Containers – DevopsCurry

Service ,All about CAAS (Container-as-a-Service)

Shiwani Sharma — Mon, 22 Apr 2024 04:52:59 +0000

Introduction TO CAAS (Container As A Service)

CAAS is a cloud service that permit and provide the platform to software developers and IT department to organize, run, deploying and scaling containerized applications. The weight of these containers are very light, movable that give a summary of software and its outpost, permits for efficient and smooth flow of deployment across several computing environments. Users can concentrate on deploying, developing application without dealing with the difficulties of infrastructure management.

This CAAS platform also consists scaling, networking, orchestration and monitoring. One of the most important examples of the CAAS platform are Docker Swarm, Amazon ECS (Elastic Container Service) & Kubernetes.

In the other ways you can also says a cloud service model that clarify the management and deployment of containerized applications.

Wikipedia explain the concept of CAAS as a service-oriented model, where the service provider delivers the content on demand to the service consumer via web services that are licensed under subscription. The term “Content as a service” (CaaS) is considered to be part of the nomenclature of cloud computing service models & Service-oriented architecture along with Software as a service (SaaS), Infrastructure as a service (IaaS), and Platform as a service (PaaS).

Benefit Of CAAS

The person or the users who are using container as a service, they only have to pay for those resources they are using as like scheduling capabilities, load balancing and compute instances etc. It permits the efficient utilization of resources by automatically adjusting container placement based on accessible capacity.
It has high availability: This platform consists of the features for permits high availability, as like automated load balancing and failover and support the maintain the availability of applications even at the time when find some problems or arising the failures of hardware.
Resources Orchestration: This platform permits for the structured using resources by automatically regulate container that is based on accessible space. The platform of CAAS has automate the deployment, scaling and organized the containerized applications. Orchestration tool help in many difficult tasks as like rolling updates, decrease the operational overhead, load balancing etc. and one of the famous orchestration tool are Kubernetes.
Cost- Efficiency: CAAS platform optimized the utilization of resources and automating management tasks and that’s the reasons of cost saving. When we uses this platform we can save the resources for the containers it is required, and one of the important features of CAAS is it has automated scaling that will support and assure you that they are not over provisioning resources.
Increased Application Performance: When we compared CAAS platform with others such as virtual machines, some others startup times and all around performance of applications, it have lower overhead. This will help to provide good compassion and experience.

Why CAAS is important?

One of the main benefit or the importance of CAAS is you can shift from one cloud to another and even you can go back to the server system that is physical. It also permits you to build multi and hybrid cloud system for the organizations. Now we will explain some of the other important reasons or points why CAAS (Container As A Service) is important is as follow:

Users can use the resources as per their requirement and they can only pay for the resources they are using. This is the best benefit because it help to save the time and money of the users, they can select or choose the resources they want to work in.
Developers gets the benefits of CAAS just by developing a application deployment and scalable container and this benefit is important to the IT teams, the reasons of its importance is it provide a container deployment service in a safe environment.

Challenges Of Using Container-as – a – Service (CAAS)

There are some challenges that CAAS has to faces and some of these are ( Networking, Security, Data Management, Cost Management, Skill Set Challenges) as follow:

Networking: It is difficult to manage network for containers and in case of large-scale deployments. In a large container or for small as well it is complex to make a communication or coordination between containers and assure for proper network segmentation and that become also challenging to handle outer access.

Security: It may arises the security risks, if the OS Kernel host is not properly isolated. It important to execute the security best practices as like utilizing reliable images, sufficient container privileges etc. It is also difficult for the security challenges to access control and privilege escalation.

Data Management: This platform container are manufactured to be stateless, but there are many application that need to stateful data and that become challenges for Container-as-a-services. In the other word you can also says that managing data backups and assuring data consistency is also become challenge.

Cost Management: It is very difficult to handle and monitor cost effectively due to the lack of visibility into the container resources. There is also a problem arises in terms of network-related cost and data transfer cost is increases mostly while serving the micro services architectures where containers are interact with each other.

Conclusion: As we journeyed through the world of Container as a Service (CAAS), this CAAS platform also consists scaling, networking, orchestration and monitoring. This platform consists of the features for permits high availability, as like automated load balancing and failover and support the maintain the availability of applications even at the time when find some problems or arising the failures of hardware.

As we conclude our exploration of CAAS, it is very clear that success lies in a holistic approach and it consist of some orchestration tools, that secure the containerized applications and navigate the cost management.

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Why you should consider adopt Containers

Thu, 14 Jan 2021 16:40:40 +0000

Why you should adopt Containers in 2021

DevOps and Container Technology

With the constant demand for changing environments, DevOps and Container technology can work well when combined. Containers help to keep the development more agile and also ensures continuous delivery thus making containers a great tool for the DevOps process.

