{"id":7205,"date":"2019-10-19T10:51:59","date_gmt":"2019-10-19T10:51:59","guid":{"rendered":"https:\/\/www.devopsschool.com\/blog\/?p=7205"},"modified":"2021-11-23T14:40:27","modified_gmt":"2021-11-23T14:40:27","slug":"top-10-devops-tools-every-software-engineer-should-learn-in-2019","status":"publish","type":"post","link":"https:\/\/www.devopsschool.com\/blog\/top-10-devops-tools-every-software-engineer-should-learn-in-2019\/","title":{"rendered":"Top 10 DevOps tools, every software engineer should learn in 2019."},"content":{"rendered":"\n

Now, here a question comes in the mind to the Software Engineers that through which tools he will go through for his better experience, for a few years, the DevOps philosophy has influenced the operations development and management in the IT industry. Companies need to be more agile, automate operations, and scale efficiently. To achieve this, DevOps aims to coordinate teams that used to work at isolated silos: developers and IT professionals.<\/em><\/p>\n\n\n\n

To achieve faster application delivery, the right tools must be used in DevOps environments. There is no single tool which fits all your needs such as server provisioning, configuration management, automated builds, code deployments, and monitoring. <\/strong><\/em> <\/strong>In this article, we will look into core tools which can be used in a typical DevOps environment.<\/strong><\/em> <\/strong><\/p>\n\n\n\n

Kubernetes<\/strong> is an\nopen-source container-orchestration system for automating application\ndeployment, scaling, and management. … It aims to provide a “platform\nfor automating deployment, scaling, and operations of application containers\nacross clusters of hosts”. It increases fault tolerance, load balancing in\na container cluster. Kubernetes maintains a desired state of cluster, this\ndesired state is described in YAML file. YAML file contains state of pods or\nslave nodes and replication unit for a cluster. Kubernetes uses this YAML file\nto maintain a desired state of cluster for example in case of one pod is\nserving more requests than other pod then it can automatically distribute this\nload to other pods, in case of one machine fails than it can configure another\npod to replace its place hence ensuring fault tolerance, load balancing and\nhigh availability in a cluster. Kubernetes is used in high performance data\ncentres like that of Google, Facebook, and Amazon Web Services. <\/p>\n\n\n\n

Jenkins<\/strong>– Everyone\nknows Jenkins, right? It\u2019s not the fastest or the fanciest, but it\u2019s really\neasy to start to use and it has a great ecosystem of plugins and add-ons. It is\nalso optimized for easy customization. We have configured Jenkins to build\ncode, create Docker containers, run tons of tests, and push to\nstaging\/production. It\u2019s a great tool, but there are some issues regarding\nscaling and performance. Jenkins is an open source automation server written in\njava. Jenkins provides automation of continuous delivery part. Jenkins is used\nin creating continuous delivery pipelines. Jenkins server will take our\napplication container from development environment and make it accessible to\ntesting environment, QA environment or any other non-production environment in\nthe beginning. Jenkins server is in the middle of whole CI\/CD pipeline. It\nautomates this whole process which means whenever a developer will commit a\nchange in a code that code will automatically be visible to testing server or\nQA team. They then can provide instantaneous feedback on these changes. Jenkins\nis used by Microsoft, Redhat, Rackspace, to name a few.<\/p>\n\n\n\n

Git<\/strong> is a\ndistributed version-control system for tracking changes in source code during\nsoftware development. It is designed for coordinating work among      programmers, but it can be used to track\nchanges in any set of files.Git was created 10 years ago following the Linux\ncommunity\u2019s need for SCM (Source Control Management) software that could\nsupport distributed systems. Git is probably the most common source management\ntool available today. After running Git internally for a short period of time,\nwe realized that we were better suited with GitHub. In addition to its great\nforking and pull request features, GitHub also has plugins that can connect\nwith Jenkins to facilitate integration and deployment. I assume that mentioning\nGit to modern IT teams is not breaking news, but I decided to add to it to the\nlist due to its great value to us.<\/p>\n\n\n\n

