Dynatrace cloud automation provides end-to-end orchestration for progressive delivery in the cloud. Learn more about DevOps engineers tools here.
As cloud-native, distributed architectures proliferate, the need for DevOps technologies and DevOps platform engineers has increased as well. DevOps engineer tools can help ease the pressure as environment complexity grows.
DevOps platform engineers are responsible for cloud platform availability and performance, as well as the efficiency of virtual bandwidth, routers, switches, virtual private networks, firewalls, and network management. They are similar to site reliability engineers (SREs) who focus on creating scalable, highly reliable software systems.
Rob Jahn, Dynatrace senior technical partner manager, and Andreas Grabner, Dynatrace DevOps activist discussed the role of platform engineers in the video “Deploy, Test, Evaluate, Repeat: The Power of Webhooks for DevOps Platforms Engineers.”
What does a DevOps platform engineer do?
Belgian engineer Patrick Debois coined the term “DevOps” in 2009 when he needed a Twitter hashtag for DevOpsDays, an agile systems administrators conference in Europe. The goal was to promote collaboration between development and operations teams rather than keeping them siloed.
As an agile methodology DevOps gained popularity with continuous integration (CI) and continuous development/delivery (CD), now practiced by more than 54% of organizations. DevOps teams are responsible for all phases of the software development lifecycle, from code commit to the deployment of products and services.
A DevOps platform engineer is a more recent term. It coincides with the advent of complex, distributed cloud technologies such as microservices and containers. The platform engineer is responsible for designing and maintaining the cloud platform with machine learning and AI automation technologies that support the DevOps goal of efficient, stable, and continuous software development pipelines.
What are DevOps engineer tools and platforms
The choice of DevOps engineer tools and cloud platforms for DevOps engineers are those that meet an organization’s current needs. They have the ability to scale and meet changing business key performance indicators and requirements for continued success in the future.
The following are 12 popular DevOps tools and platforms to consider implementing:
- GitHub. Version control system and source code management with end-to-end DevOps platform and cloud-hosted Git services.
- Jenkins. Open source CI/CD pipeline tool with extensible server automation for distributed builds and scaling.
- Atlassian Jira. Issue tracking system to manage issues, trigger workflows, and track code changes.
- Selenium. Open source automated browser and testing tool.
- Ansible. Open source, cross-platform automation tool for resource provisioning.
- Chef. Infrastructure as code (IaC) configuration management tool.
- Amazon Web Services (AWS). Automated DevOps throughout AWS hybrid-cloud environments.
- Codefresh. CI/CD solution that automates GitOps workflows for cloud-native applications.
- Kubernetes, Container orchestration platform offering orchestration, automation, security, governance, and other capabilities.
- Docker. Open source software containerization platform.
- Puppet. Configuration management.
- Microsoft Azure. DevOps services that offer agile tools to simplify collaboration and work item tracking.
Why is adding automation to tools and platforms important?
Automation is necessary for successful DevOps practices. Automated tools not only ensure consistency throughout workflows and streamline repetitive processes,but also support implementation of fast, efficient CI/CD pipelines that scale without manual intervention.
Automation added to DevOps platforms also supports automated workflows in addition to providing seamless, automated operability for consistent results in public, private, or hybrid cloud environments. When feedback loops between operations and development teams occur without manual intervention, iterative updates deploy more quickly.
Three primary steps to automate in the operations phase of a DevOps delivery pipeline are the following:
- Deploy. Automate the release of developed products and services with approved changes to be accessed by end users.
- Test. Apply automated testing at each stage of the software development lifecyle (SDLC) to ensure quality and product-readiness, even after a product or service release. Post-deployment testing can reveal previously undetected problems that negatively affect end users.
- Evaluate. Monitor the project to gain valuable insights on user interactions, user response, and success of the project. Repeat the evaluation process after deploying and testing each new update or fix.
How cloud automation can help
Organizations often adopt advanced architecture and move to progressive delivery in the cloud. But they struggle to keep up with the underlying tooling and processes. Manual processes are still in place, with DevOps and SRE teams spending most of their time building automation and trying to connect all legacy tools.
Cloud automation helps DevOps platform engineers and SRE teams develop better-quality software faster by orchestrating observability, automation, and intelligence in a unified platform. Cloud automation provides an easy way for an organization to save time and resources by integrating all their DevOps tools, from chaos testing to collaboration and ticketing.
Dynatrace data-driven delivery automation uses cloud automation for end-to-end orchestration. Dynatrace orchestrates the entire multistage delivery process, so your organization can easily plug in individual point tools, rather than build integrations from disparate, individual tools.
To see this process in action with a live demo of a cloud deployment pipeline using Jira, GitLab, and Github, check out our on-demand observability clinic: Deploy, Test, Evaluate, Repeat: The Power of Webhooks for DevOps Platforms Engineers.”
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