8 DevOps Tools You Should Use for Opinionated, Cloud Native App Development

The following is a guest blog post written by Taurai Mutimutema.

If you've been following the infrastructure as a service trend (not hype), then by now you know there are more reasons to be in the cloud than not. Even without conceding to it, the best applications out there are being delivered through DevOps tools and processes.

If you're looking to get started on doing things the same way, or already are and just need to ”spy” on what the other team is using, keep reading. This article will share some of the best tools being used in the industry. Efficiently running an opinionated cloud-native app development environment requires the DevOps tools we'll be sharing shortly.

Before delving into the crux of the matter, it seems wise to have the same notions around a few terms: "DevOps," "opinionated" and "cloud native." This information dissemination endeavor will not take for granted the knowledge of any of these terms.

When development of a software product merges with the IT processes that complete a  pipeline, we attain a DevOps situation. Members of a DevOps team collectively take advantage of practices that make it easier to create and manage a product from conception to deployment in a timely manner.

Most of the features in an opinionated environment are prescribed. When it seems easy to create containers that come with (or are prescribed to) resources and specs, the environment does away with you having to buy hardware to add such. The opposite would be having to buy SSDs to add storage capacity. Opinionated comes with such environment variables prescribed and ready for use.

The cloud native way of creating and deploying applications is one in which containerized environments are a staple. This means you'd have applications created and managed by DevOps teams through continuous integration and delivery. The advantages of such configurations make it perfect for applications with high numbers of users along with many changes being effected in order to scale or just repair while users are always online.

Most DevOps teams' performance can be traced back to their tools of choice. Each function on a product pipeline is likely to have various tool options from which to pick and apply. It’s not uncommon to have company policy dictate the tools used when developing software. To attain what could be viewed as a symphony, it’s vital to have DevOps tools for collaboration, development, monitoring, and other tasks to be carried out efficiently.

On the user end of the product's existence, interfaces and tools that facilitate productive feedback also tie in with the objective to make the same product's pipeline efficient. DevOps teams that streamline the feedback from their user base often end up with a more satisfying digital product. Some open-source DevOps tools go on to automatically maintain the near 100 percent uptimes that used to only be possible for tech giants with deep pockets.

Continuous integration and continuous delivery (CI/CD) are the prevailing and infinite themes that DevOps teams carry out to keep a software product relevant. Various stages of the product's pipeline require specialized tools in order to keep the delivery pace optimal.

What you’ll notice is that plenty of the DevOps tools mentioned below are built on open-source resources such as Kubernetes (K8s). By leveraging the freely accessible yet powerful K8s API, clever DevOps tools exhibit both the opinionated and cloud-native properties.

In order to set up the environment and sometimes go as far as automating the upkeep of your applications' infrastructures, DevOps tools such as the ones below are a prerequisite.

Natively run over a wide range of Kubernetes-managed platforms, CloudBees CI automates the configurations and even agent pool scaling. When working across multiple cloud services, CloudBees CI allows for a central point from which to manage controllers when necessary. Effectively, you get access to a CloudBees-unique feature of "controller of controllers". This control spreads over all clusters regardless where they reside. Also of note—CloudBees CI automatically hibernates inactive controllers to optimize resources where they are required.

Built directly on the K8s API, Jenkins X forges together the ease of creating and managing containers along with the omniscient health checks that keep apps running when integrating new features.

Once set up, Jenkins X effectively automates CI/CD without the need for deep understanding of an entire pipeline. Using HELM to deploy your applications inside the Jenkins X DevOps tool makes it easy to create and update configurations of the product and its environment. This cuts the time to deploy significantly.

Google's implementation of the K8s API, Skaffold is a client-side only command-line tool that takes away the cluster management responsibilities from a DevOps team. With Skaffold, you get to build and deploy application versions locally and to remote servers.

The most attractive feature with Skaffold has to be the ability to carry out a full battery of operations with a single command: skaffold dev. This initiates a process for your new code that checks for syntactical correctness and builds, tests, and deploys artifacts created from the new version of code.

As if these steps automated by Skaffold weren’t enough, it goes on to monitor and clean the artifacts. It also uses HELM to manage deployments and the configuration files created and updated with each successive cycle of the CI/CD model. Google also has Tekton, a K8s-native framework that many developers working with Jenkins X have found useful.