Docker<\/strong> is a\ncontainerization technology. Containers consist of all the applications with\nall of its dependencies. These containers can be deployed on any machine\nwithout caring about underlying host details. Containers can be a .net\napplication or a website along with its dependencies like .net or lamp stack in\ncase of website application. These containers are used to automate the\ndeployment process of application in production and non-production environment.<\/p>\n\n\n\n

Everything that can be said about how Docker is transforming\nIT environments has already been said. It\u2019s great\u2026life changing, even \u2014\n(although we\u2019re still experiencing some challenges with it). We use Docker in\nproduction for most services. It eases configuration management, control\nissues, and scaling by allowing containers to be moved from one place to\nanother.<\/p>\n\n\n\n

We see Docker progressing and look forward to welcoming the\ncompany\u2019s new management and orchestration solutions. For those who might be\nhaving issues with Docker, we\u2019ve also compiled a list of challenges and\nsolutions when migrating to Docker.<\/p>\n\n\n\n

Puppet <\/strong>is an\nopen-core software configuration management tool. It runs on many Unix-like\nsystems as well as on Microsoft Windows, and includes its own declarative\nlanguage to describe system configuration. It is an alternative to Ansible and\nprovides better control over client machines. Puppet comes up with GUI which\nmakes it easy to use than Ansible. Puppet is cross platform, it runs on both\nUnix and Microsoft Windows. Puppet uses a manifest file and applies those\nspecifications across all machines. Unlike Ansible, Puppet is agent-based tool.\nPuppet master runs on master machine and Puppet agent runs on all client\nmachines. Puppet is used by Microsoft, Google, Accenture, etc. Puppet allows\ncompanies to simultaneously manage dozens of development teams and thousands of\nresources. This is because it automatically understands the inherent\nrelationships that occur in any infrastructure.<\/p>\n\n\n\n

It manages dependencies and treats errors in a smart way.\nWhen it finds a configuration that fails, it skips the other dependent\nconfigurations. Due to all this, it has become one of the most used DevOps\ntools. Puppet has over 5,000 modules and support for hundreds of external\ntools.<\/p>\n\n\n\n

Ansible<\/strong>– Again,\nsimplicity is key. Ansible is a configuration management tool that is similar\nto Puppet and Chef. Personally, we found those two to have more overhead and\ncomplexity to our use case\u2013 so we decided to go with Ansible instead. We know\nthat Puppet and Chef probably have a richer feature set, but simplicity was our\ndesired KPI here. We see some tradeoffs between configuration management using\nAnsible and the option to simply kill and spin new application instances using\na Docker container. With Docker, we almost never upgrade machines but opt to\nspin new machines instead, which reduces the need to upgrade our EC2 cloud\ninstances. Ansible is used mostly for deployment configuration mostly. We use\nit to push changes and re-configure newly-deployed machines. In addition, its\necosystem is great, with an easy option to write custom applications. Ansible\nis an open source application which is used for automated software\nprovisioning, configuration management and application deployment. Ansible is\nthe backbone of controlling an automated cluster environment consisting of many\nmachines. Ansible works on client server model. Client acts as a master which\nis centre point in our cluster and provides centralized control of all client\nmachines (slaves) that are connected to it. We can give any command to any\nclient machine or deploy any application to more than one machine from a single\nmaster machine. Ansible only requires SSH for communication so it does not need\nany software dependency to run. Ansible works on Unix.<\/p>\n\n\n\n

