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How DevOps Teams can utilize open-source tools

To get the most out of DevOps, approach your open source strategy in two dimensions: horizontal and vertical. Consider this advice on practical tools and approaches. Open-source software development is rapidly becoming an integral part of the DevOps team’s toolkit. Open-source software (OSS) allows businesses to avoid the cost of expensive proprietary software. So that cannot be scaled to the company or can become obsolete over time, especially at the beginning of a journey. Cost savings are a clear benefit, but open-source flexibility is ideal for DevOps in practice.

Today’s software teams are tasked with providing automation across various DevOps workflows. We need to support a broad portfolio of applications and tools while meeting the needs of a wide range of people, including developers, SREs, and QA testers. The nature of open source software is very good at overcoming these challenges, as OSS is much easier (and cheaper) to integrate into pipeline elements than other solutions. As a result, the entire community has revolved around these tools to provide necessary guidance and support for others’ journeys.

Whether or not you need to connect your continuous integration server to configuration management tools. There may already be guidance for that. These synergies have led to the development of many open-source DevOps tools. Many are now widely used (full disclosure: I work for Delphix, which has its open-source project). By working with dozens of DevOps teams from Fortune 500 companies and using OSS tools in-house, we found that the teams needed to work on an open-source strategy in two dimensions. Horizontal and vertical. This is what I mean:

Build horizontal: Focus on automation and speed.

Continuous integration and delivery or deployment (CI / CD) is the Holy Grail of software. Many are looking for it, but few have found it. Open source tools can be an essential first step in the DevOps path to a Dedicated software development team. This is only if the team brings automation and speed to the various stages of the process.

For this reason, experts refer to the DevOps “toolchain” (the product they use) that supports the software “pipeline” (the method of software delivery). It visually represents these elements as a horizontal deployment. Enterprise-wide two-end tools are the key to highly functional and mature DevOps practices. But it’s not as easy as it sounds. Traditionally, it has been expensive and difficult for businesses.

The good news today is that there are even more open source options at each successive step in the software delivery life cycle (SDLC). Suppose you know where to look, from source code management to building artefact storage, release monitoring, to deployment. In that case, there’s an OSS solution for that.

Choose vertical: Add control to every layer of DevOps

After leveraging open source tools to build speed and automation across the enterprise SDLC, what’s next? Although less obvious is the notion that DevOps teams need to think about tool coverage and instrumentation. This is for vertical stacks divided into code, infrastructure, and data layers at the base level. Instantiation of these elements varies at different stages of the SDLC.

However, these layers are somehow present at almost every step in DevOps practice. For example, at the start of the SDLC, the stack might consist of a few lines of code running on a laptop and a small MySQL database with dummy data. However, later in the life cycle, the stack can serve terabytes of data for production applications fully built on the cloud infrastructure as a service. Regardless of the configuration, the team must control and automate all vertical stack elements in the SDLC. If you choose to Hire Full Stack Developer and focus on DevOps, such notions can be materialized.

Again, the good news is that there are plenty of useful OSS tools, from Git (code) to Ansible, Salt (infrastructure), Liquibase, Flyway, and Titan (data). This is important because the team needs to bring speed, control, and automation to all levels of DevOps practice. This does not create a bottleneck that is blocking the entire train. It’s excellent to automatically deploy and configure builds in minutes on a cloud-based test infrastructure. However, suppose it takes a few days to deliver the test data to this cloud environment. In that case, there is a risk of speed illusion, but speed itself is not dangerous. For this reason, all layers of your DevOps process must be addressed from top to bottom for the development process to flow from one

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