #multicloud or custom cloud architecture diagrams from code.

The diagrams as a code tool supports all cloud providers like #AWS, #Azure, #GoogleCloud, #AlibabaCloud, #IBM and their respective services/components. If some of the services are not available, you can create one using the custom node feature.

Link to Github repo – https://lnkd.in/djSaBwaT

I used the custom extensions node to develop my own constructs for a Google Cloud CI/CD process using Cloud Code, Cloud Build, Google Cloud Deploy, and GKE.  You can use it for rapid prototyping.

The code and details are available on my blog - https://lnkd.in/d73aRYhq

If you are looking to generate #multicloud or custom cloud architecture diagrams from code , then look at “Diagram as Code for prototyping cloud system architectures” tool.

The diagrams as a code tool supports all cloud providers like #AWS, #Azure, #GoogleCloud, #AlibabaCloud, #IBM and their respective services/components. If some of the services are not available, you can create one using the custom node feature.

Link to Github repo – https://lnkd.in/djSaBwaT

I used the custom extensions node to develop my own constructs for a Google Cloud CI/CD process using Cloud Code, Cloud Build, Google Cloud Deploy, and GKE.

The code and details are available on my blog - https://lnkd.in/d73aRYhq

Technically, one full stack engineer can deliver your end-2-end project/solutions. This is an interesting article on the rise of full stack engineers and demand for it.

In my view, the demand for full stack engineers will rise even further as they transition fast and adopt new skills for Web 3.0 and #Metaverse

Article Link - https://lnkd.in/dS3Rb3qS

Cloud skills are an essential part of full stack. Technically, one full stack engineer can deliver your end-2-end project/solutions. This is an interesting article on the rise of full stack engineers and demand for it.

In my view, the demand for full stack engineers will rise even further as they transition fast and adopt new skills for Web 3.0 and #Metaverse

Article Link - https://lnkd.in/dS3Rb3qS

Technically, one full stack engineer can deliver your end-2-end project/solutions. This is an interesting article on the rise of full stack engineers and demand for it.

In my view, the demand for full stack engineers will rise even further as they transition fast and adopt new skills for Web 3.0 and #Metaverse

Article Link - https://lnkd.in/dS3Rb3qS

Cloud optimisation is an continuous process to cut down on cloud resources not being used and save on cloud cost substantially.

Here are some of the few basic optimization steps that you could follow for your cloud projects. The strategy works for across cloud providers.

Logs management - The storage for logs can grow exponentially, especially if you have central logging enabled. This is across environments (dev, test, prod etc). The first step is to get a tab of log storage being used and filter out logs not being used. For instance, apart from log levels, you can filter out default service logs. Each environment can have a different log optimization strategy. For instance, for Google Cloud you can exclude Google Kubernetes Engine container and pod logs based on GKE internal namespaces i.e knative-serving etc.

Network optimization - Keep a tab of network resources that are lying idle. For instance, Static IPs not associated with a resource adds to your cloud cost. Usually deleting a cloud resource using the static ip, does not delete the static ip and you many not realise this unless you look at the cloud bills in detail.

Idle resource management - Build out a calendar to automate shutting down non-production resources when not-in use (i.e based on non-office hours, weekends). For instance, you can also suspend/hibernate the VM, you will charged only for storage costs. Here is a #AWS reference on using #Lambda to turn on/off resources -https://lnkd.in/gGgVeDTk

Turn on cloud recommendations - Each cloud provider provides certain recommendations to identify idle resources, oversized VMs etc.. For instance, Google Cloud has a Recommender API that provides a dashboard for these details.

Delete unwanted backups and snapshots - Automated database backups, storage and VM snapshots all add to the cloud cost. Each environment (dev, test, prod) needs a different strategy. Identify snapshots not required and delete them periodically.

For more details and references, please visit my blog @ https://lnkd.in/gNsDgc7A

Cloud optimisation is an continuous process to cut down on cloud resources not being used and save on cloud cost substantially.

Here are some of the few basic optimization steps that you could follow for your cloud projects. The strategy works for across cloud providers.

Logs management -  The storage for logs can grow exponentially, especially if you have central logging enabled. This is across environments (dev, test, prod etc). The first step is to get a tab of log storage being used and filter out logs not being used. For instance, apart from log levels, you can filter out default service logs. Each environment can have a different log optimization strategy. For instance, for Google Cloud you can exclude Google Kubernetes Engine container and pod logs based on GKE internal namespaces i.e knative-serving etc.

