Best DevOps Software for Linux of 2025 - Page 4

Only JVM with pauseless trash collection technology. This ensures fast startup and consistent high-performance without GC pauses or jitter. Zing is optimized for Linux and x86 platforms and can be run on-premises or in cloud. It is suitable for enterprise applications and production workloads, including web-facing apps, human-facing response times, latency-sensitive trading, and payments platforms. One survey respondent, a vice president of Infrastructure Technology and DevOps, stated that they were the only JVM he could trust to not fail him. Another respondent, a CTO said that Azul is the only JVM that can be trusted in a high-stakes environment.

Tanzu Observability by Broadcom is an advanced observability solution designed to provide businesses with deep visibility into their cloud-native applications and infrastructure. The platform aggregates metrics, traces, and logs to deliver real-time insights into application performance and operational health. By leveraging AI and machine learning, Tanzu Observability automatically detects anomalies, accelerates root cause analysis, and offers predictive analytics to optimize system performance. With its scalable architecture, the platform supports large deployments, enabling businesses to manage and improve the performance of their digital ecosystems efficiently.

HyScale transforms agile teams' ability to deploy software to modern IT infrastructures powered with cloud, containers, and Kubernetes. It is open-source and vendor-neutral. Containerized and created apps for a microservice-based platform that minimizes delays in application delivery. A leading UK insurance company needed to migrate monolithic apps from the UK to K8s and set up a self service process in a matter of weeks. Automated CI/CD pipeline for a US-based transport management company. You should be focusing on your app and quickly implement any changes. Continuously deliver microservices via Kubernetes using self-service DevOps. Deliver apps to Kubernetes that run on multi-cloud environments. Streamline your workflow with left-shifted security and gain visibility over container sprawl.

Terragrunt acts as a lightweight wrapper that enhances your ability to maintain dry configurations, facilitates the use of various Terraform modules, and aids in overseeing remote state management. To effectively handle your Terraform state, configure it in a root directory so that it gets inherited by all child modules seamlessly. You can also specify CLI arguments in the Terragrunt configuration to ensure that Terraform commands are executed consistently and repeatably. This approach allows you to execute a single command that applies to all modules simultaneously, rather than running it separately for each one. Additionally, Terragrunt has the capability to retrieve remote Terraform configurations, streamlining your workflow. Ultimately, this means you only need to define the Terraform code for your infrastructure a single time, making management much more efficient and organized. By leveraging Terragrunt, you can significantly reduce duplication and enhance collaboration across your infrastructure projects.

Kubiya is an innovative internal developer platform powered by AI that utilizes conversational technology to optimize DevOps workflows. By seamlessly connecting with existing tools and platforms, it enables developers to engage with their systems through natural language, significantly decreasing the time required for automation and boosting overall productivity. This platform features AI-driven assistants that can efficiently manage routine functions such as overseeing Jira queues, provisioning infrastructure, and applying just-in-time cloud permissions, thereby empowering engineering teams to concentrate on more strategic tasks. With its agentic-native architecture, Kubiya guarantees reliable and secure operations, adhering to rigorous enterprise security standards and compliance with corporate policies. Additionally, the platform integrates effortlessly into communication tools, including Slack and Microsoft Teams, offering a user-friendly conversational interface for task delegation and automation. As a result, Kubiya not only enhances efficiency but also fosters a more collaborative environment for development teams.

With Lens Autopilot, DevOps engineers from Mirantis create CI/CD pipelines tailored to your specific applications, development and approach. Our monitoring and alerting provides real time status of clusters and resources with access to logs for prompt troubleshooting and debugging of errors. Lens Autopilot combats security threats and detects vulnerabilities early with continuous monitoring and alerting which can be integrated with Slack or Microsoft Teams. View all of your logs and key metrics into a unified Grafana Loki dashboard. Combining the powerful capabilities of Lens with Mirantis’ world-class professional services expertise, Lens Autopilot delivers a ZeroOps, fully managed service for organizations that want to improve their application delivery on top of Kubernetes, significantly improving their return on investment. Mirantis is proud and confident to guarantee our technical capability to achieve the following outcomes with Lens Autopilot in 12 months or less.

OpsBridge is built to effortlessly connect with Salesforce applications, offering instant visibility, proactive oversight, and strategic insights that enhance business agility and operational efficiency. This integration empowers organizations to respond swiftly to changes and optimize their operations effectively.

KitOps serves as a robust system for packaging, versioning, and sharing AI/ML projects, leveraging open standards to seamlessly integrate with existing AI/ML, development, and DevOps tools, while also being compatible with your enterprise container registry. It has become the go-to choice for platform engineering teams in the AI/ML domain seeking a secure method for packaging and managing their assets. With KitOps, you can create a comprehensive ModelKit for your AI/ML projects, encapsulating all elements necessary for local reproduction or production deployment. Additionally, the ability to selectively unpack a ModelKit allows team members to optimize their workflow by only accessing the components pertinent to their specific tasks, thereby conserving both time and storage resources. Given that ModelKits are immutable, can be signed, and reside within your established container registry, they provide organizations with an efficient means of tracking, controlling, and auditing their projects, ensuring a streamlined workflow. This innovative approach not only enhances collaborative efforts but also fosters consistency and reliability across AI/ML initiatives.