Managing how changes roll into deployments, feature flags are a smart way through which DevOps teams can create sandboxes to fully develop and test changes. Let's look at a few such tools.

With CloudBees Feature Management, your DevOps teams get to run variations of the same application with some features only accessible to specific user levels, locations, or even access devices. Since development is almost always underway under the CI/CD work model, a tool that can be used by other members of the pipeline team not critical to the coding phase can help with managing feature flags.

Sales and marketing teams can plug into the pipeline with A/B tests of new features or even content for audiences as they polish their strategies. CloudBees Feature Management comes with an easy-to-learn interface that cuts short the time to create, deploy, and test new features.

Another feature flagging service, Flagger runs on K8s and manages product deployment; it also protects your users from potential flaws. It runs on the concept of showing new versions of an application to different users and querying either Prometheus or other services before alerting actors through release notes in Slack, Docker, or MS Teams.

Flagger is open source, with a support community using it to continuously monitor and control the deployment stage of K8s-based pipelines.

Continuously changing the codebase of your application requires continuous monitoring. Your DevOps team will benefit from keeping a finger on the pulse of the entire pipeline.

Nagios is an open-source and well-supported DevOps monitoring tool that gives insight into the entire product pipeline. It provides access to metrics and actionable data on critical levels of the CI/CD workflow.

Network visibility: Nagios allows real-time data on the active status of a network to be gathered and displayed on dashboards. Through the use of plugins, your team can configure and follow updates that help your network stay healthy from overload.

Application metrics: Keeping an eye on the actual product while users interact with it helps teams to detect and sometimes predict downtimes before they occur. With Nagios, you can keep an eye on applications deployed across multiple platforms for real-time status reports.

Server monitoring: Through an array of over 5,000 additional plugins, you can configure a server-monitoring dashboard that fits your environment and requirements.

Another powerful network monitoring and visualization tool is Netdata. The most appealing part, and a point that separates it from Nagios, is how easy it is to start monitoring. The company claims a two-second installation process that brings over a thousand systems and application status updates.

It features a lightweight database that doesn't suck resources from your infrastructure while allowing you to archive logs and display data on dashboards seamlessly.

In order to complete the CI/CD workflow loop, feedback from the application itself becomes data that developers use to improve it.

The need to take control of an application's release can be satisfied by the use of CloudBees CD service. By sticking to product delivery deadlines and automatically running deployments across desired environments, DevOps teams can keep their applications scaling controllably.

Once deployment completes, CloudBees CD automatically collects feedback data from the application and displays information on dashboards. Several dashboards allow transparent user access screening and more information through optional plugins you can configure to show customized reports. The continuous and instant feedback make it easy for application developers to write code with visible end results clear for all to understand.

By now you may have noticed that most of the tools on this list have some open-source components infused within their builds. The inclusion of code from other developers comes with security vulnerabilities that need constant checks as the application evolves. Licenses too need to be respected when taking components already coded and attaching them with yours.

WhiteSource assists developers in keeping track of such components' potential security risks and makes use of the accompanying licenses to safeguard the final product.

Most useful from the developer and project manager/QA engineer's desk, less time would be spent reading into security-related documentation since WhiteSource arranges threats and alerts your DevOps team before threats bring the entire pipeline to a halt.

Selecting DevOps tools from among the thousands of options currently available boils down to preference and pipeline environment constraints. Where you're working within a hybrid infrastructure model, that filter alone cuts off a lot from that list of available options.

Another point most decision-makers will want to take into consideration is the technical know-how required to run a DevOps tool as part of the entire product workflow. Tools that are strictly command-line based will not be well suited for less technical members of the team. Which is why even when code is being commented on or altered slightly, as with the feature flag scenario, a front-end, no-code, and user-friendly tool such as CloudBees Feature Management would make life easier for the entire DevOps team.

In conclusion, if your team is on its way to starting out on the path to a DevOps model of product delivery of cloud-native applications, it makes sense to have the best tools for each stage of the product pipeline. Knowing what your various team members are comfortable with, along with investing some time to try out new tools, is a commendable starting point. We hope the tools mentioned above make a good foundation for you.

Taurai Mutimutema is a systems analyst with a knack for writing, which was probably sparked by the need to document technical processes during code and implementation sessions. He enjoys learning new technology, and talks about tech even more than he writes.