As organizations move more of their operations to the cloud, the need for secure and compliant infrastructure becomes increasingly important. With the rapid pace of cloud adoption, it’s crucial to have a tool that can help you ensure that your cloud infrastructure is configured securely and in compliance with best practices. So in today’s blog, we will be talking about a solution for all these problems which is Checkov.
What is Checkov?
Checkov is a tool that helps developers and operations teams ensure that their infrastructure is secure and compliant with best practices. It does this by automatically scanning infrastructure as code (IaC) and runtime environments for issues that could potentially lead to security vulnerabilities or compliance failures. Checkov works by scanning code written in various IaC languages (such as Terraform, CloudFormation, and ARM templates) and looking for patterns that could indicate security or compliance risks. It can also be integrated into a continuous integration/continuous deployment (CI/CD) pipeline, allowing it to scan code automatically as it is being developed and deployed.
Kubernetes is one of the most popular projects around container orchestration but it’s quite interesting that Kubernetes itself has no code to run or manage Linux/windows containers. So, what is running the containers within your Kubernetes pods?
Yes… Kubernetes doesn’t run your containers
It’s just an orchestration platform sitting above container runtimes. No code to run a container and to manage the container’s lifecycle on its own, instead, dockershim was implemented (in kubelet ) for talking to Docker as container runtime. I will talk about dockershim in the later section of the blog.
Also, docker has grown and matured over the last few years and has gained a stack of components like runc (open container initiative), containerd (CNCF project). OCI (est. in June,2015) splits docker into two parts:
1) to handle docker cli & processing requests and 2) to handle container running functions i.e runC.
In this blog, we will see how we can deploy the Elasticsearch, Fluent-bit, and Kibana (EFK) stack on Kubernetes. EFK stack’s prime objective is to reliably and securely retrieve data from the K8s cluster in any format, as well as to facilitate anytime searching, analyzing, and visualizing of the data.
What is EFK Stack?
EFK stands for Elasticsearch, Fluent bit, and Kibana.
Elasticsearch is a scalable and distributed search engine that is commonly used to store large amounts of log data. It is a NoSQL database. Its primary function is to store and retrieve logs from fluent bit.
Fluent Bit is a logging and metrics processor and forwarder that is extremely fast, lightweight, and highly scalable. Because of its performance-oriented design, it is simple to collect events from various sources and ship them to various destinations without complexity.
In the previous blog, we discussed setting up Offline Kubernetes Cluster over on-premises servers. After setting up the Kubernetes cluster we need to have some basic components to manage the orchestration and monitoring of the Kubernetes Cluster which will help Horizontal Pod Autoscaler and Vertical Pod Autoscaler to get information about CPU/Memory. Also, we have to limit access to all the components and Microservice we have set up for the SSO tool.
To begin with, we need a service mesh tool to manage the traffic flow between multiple microservices and We have many tools for this like Istio, Linkerd, Cilium Service Mesh, Consul connect, etc. Here I am considering Istio.
Firstly, We will be talking Istio Setup over Kubernetes Cluster.
Istio is an open source service mesh that helps organizations run distributed, microservices-based apps anywhere. Istio enables organizations to secure, connect, and monitor microservices, so they can modernize their enterprise apps more swiftly and securely. Istio allows organizations to deliver distributed applications at scale. It simplifies service-to-service network operations like traffic management, authorization, and encryption, as well as auditing and observability.
In an organization, there are multiple projects, and every project has multiple users every user has a different role to perform, based on the role whether he is owner, maintainer, developer, reporter, or guest we assign the role to that user, but the main problem is that when we have to use those users to the different project then we have to do all the same task again. There is a better way to manage users in GitLab by creating groups and assigning those groups to the project.
What is GitLab Group?
In GitLab, we use groups to manage one or more related projects at the same time. We can use groups to manage permissions for your projects. If someone has access to the group, they get access to all the projects in the group. We can also view all of the issues and merge requests for the projects in the group, and view analytics that shows the group’s activity. We can also create subgroups in a group.