Network optimization - Keep a tab of network resources that are lying idle. For instance, Static IPs not associated with a resource adds to your cloud cost. Usually deleting a cloud resource using the static ip, does not delete the static ip and you many not realise this unless you look at the cloud bills in detail.

Idle resource management - Build out a calendar to automate shutting down non-production resources when not-in use (i.e based on non-office hours, weekends). For instance, you can also suspend/hibernate the VM, you will charged only for storage costs. Here is a #AWS reference on using #Lambda to turn on/off resources -https://lnkd.in/gGgVeDTk

Turn on cloud recommendations - Each cloud provider provides certain recommendations to identify idle resources, oversized VMs etc.. For instance, Google Cloud has a Recommender API that provides a dashboard for these details.

Delete unwanted backups and snapshots - Automated database backups, storage and VM snapshots all add to the cloud cost. Each environment  (dev, test, prod) needs a different strategy. Identify snapshots not required and delete them periodically.

For more details and references, please visit my blog @ https://lnkd.in/gNsDgc7A

This is an interesting survey on sustainable travel and the
challenges highlighted, including lack of professional tools to
visualise environmental impact of travel and lack of training
or personnel knowledge on sustainability.

Link to the article - https://lnkd.in/d3B9x2xa

Interestingly, Google flights now shows carbon emission estimates
next to each flight. Flights are labelled as higher, typical, lower, or
unknown emissions. The tech behind the calculation includes
various factors like Aircraft model, speed, distance etc..
More details @
https://lnkd.in/d-9tCY9z

This is a good technology problem to solve where green travel
will have various combinations and trade-offs like intelligent routes,
fuel v/s EV charging vehicles, SAF aviation fuels, ride sharing option, cost factors, etc..

As industry moves toward carbon efficient travel, the
next version of your travel portal in future will hopefully
include a green option to make all these choices and reward
users to make sustainable choices.

Creating and enforcing configurations and security policies in a unified way is critical to manage and audit environments at scale.

Learn how to design policy driven CI/CD process and how to use platforms like Google Cloud #Anthos Config Management to deliver GitSecOps at scale.

Creating and enforcing configurations and security policies in a unified way is critical to manage and audit environments at scale.

Learn how to design policy driven CI/CD process and how to use platforms like Google Cloud #Anthos Config Management to deliver GitSecOps at scale.

For regular tech update, do subscribe to the newsletter -  https://lnkd.in/diqk6fvr

Having a optimized build and CI/CD process results in faster, efficient and cost effective builds. Here are Top 5 things for optimization.

1. Build Lean Container Images - Separate building the application from building its runtime layer and build form minimal base images

2. Using a cache like Kaniko with your build to cache container build artifacts. Kaniko works with all major cloud container registry.

3. Selective deployments based on last build and changes

4. Exclude files not required by build using vendor supported *.ignore files

5. Move towards Green computing - Understand the carbon impact of your builds and schedule it - batch changes for build, leverage green regions and timelines..

View the references for each of the above steps in my blog - https://lnkd.in/dMGpCwPA

Having a optimized build and CI/CD process results in faster, efficient and cost effective builds. Here are Top 5 things for optimization.

1. Build Lean Container Images - Separate building the application from building its runtime layer and build form minimal base images

2. Using a cache like Kaniko with your build to cache container build artifacts. Kaniko works with all major cloud container registry.

3. Selective deployments based on last build and changes

4. Exclude files not required by build using vendor supported *.ignore files

5. Move towards Green computing - Understand the carbon impact of your builds and  schedule it - batch changes for build, leverage green regions and timelines..

View the references for each of the above steps in my blog - https://lnkd.in/dMGpCwPA

API Security Best practices - Learn how to design and create secure APIs. The approach listed works for any cloud provider #aws #gcp #azure

Security should be by design and part of your development process. Lack of proper API security often leads to exposing sensitive data. API penetration testing should be part of your security testing process for your public facing applications.

Watch the video @ https://lnkd.in/edrhHx5j

Do subscribe to the Technology Bytes Newsletter for bi-weekly technology insights - https://lnkd.in/diqk6fvr

API Security Best practices - Learn how to design and create secure APIs.

Security should be by design and part of your development process. Lack of proper API security often leads to exposing sensitive data.  API penetration testing should be part of your security testing process for your public facing applications.

Watch the video @ https://lnkd.in/edrhHx5j

Do subscribe to the Technology Bytes Newsletter for bi-weekly technology insights - https://lnkd.in/diqk6fvr