Platform engineering has become an increasingly important aspect of modern software development. It provides the infrastructure and tools needed to deploy and manage applications at scale. Platform engineering involves designing, building and maintaining the systems and services that power cloud computing platforms, mobile app development platforms, financial services platforms, social media platforms, e-commerce platforms and other applications.
Here, in this blog, we will provide an overview of what platform engineering is, the benefits of platform engineering, why it is important as well as real-world examples of its use in various industries.
GitHub Actions is a powerful tool for automating software workflows, and it can be used to build, test, and deploy code right from GitHub. It provides a way to automate repetitive tasks and can be integrated with many popular tools and platforms.
GitHub Actions can use two types of runners: hosted and self-hosted.
Hosted runners are provided by GitHub and run on virtual machines in the cloud.
Self-hosted runners are machines that you set up and manage yourself. They run on your infrastructure, and you can customize them to meet your needs.
In this tutorial, we will show you how to set up GitHub’s self-hosted runner on Kubernetes.
Prerequisites
Before you begin, make sure you have the following:
Cloud Implementation has become a key component of modern IT systems, enabling organizations to scale their operations and reduce costs. However, managing cloud infrastructure seamlessly and driving a cloud deployment securely is not easy. It requires a deep understanding of the underlying technologies and the right cloud advisory.
In this blog, we’ll explore the building blocks of cloud infrastructure, including virtualization, containers, microservices and serverless computing. Here, we’ll discuss how these technologies work together to create a flexible, scalable and cost-effective cloud infrastructure. We’ll also discuss the different challenges of managing cloud infrastructure and cloud deployment.
What is Cloud Infrastructure?
Cloud infrastructure refers to the physical and virtual components, resources and services that are used to build and operate cloud computing environments. Cloud infrastructure includes servers, storage devices, networking equipment, software applications and tools that are hosted and delivered over the internet.
In a cloud infrastructure, resources are delivered as a service and customers can access them on demand and pay only for what they use. This is a key advantage of cloud computing as it enables businesses to quickly scale up or down their infrastructure needs without having to invest in expensive hardware or manage complex systems themselves.
Cloud infrastructure can be classified into three main types: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).
IaaS: In IaaS, customers are provided with virtual machines, storage and networking infrastructure, which they can use to deploy and run their own applications.
PaaS: In PaaS, customers are provided with a platform for developing, testing and deploying their applications, while the cloud provider manages the underlying infrastructure.
SaaS: In SaaS, customers are provided with software applications that are hosted and delivered by the cloud provider.
Cloud infrastructure is typically hosted and managed by large cloud implementation providers such as Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform. These providers help in hybrid cloud implementation, cloud infrastructure management, cloud deployment and much more. These providers have built massive data centres around the world, which host millions of virtual machines and store exabytes of data.
Why are you doing a lambda function trigger enabled using pipeline?
For the AWS service to invoke your function directly, you need to create a trigger using the Lambda console. A trigger is a resource you configure to allow another AWS service to invoke your function when certain events or conditions occur. Your function can have multiple triggers. Each trigger acts as a client invoking your function independently, and each event that Lambda passes to your function has data from only one trigger. By using the code pipeline we enabled our lambda function trigger when we needed it.
What is the benefit?
People don’t need to add lambda function roles permission manually and don’t need to enable trigger manually because, after policy gets attached to the particular roles then we can enable trigger and it happens by using pipeline whenever we need every time automation happens.
DevOps is a set of practices that combines software development and IT operations, with the goal of delivering high-quality software more quickly and reliably. However, measuring the effectiveness of DevOps can be challenging, as it involves multiple teams and processes. In order to ensure that your DevOps tools and practices are delivering the desired outcomes, it’s important to track the right metrics.
Here, in this blog, we’ll discuss the top 5 metrics to measure DevOps performance. These metrics will help teams understand how their DevOps processes are working, identify areas for improvement and ultimately deliver better software faster.
Effective use of these metrics can help organizations achieve their business objectives and stay competitive in today’s fast-paced software development landscape. So, let’s take a look at these DevOps metrics.
Mean Time To Detect (MTTD)
MTTD stands for Mean Time To Detect and is a DevOps metric that measures the average time it takes to detect an incident or problem. It is an important metric for organizations that want to improve their incident response processes and reduce downtime.
