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Most trusted JOB oriented professional program
DevOps Certified Professional (DCP)

Take your first step into the world of DevOps with this course, which will help you to learn about the methodologies and tools used to develop, deploy, and operate high-quality software.

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DevOps to DevSecOps – Learn the evolution
DevSecOps Certified Professional (DSOCP)

Learn to automate security into a fast-paced DevOps environment using various open-source tools and scripts.

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Get certified in the new tech skill to rule the industry
Site Reliability Engineering (SRE) Certified Professional

A method of measuring and achieving reliability through engineering and operations work – developed by Google to manage services.

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Master the art of DevOps
Master in DevOps Engineering (MDE)

Get enrolled for the most advanced and only course in the WORLD which can make you an expert and proficient Architect in DevOps, DevSecOps and Site Reliability Engineering (SRE) principles together.

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Azure DevOps Solutions Expert

Learn about the DevOps services available on Azure and how you can use them to make your workflow more efficient.

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Learn and get certified
AWS Certified DevOps Professional

Learn about the DevOps services offered by AWS and how you can use them to make your workflow more efficient.

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Top 10 DevOps tools, every software engineer should learn in 2019.

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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.

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. In this article, we will look into core tools which can be used in a typical DevOps environment.

Kubernetes is an open-source container-orchestration system for automating application deployment, scaling, and management. … It aims to provide a “platform for automating deployment, scaling, and operations of application containers across clusters of hosts”. It increases fault tolerance, load balancing in a container cluster. Kubernetes maintains a desired state of cluster, this desired state is described in YAML file. YAML file contains state of pods or slave nodes and replication unit for a cluster. Kubernetes uses this YAML file to maintain a desired state of cluster for example in case of one pod is serving more requests than other pod then it can automatically distribute this load to other pods, in case of one machine fails than it can configure another pod to replace its place hence ensuring fault tolerance, load balancing and high availability in a cluster. Kubernetes is used in high performance data centres like that of Google, Facebook, and Amazon Web Services.

Jenkins– Everyone knows Jenkins, right? It’s not the fastest or the fanciest, but it’s really easy to start to use and it has a great ecosystem of plugins and add-ons. It is also optimized for easy customization. We have configured Jenkins to build code, create Docker containers, run tons of tests, and push to staging/production. It’s a great tool, but there are some issues regarding scaling and performance. Jenkins is an open source automation server written in java. Jenkins provides automation of continuous delivery part. Jenkins is used in creating continuous delivery pipelines. Jenkins server will take our application container from development environment and make it accessible to testing environment, QA environment or any other non-production environment in the beginning. Jenkins server is in the middle of whole CI/CD pipeline. It automates this whole process which means whenever a developer will commit a change in a code that code will automatically be visible to testing server or QA team. They then can provide instantaneous feedback on these changes. Jenkins is used by Microsoft, Redhat, Rackspace, to name a few.

Git is a distributed version-control system for tracking changes in source code during software development. It is designed for coordinating work among      programmers, but it can be used to track changes in any set of files.Git was created 10 years ago following the Linux community’s need for SCM (Source Control Management) software that could support distributed systems. Git is probably the most common source management tool available today. After running Git internally for a short period of time, we realized that we were better suited with GitHub. In addition to its great forking and pull request features, GitHub also has plugins that can connect with Jenkins to facilitate integration and deployment. I assume that mentioning Git to modern IT teams is not breaking news, but I decided to add to it to the list due to its great value to us.

Docker is a containerization technology. Containers consist of all the applications with all of its dependencies. These containers can be deployed on any machine without caring about underlying host details. Containers can be a .net application or a website along with its dependencies like .net or lamp stack in case of website application. These containers are used to automate the deployment process of application in production and non-production environment.

Everything that can be said about how Docker is transforming IT environments has already been said. It’s great…life changing, even — (although we’re still experiencing some challenges with it). We use Docker in production for most services. It eases configuration management, control issues, and scaling by allowing containers to be moved from one place to another.

We see Docker progressing and look forward to welcoming the company’s new management and orchestration solutions. For those who might be having issues with Docker, we’ve also compiled a list of challenges and solutions when migrating to Docker.