Containers provide an approach to package the application’s source code, libraries, configuration files, and all dependencies in a single object. This object is then able to run applications from a small to a large complex. Containers offer OS-level virtualization that allows you to share the operating system on a server and run it as an isolated resource. Unlike virtual machines, containers do not contain images for the operating system which makes them light-weight and portable.

If you are working on a large project then you can deploy multiple containers which can be managed by a container orchestrator. Containerization simplifies the DevOps process by reducing the interdependencies between IT operations and the Dev team. Containerization helps to streamline the development and production process. By including a container method will positively transform DevOps.

Understanding the role of containers in DevOps

By leveraging containers in the DevOps process you will be able to serve your customers faster, better, and effectively continuously. You must adopt a solid strategy to build and maintain a container environment. Though DevOps eased the software delivery process containerization will fast-paced your application delivery in an efficient way. Before applying the container, you should understand a few points for effective container management in DevOps.

Integration with IT

The main selection criteria for the container technology is how well and easily it gets integrated with existing IT enterprises without impacting its working pipeline and DevOps process. By far, storage management is considered to be the most important integration point for containers, if it gets integrated with it efficiently then it will work well with the current DevOps process.

Security and compliance framework

Ensuring that the container is in the line with the security and compliance framework of the company is important for DevOps success. You can ensure safety and compliance by continuous scanning, creating a private repository, and documenting rules for it.

Support hybrid infrastructure

Containers are dynamic and can be stored on various platforms as per the business requirement. You can host containers on-premise VMs, off-premise container service, off-premise VMs, and many more. But in some cases, organizations require multiple container services that require hybrid infrastructure to improve performance.

Microservices

With the help of microservices, you can easily break down large applications into smaller components which can be added to larger applications. It is not necessary to run large applications at a time, but you can deploy smaller components individually that will speed up the process and reduce turnaround time. You can deploy each microservice within a container.

PAAS and FAAS

Container adoption works well for Platform as a Service and Function as a Service due to the flexibility of the container. The container helps PaaS to easily onboard the legacy applications and allows FaaS to delay the code releases.

Application-centric container management

It allows the policy-driven deployment, monitoring, alerting, scaling, and updates of the container applications without imposing any infrastructure restrictions. Application-centric container management provides an abstraction layer on top of different container services that allows the customer to deploy their application in the private or public cloud.

Benefits of containers in DevOps

Containers ensure a streamlined process that allows you to build, test, deploy, and redeploy applications or programs in multiple environments. Containerization offers immense benefits to simplify the DevOps workflow. Some of the benefits are mentioned below.

Provide simple updates- if you want to deliver software continuously then applications need to be updated in a constant and streamlined manner. Containers allow easy software or application updates. Containers allow applications to be distributed in multiple microservices and an update to a small part of your application does not impact other parts of the application.
Containers support multiple Frameworks– DevOps allows the agility to switch between multiple programming frameworks and containers. With containers, you can run any type of application irrespective of the language they are written in. You can then move those containers easily among different hosts.
Makes DevOps workflow consistent- whenever you create and deploy your application within a container, the environment remains the same throughout the delivery chain. This process provides better team collaboration and makes it easy as every team member is working in the same containerized environment.
Cost-saving- unlike VMs, containers do not need OS which may include a cost. Containers run side by side and share the OS kernel of a single physical machine. Also, containers do not require allocation of resources and work on microservices which minimizes the resource overhead.
Faster agility- creating a new container is much faster than setting up a new virtual machine. Once deployed, containers can easily scale as per the growing business demands and data.
Containers are immutable- containers come with precise and controlled environments to create a CI/CD pipeline. Containers are immutable, the software that is tested will be the same as the software to be deployed without any discrepancies.
Ensures security- to maintain container security, the lifetime of the container needs to be reduced to protect it from hackers which gives them a little window to play. You can also refresh containers every minute or so and it keeps the containers up-to-date.

Conclusion

In a nutshell, here’s what Containers can do for you: They can get more applications running on the same hardware than other technologies; they make it easy for developers to quickly create ready-to-run containered applications; and they make managing and deploying applications much easier.

So we have seen how the Container technology is overtaking the entire software world by a storm. Containers are not a technology but more of a revolution, it is just a matter of time when all software applications will be using and running on Containers. So now is the time to think and decide if you have already not started using containers within your organisation, to make a try and adopt Containers as a part of your codebase.

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Exploring alternatives to Docker? Podman could be your ultimate solution !

Tue, 05 Jan 2021 14:53:54 +0000

Podman: A Daemonless Docker Alternative

Containerization has become one of the most popular technology in the last few years. Today companies focus on designing cloud-native applications that can be run within containers as microservices. It improves the scalability of the applications to run on any platform irrespective of the underlying system. One of the commonly used container engines is Docker which is preferred to run Kubernetes to orchestrate their applications.

