Step functions are very useful, if you are planning to build a workflow across multiple AWS services. It connects different AWS resources and gives us control over the execution path based on predefined conditions and feedback.
Read More
If you have used Windows container workloads on AWS as mentioned here,then you might be aware that implementing a code build and deployment pipeline is not a straight forward task.
Read More
Consider, we have deployed an infrastructure successfully using Terraform scripts.Now, you want to visualize your infrastructure and see the relation between resources created and how they are dependent on each other.
Read MoreMost of the time, what programming really is - is just a lot of trial and error. Debugging on the other hand is - in my opinion - an Art and becoming good at it takes time and experience - the more you know the libraries or framework you use, the easier it gets.
Different ways to debug your python code with logging.
To show off the versatility of RabbitMQ, we are going to use three case studies that demonstrate how RabbitMQ is well suited as a black-box managed service approach, as one that integrates tightly with the application enabling a well-functioning micro-service architecture, or as a gateway to other legacy project
Good write up on introducing RabbitMQ and it’s use cases
If you are using Terraform to deploy the infrastructure in AWS and if it includes auto scaling groups and policies set on EC2 machines and ECS services,you have to prevent resetting the Desired Count of the scaled up services on every IAC deployment.
Read MoreService mesh is a blazing hot topic in software engineering right now and rightfully so. I think it’s extremely promising technology and I’d love to see it widely adopted (in cases where it truly makes sense). Yet it remains shrouded in mystery for many people and even those who are familiar with it have trouble articulating what it’s good for and what it even is (like yours truly)
Good description of all the use cases for the service mesh
You shouldn’t pick up a given technology and integrate it with your stack just because it’s the trendy thing. We didn’t jump into the cloud 10 years ago just because it was cool, it felt like we were comparatively late to adopt Kubernetes, we don’t use a service mesh. We’ve let these technologies mature, and now we’re getting real value.
Nice read,gives insight in to the architecture decisions behind hey.com
Building automated deployment safety into the release process by using extensive pre-production testing, automatic rollbacks, and staggered production deployments lets us minimize the potential impact on production caused by deployments. This means that developers don’t need to actively watch deployments to production.
Extensive blog post on deployment and release methodologies followed at AWS, worth reading for anyone working on CI/CD implementations.
Telegram can be used for chatops using the extensive Bot API provided.Its user base,availability of mobile and web app support makes it good candidate for personal and small business use,if not enterprise.
Read More