The DevOps market expects to grow from $2.9 billion to $8 billion by 2024 (IDC). This is due largely in part to the emergence of more sophisticated DevSecOps and DevOps tools. There are a host of tools available, many of which accomplish the same task. However, the best tools help your team be agile and build robust, reliable, and scalable CI/CD pipelines with ease. Here’s our take on the top 5 best DevOps tools to help you get the most out of your CI/CD process.
1. Jenkins
Jenkins is a well-known open-source automation server. It is used to implement continuous integration (CI) and continuous delivery (CD). Once the DevOps tool iis configured, it can pull the code from the repository, run a series of automated tests and execute builds. Implementing CI/CD with technology like Jenkins simplifies the build process. It helps to ensure quality code delivery with each build. This is especially useful when large development teams are working on a single project which could result in competing code commits. These types of scenarios often cause difficult troubleshooting which slows down the deployment process.
One of the most significant advantages of this DevOps tool is the ability to quickly detect and correct errors. If newly contributed code introduces a flaw into the build, it is caught instantly. That way offending code can then be isolated, changed, and recommitted.
The Jenkins CI server can be executed as a standalone application with a built-in Java servlet container or as a servlet in other Java servlet containers such as Apache Tomcat.
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2. Docker
Docker is an open-source container-based platform for creating, managing, and deploying applications. This DevOps tool helps you to isolate apps from infrastructure and build software quickly.
Docker containers are virtual operating systems that include all libraries, system tools, code, and runtime in a lightweight and portable package. This means that you can deploy your containerized app anywhere without additional configuration. Containers are built using what is known as a Dockerfile. This file contains the instructions necessary for building an image, which is a template of a container. Once the image is created, it can be used to build a container. This process is similar to making a virtual machine from a .ova file, but it is significantly faster because it does not include all of the operating systems.
A single container can operate anything from a small microservice to a large application. Docker environments isolate application components from each other. That way, these components aren’t competing for the same resources. It also enables a more secure environment because issues, such as a security concern in one container, won’t negatively impact the rest of the containers on the server.
Whether the system is a local data center or a public cloud, this separation enables quick and consistent deployment of container-based applications. Containers allow more control over resources, boosting infrastructure efficiency and resulting in improved utilization of computer resources.
Docker containers are lightweight, so they start very quickly and use fewer resources than virtual machines (VMs). Developers will find it easier to move applications between environments, including testing and production environments. Docker containers also allow for more efficient resource utilization in production environments by allowing applications to share resources.
3. Ansible
Ansible is a system management system used to configure and provision servers, storage, network devices and software. It’s goal is to minimize an issue prevalent in complex environments; management of large numbers of system components. Often, these devices need to be configured and deployed using the same parameters. Ansible groups these components together so they can be configured and provisioned at the same time rather than independently.
How does this DevOps tool work? First, a playbook is developed, which contains the instructions for how to configure a target system. Ansible then executes the playbooks to configure the system per the instructions in the file. A few of the most notable features of the tool include:
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Installing software packages
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Configuring network devices
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Running tests to verify configuration meets required parameters
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Updating device or component inventory files
Ansible has been designed from the ground up to be easy to use. It has a simple syntax making it easy for non-programmers to get started with it. It is also highly configurable allowing you to define how each task should be executed.
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4. Prometheus
Monitoring and alerting are two of the most important components of an infrastructure monitoring system. Monitoring is the process of checking the status of your production environment to make sure everything is running well. Alerting is the process that automatically takes action when something goes wrong, such as an unexpected spike in CPU usage that could indicate a network attack.
Prometheus is a monitoring and alerting DevOps tool that provides real-time notifications about system status. Prometheus is a time series database that can be used to execute Docker and Go apps. The tool collects data from tasks directly or via an intermediary gateway optimized for temporary jobs. A key feature of the tool is a robust dashboard used to display metrics about system performance. Users also have the option of querying the data using the PromQL querying language. The following are some of the key benefits of using Prometheus:
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Does not require agents to be installed on nodes or machines. The monitoring data is collected directly from the containers, applications, and services.
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Supports a wide range of languages. Although it is primarily written in Go, Prometheus can be used with other programming languages such as Python, Java, Ruby, and Node.js.
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Supports embedded scripting languages such as Lua and has a plugin system that allows users to write custom plugins to extend its functionality.
Prometheus was designed to be scalable and distributed across a cluster of nodes or machines, so that the monitoring data collected is not stored on a single machine or node but distributed across multiple machines. This ensures that even if a single machine or node fails, the monitoring data will not be lost.
5. Kubernetes
Kubernetes, often known as "K8s," orchestrate the execution of containerized applications over a cluster of hosts. Using on-premises infrastructure or public cloud platforms, this DevOps tool automates the deployment and administration of cloud-native apps. It automates dynamic container networking and distributes application workloads throughout a Kubernetes cluster. Kubernetes also enables resiliency by allocating storage and persistent volumes to running containers, offering automatic scaling, and continuously working to maintain the desired state of applications.
Kubernetes provides the following:
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Self-healing and self-managing capabilities with automated failure recovery.
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A declarative API that gives you the ability to define the desired state of your app rather than how it should be configured. This allows developers to focus on writing code instead of worrying about infrastructure details.
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Scalability and resource utilization with support for horizontal auto-scaling, load balancing, service discovery, and container networking.
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Security via authentication and authorization mechanisms that restrict access to resources in a cluster based on user identity. This is especially useful for containerized applications because they can run as non-root users with restricted privileges.
Why Packagecloud?
Packagecloud is a cloud-based service that enables you to keep all of the packages that need to be distributed across your organization's machines in one repo without having to own any of the infrastructure involved in hosting it. The tool works seamlessly with DevOps tools. As a result, your team can focus on delivering reliable code consistently without the extra headache of server maintenance. Sign up for the Packagecloud free trial to get set up today.