A whole new revolution of containerization started with Docker containers ,where the daemon process manages the whole bunch of things and soon it became one of the most popular and widely used container management systems.

But recently Podman has emerged as a strong competitor for Docker. With Docker, you depend on daemons while with Podman you can run directly using runC runtime containers. There is more to Podman which we will discuss below.

What is Podman?

Podman is a daemon-less container engine for developing, managing, and running OCI Containers on your Linux machines. Containers can either be run as root or in rootless mode.

Podman was developed by Red Hat in 2018. Podman is an open-source container management tool that allows you to build, manage, and to run OCI containers. Podman is also a containerization engine that works on a completely different approach than Docker. Podman does not depend on daemon to work, unlike Docker that uses both Docker CLI and Docker Daemon to work with images and registries. The main drawback of Docker using daemon is that it has to depend on a single process, which also leads to a single point of failure creating all the dependent child processes that will also get failed or orphaned. This failure limits Docker’s flexibility as a containerization engine.

Podman is designed according to OCI standards that allow Podman to interact directly with the kernel, containers, and images. Podman is more secure than Docker as it does not require root access.

Features of Podman

Podman images are created according to OCI standards so that they can be easily pushed to other container management tools and registries.
You can run Podman without having the root access and privileges.
Podman allows you to manage one or more containers to operate them together and perform various actions on pods.
Currently, Podman is available for Linux-based systems only and does not have a wrapper available for Windows and MacOS.
Unlike Docker compose, the feature for Podman is under progress due to which Podman will not be able to manage multiple containers locally.
Podman is mature enough to deploy applications and microservices in containers.
To manage images and builds for your podman instance you can use Buildah.
Podman ensures security in a holistic way making the entire ecosystem safe.
Podman allows you to access resources that will create a highly available network for your application provided by CNI which is great for developers.
With the help of Podman, you can easily scan OCI images without downloading them. Also, you can move them from one repository to another.
It uses the Buildah tool to manipulate or create images within a running container.
Podman runs containers with Systemd enabled by default.
Podman uses UID separation using namespaces that adds up an extra isolation layer while running the containers.

The Podman approach is simply to directly interact with the image registry, with the container and image storage, and with the Linux kernel through the runC container runtime process (not a daemon)

Image Source: https://developers.redhat.com/blog/2019/02/21/podman-and-buildah-for-docker-users/

Podman vs Docker

Below are some differences mentioned between Podman and Docker.

The main and the topmost difference is the Daemonless feature of Podman. On one hand, Docker runs each task using Docker daemon while on the other hand, Podman is light-weight and does not require a continuous running instance to run the containers.
The other main difference is that Podman is rootless which means Podman can run either as a root or non-root. In whatever way you run the Podman containers it will be compliant without compromising the security.
Podman supports running pods which means a collection of containers that can be run close to each other. Podman supports running multiple containers together.
Podman allows you to store images and containers in different places while Docker stores images locally.
Podman works on the traditional fork-exec model while Docker works on the client-server architecture of the containers.

Conclusion

Now without a daemon to worry about, you can easily create and manage complex containers while maintaining security and keeping the ecosystem efficient with the help of Podman as your containerization engine.

That being said Podman is still a new technology which is evolving and it might be better to be in a `wait and watch` situation, before we start seeing community adoption for Podman and it becomes a more matured and stable tool. You can definitely try it on your local machines and explore it more, but taking it to your production environment might still need some time.

What are your thoughts on Podman and this post, please do share with us in comments.

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Cloud Cost Optimisation and saving on DevOps in 2021

Tue, 29 Dec 2020 07:27:24 +0000

DevOps 2021: Optimise your DevOps cost and Cloud spend

Introduction

As companies are moving towards cloud technology in integration with DevOps, they are getting huge benefits out of it. But a serious problem occurs when implementing the latest tools and strategies turns into spending a massive amount of money. Cross-cutting is the only way that companies focus on while maintaining their quality. Companies are now emphasizing the methods that help them to reduce unnecessary costs and optimize cloud spend.

But what is the way that companies get to know their actual expenditure in advance so that they can control and optimize in the first place? Also, the DevOps team could not have the actual visibility of how their decision is impacting the cloud costs. So the main goal is to implement the DevOps strategies that can optimize the cloud costs.

Ways to reduce DevOps costs

Every public cloud provider wants to reduce their costs thus wants to focus on implementing DevOps strategies that blend well in the environment. But public clouds are not completely cost-effective. But considering the below points you can somehow reduce the DevOps costs.

* Automate scaling

A business goes through many peaks and troughs concerning coming requests. Such a situation like online biggest sales when a request to particular sites rises and may lead to disrupting the working of an application. You must prepare your application for these peaks otherwise the invested money and resources will get wasted. By automating the scaling will enable the application to add servers whenever they are required and turning extra servers when they are not required.