Puppet is an open-core software configuration management tool. It runs on many Unix-like systems as well as on Microsoft Windows, and includes its own declarative language to describe system configuration. It is an alternative to Ansible and provides better control over client machines. Puppet comes up with GUI which makes it easy to use than Ansible. Puppet is cross platform, it runs on both Unix and Microsoft Windows. Puppet uses a manifest file and applies those specifications across all machines. Unlike Ansible, Puppet is agent-based tool. Puppet master runs on master machine and Puppet agent runs on all client machines. Puppet is used by Microsoft, Google, Accenture, etc. Puppet allows companies to simultaneously manage dozens of development teams and thousands of resources. This is because it automatically understands the inherent relationships that occur in any infrastructure.

It manages dependencies and treats errors in a smart way. When it finds a configuration that fails, it skips the other dependent configurations. Due to all this, it has become one of the most used DevOps tools. Puppet has over 5,000 modules and support for hundreds of external tools.

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

Chef is a configuration management tool. Chef is used to manage configuration like creating or removing a user, adding SSH key to a user present on multiple nodes, installing or removing a service, etc. We can manage upto 10,000 nodes by using chef. These changes are pushed by cookbooks or recipes. Chef has three components viz. Chef Server, workstation and nodes. Chef server is a central point where all details of our Chef infrastructure resides. Chef workstation holds recipes or cookbooks which pushes particular configuration to our chef infrastructure. Nodes are simple machines which are configured by using chef. Chef has API support from AWS, Azure, Rackspace, which makes it easy to use with infrastructure as a code methodology.

We also looked into Icinga, which was originally created as a fork of Nagios. Its creators aim to take Nagois to the next level with new features and a modern user experience. There is a debate within the open source community about the merits of Nagios and its stepchild, but for now we are continuing to use Nagios and are satisfied with its scale and performance. The switch to newer technology, such as Icinga, may be appropriate in the future as we progress.

Gradle is an open-source build-automation system that builds upon the concepts of Apache Ant and Apache Maven and introduces a Groovy-based domain-specific language (DSL) instead of the XML form used by Apache Maven for declaring the project configuration. Gradle allows you to build any software, because it makes few assumptions about what you’re trying to build or how it should be done. The most notable restriction is that dependency management currently only supports Maven- and Ivy-compatible repositories and the file system.

This doesn’t mean you have to do a lot of work to create a build. Gradle makes it easy to build common types of project — say Java libraries — by adding a layer of conventions and prebuilt functionality through plugins. You can even create and publish custom plugins to encapsulate your own conventions and build functionality.

Nagios– Infrastructure monitoring is a field that has so many solutions… from Zabbix to Nagios to dozens of other open-source tools. Despite the fact that there are now much newer kids on the block, Nagios is a veteran monitoring solution that is highly effective because of the large community of contributors who create plugins for the tool. Nagios does not include all the abilities that we had wanted around the automatic discovery of new instances and services, so we had to work around these issues with the community’s plugins. Fortunately, it wasn’t too hard, and Nagios works great. Nagios is used for continuous monitoring of infrastructure. Nagios provides server monitoring, application monitoring, network monitoring. By Nagios we can monitor whole data center from a single server. We can see whether switches are working correctly, servers are not having too much load or if any part of application is down. It provides a nice GUI interface to check various details like how much memory is used, what is fan speed, routing tables of switches, or state of SQL server. Nagios has a modular design. It supports NRPE plugins which can be used to add monitoring parameter on existing Nagios. There are various plugins available on the internet which can be used freely to add features to Nagios. Nagios is most popular tool in continuous monitoring.

Bamboo–  Atlassian is one of the companies that must be taken seriously when referring to DevOps. In this field, Bamboo is a tool that gathers compilations, tests and automated versions in one single workflow. Thus, Bamboo creates multi-phase compilation plans; configures triggers to initiate complications after each commit, and assigns agents to essential compilations and deployments.

In the test phase, it allows making automated tests to revert any product exhaustively with each change. Similarly, it allows conducting parallel tests to facilitate and speed up errors detection. Finally, it automates the deployment of projects at every possible environment, offering flow control with specific permissions to each environment.

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.



So, these are some of the most widely used DevOps tools currently. They are being used by many big enterprises and should be known to developers in 2019. However, this list is my point of view and do let me know if I missed any important name and I will surely include it in my next article. Do drop a comment guys if you find this list helpful and I will continue to bring such articles in the future.