Chef<\/strong> is a\nconfiguration management tool. Chef is used to manage configuration like\ncreating or removing a user, adding SSH key to a user present on multiple\nnodes, installing or removing a service, etc. We can manage upto 10,000 nodes\nby using chef. These changes are pushed by cookbooks or recipes. Chef has three\ncomponents viz. Chef Server, workstation and nodes. Chef server is a central\npoint where all details of our Chef infrastructure resides. Chef workstation\nholds recipes or cookbooks which pushes particular configuration to our chef\ninfrastructure. Nodes are simple machines which are configured by using chef.\nChef has API support from AWS, Azure, Rackspace, which makes it easy to use\nwith infrastructure as a code methodology.<\/p>\n\n\n\n

We also looked into Icinga, which was originally created as\na fork of Nagios. Its creators aim to take Nagois to the next level with new\nfeatures and a modern user experience. There is a debate within the open source\ncommunity about the merits of Nagios and its stepchild, but for now we are\ncontinuing to use Nagios and are satisfied with its scale and performance. The\nswitch to newer technology, such as Icinga, may be appropriate in the future as\nwe progress.<\/p>\n\n\n\n

Gradle<\/strong> is an\nopen-source build-automation system that builds upon the concepts of Apache Ant\nand Apache Maven and introduces a Groovy-based domain-specific language (DSL)\ninstead of the XML form used by Apache Maven for declaring the project\nconfiguration. Gradle allows you to build any software, because it makes few\nassumptions about what you\u2019re trying to build or how it should be done. The\nmost notable restriction is that dependency management currently only supports\nMaven- and Ivy-compatible repositories and the file system.<\/p>\n\n\n\n

This doesn\u2019t mean you have to do a lot of work to create a\nbuild. Gradle makes it easy to build common types of project \u2014 say Java\nlibraries \u2014 by adding a layer of conventions and prebuilt functionality through\nplugins. You can even create and publish custom plugins to encapsulate your own\nconventions and build functionality.<\/p>\n\n\n\n

Nagios<\/strong>–\nInfrastructure monitoring is a field that has so many solutions\u2026 from Zabbix to\nNagios to dozens of other open-source tools. Despite the fact that there are\nnow much newer kids on the block, Nagios is a veteran monitoring solution that\nis highly effective because of the large community of contributors who create\nplugins for the tool. Nagios does not include all the abilities that we had\nwanted around the automatic discovery of new instances and services, so we had\nto work around these issues with the community\u2019s plugins. Fortunately, it\nwasn\u2019t too hard, and Nagios works great. Nagios is used for continuous\nmonitoring of infrastructure. Nagios provides server monitoring, application\nmonitoring, network monitoring. By Nagios we can monitor whole data center from\na single server. We can see whether switches are working correctly, servers are\nnot having too much load or if any part of application is down. It provides a\nnice GUI interface to check various details like how much memory is used, what\nis fan speed, routing tables of switches, or state of SQL server. Nagios has a\nmodular design. It supports NRPE plugins which can be used to add monitoring parameter\non existing Nagios. There are various plugins available on the internet which\ncan be used freely to add features to Nagios. Nagios is most popular tool in\ncontinuous monitoring.<\/p>\n\n\n\n

Bamboo<\/strong>–  Atlassian is one of the companies that must be\ntaken seriously when referring to DevOps. In this field, Bamboo is a tool that\ngathers compilations, tests and automated versions in one single workflow.\nThus, Bamboo creates multi-phase compilation plans; configures triggers to\ninitiate complications after each commit, and assigns agents to essential\ncompilations and deployments.<\/p>\n\n\n\n

In the test phase, it allows making automated tests to\nrevert any product exhaustively with each change. Similarly, it allows\nconducting parallel tests to facilitate and speed up errors detection. Finally,\nit automates the deployment of projects at every possible environment, offering\nflow control with specific permissions to each environment.<\/p>\n\n\n\n

Although it has lot fewer plugins than Jenkins (its great competitor in this field), its main advantage is being more complete out of the box solution, and that it can be integrated with other Atlassian tools, such as Jira, Bitbucket or Fisheye. <\/p>\n\n\n\n

Reference<\/h3>\n\n\n\n