* Avoid unnecessary VMs usage

Public clouds offer pay per use service that helps IT companies to manage their unnecessary requests. But there can be a cost issue when you do not manage your VMs, an overrun can result in high cost. It is important to identify the duration when you can shut off the VM without impacting the production backup. It is not always necessary to keep your staging environment up and running. So it is a better approach to turn off the unwanted resources saving the costs.

* Manage Cloud sprawl

The way you control your Devops toolchain, the cloud usage also needs to be controlled by DevOps. Cloud sprawling can lead to massive costs due to unmanaged VMs and cloud instances. This can be managed if you place a well-implemented strategy to outline the number of VMs that falls into the budget. A proper check and balance can manage the cloud sprawl cost.

* Protect against security gaps

A company must enforce their security policies so there can be no flaws left at both users as well as employee end. Your complete system will be vulnerable if any of the flaws will get exposed and can be easily accessible by hackers for breach. This will lead to more cost and investment for security and recovering from the impact.

* Developing applications in containers

With the help of containers, you can easily host your applications and this will increase team collaboration. This will reduce the cost of the resources to run the enterprise. Also, containers help create a simple software update process without impacting the service. Containers allow the DevOps team to choose any programming environment to run their application.

Cloud Cost Optimization: What it means?

Cloud cost optimization is the method that helps you to reduce the overall cloud cost by identifying the mismanaged resources, selecting the right computing services, and eliminating waste. Optimizing cloud spend means that the developers and the DevOps team should have the visibility of how their decision is impacting the costs. So that they can make cost-effective decisions for the organization without impacting the pace of the automation process.

But if you are using the cloud then you might be aware of the fact that the cloud offers pay per request to lower IT costs. But some of the services charge for the complete resources whether they are used by the company or not which results in wasted resources. Once the cost is optimized then you can easily spend that cost on some meaningful tasks like building new applications.

Cloud Cost Optimization Techniques- The Best Practices

Below are some strategies that you can implement within your organization to cut down on the bill and save money by eliminating unused resources.

Identifying the unused resources
It is important to identify the unused resources from your end. There might be cases when an administrator signs up for some temporary server to compute data and then forgets to turn it off. This will lead to unnecessary AWS bills. This is a common mistake that goes around companies and leaves the resources wasted.

Utilize heatmaps
Heatmaps are a common and important technique that is used for optimizing the cloud cost. A heatmap is a visual tool that displays peaks and valleys in computing demand. Developers and administrators can use this information to manage the start and stop features for cost optimization. It helps you to find servers that may not be required at weekends and you can turn it off to save cost.

Take advantages of spot instances
Spot instances can help you to save AWS spend and are available to be purchased for immediate use. Spot instances are suitable for particular computing cases like batch jobs which can be terminated quickly. Such jobs are common in almost every company so spot instance should be a part of all cloud cost optimization strategies.

Minimize the data transfer cost
You can minimize the cost by making sure that the object storage and the compute services fall in the same region. This is because the data transfer is free in the same region. You can reduce the API cost by using batch objects instead of a large number of small files.

Opt for Serverless computing
You can also choose serverless computing options like AWS lambda, Azure Functions or Google Cloud functions or even open osurce options like OpenFaas etc. It allows developers to configure the cloud instances which will save a lot of time and also operational expenses.

Purge or migrate unwanted files and data after certain period
You can configure rules for data deletion or migration between different types of storage. This drastically reduces the long-term storage costs. All the major cloud vendors have the feature of Lifecycle Management.

Using auto-scaling to reduce costs during non-peak hours
Most of the applications have varying traffic and loads during their peak and non-peak hours, maybe during a day or a week. So identifying this pattern of high peak hours and using autoscaling your resources and then again scaling them down during non-peak hours, can also save a lot on your cloud cost.Also turning-off your unused instances when not needed, can significantly lower your monthly cloud bill.

Compress your Data before Storage
Compressing your data also reduces your storage requirements, thereby reducing the cost of storage.There are many data compression tools available in the market that you can use to squeeze your data into the cloud storage, hence reducing your storage costs.

Conclusion

We all agree with the fact that Cloud computing and Devops are future technologies and hold great potential.However over a period of time, the money invested in these technologies starts to grow exponentially and shows in your monthly bills. This is when organizations start feeling if implementing Devops or moving to Cloud was a bad financial decision for them. However if you follow the above mentioned points during your Devops and Cloud implementation, definitely you can streamline your expenses and also cut-off on a lot if unwanted spend on unused instances, storage,data transfer etc.

So the promise of saving money using the Cloud can be achieved, as long as detailed attention is paid to Cloud Cost Optimization during the planing and implementation phases.

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