Operant AI announced the launch of MCP Gateway, an expansion of its flagship AI Gatekeeper™ platform, that delivers comprehensive security for Model Context Protocol (MCP) applications.
As software development teams grow, so does the number of headaches they have to deal with — or "the curse of growth" as some like to refer to it. One such headache is the pressure to deliver new products and features consistently.
Many teams respond to this pressure by adopting a DevOps culture to ship products and features more speedily while preserving business value.
But "adopting a DevOps culture" means different things to different teams. Running a docker run command to automate application deployment might suffice for some. However, one command might not be enough for others with more extensive product portfolios. For these, automating multiple tasks within the DevOps process might be necessary to boost speed, precision, and consistency while reducing human error.
The latter, for many organizations, boosts the likelihood of meeting business goals with higher operational consistency and lower potential for human error. But the journey begins by understanding a team's DevOps flow and identifying precisely what tasks deliver the best return on engineers' time when automated. The rest of this blog will help DevOps team managers by outlining what jobs can — and should be automated.
Continuous Integration/Continuous Delivery
Proponents of agile methodology see CI/CD as the best practice for DevOps teams. By automating integration and delivery, software development teams can seamlessly optimize code quality and software security in the background while committing their focus to business objectives.
This automation accelerates the speed to market through quicker, more efficient shipping of software products.
Automatable processes that fall within the CI/CD umbrella include:
■ Builds
■ Code commits
■ Deployment of packaged applications in production/testing environments
Infrastructure management
DevOps teams can test applications in a simulated production environment much earlier in the software development lifecycle (SDLC) by automating infrastructure. This is especially useful as configuration and maintenance of infrastructures such as networks and servers is time-consuming. Automating infrastructure exchanges the burden of manual configurations with the gift of multiple test environment provisioning — so that developers can resolve common deployment issues early in the SDLC.
Provisioning
Automated provisioning facilitates the provision of computer resources on-demand and without human intervention. By automating provisioning, businesses can accelerate product delivery with a highly scalable, flexible architecture and dynamic resource allocation.
Application Deployment
According to Google's DevOps Research and Assessment Program (DORA), deployment automation is instrumental in accelerating software delivery and improving overall organizational performance.
With deployment automation, engineers can minimize the risk of production deployments by seamlessly deploying software to production and test environments. Automation also expedites the feedback loop, enabling teams to implement faster tests and updates.
Software testing
Test automation reduces the dependence on human intervention during testing. Test scripts, automation frameworks, and tools help engineers check product functionality more efficiently. Test automation can be applied to a range of testing tasks, including:
■ Unit testing
■ UI/UX testing
■ Smoke testing
Log management
Applications rely on logs for fault identification, and each application can generate a significant number of logs. The process of error identification and resolution can be eased with automation by using log management tools for aggregating logs.
Monitoring
As new features are added, so is an added layer of complexity for monitoring the performance of applications. By automating monitoring, DevOps teams can identify and resolve any declines in the customer experience more efficiently.
Final Word
Against an industry background of engineer scarcity, DevOps automation reduces the number of human engineers required to perform critical tasks. Introducing automation into an organization's DevOps culture accelerates multiple processes while facilitating seamless scaling with more efficient workflows. DevOps team managers should choose tools with high automation capabilities to utilize their engineering resources more efficiently and see results faster.
Industry News
Oracle has expanded its collaboration with NVIDIA to help customers streamline the development and deployment of production-ready AI, develop and run next-generation reasoning models and AI agents, and access the computing resources needed to further accelerate AI innovation.
Datadog launched its Internal Developer Portal (IDP) built on live observability data.
Azul and Chainguard announced a strategic partnership that will unite Azul’s commercial support and curated OpenJDK distributions with Chainguard’s Linux distro, software factory and container images.
SmartBear launched Reflect Mobile featuring HaloAI, expanding its no-code, GenAI-powered test automation platform to include native mobile apps.
ArmorCode announced the launch of AI Code Insights.
Codiac announced the release of Codiac 2.5, a major update to its unified automation platform for container orchestration and Kubernetes management.
Harness Internal Developer Portal (IDP) is releasing major upgrades and new features built to address challenges developers face daily, ultimately giving them more time back for innovation.
Azul announced an enhancement to Azul Intelligence Cloud, a breakthrough capability in Azul Vulnerability Detection that brings precision to detection of Java application security vulnerabilities.
ZEST Security announced its strategic integration with Upwind, giving DevOps and Security teams real-time, runtime powered cloud visibility combined with intelligent, Agentic AI-driven remediation.
Google announced an upgraded preview of Gemini 2.5 Pro, its most intelligent model yet.
iTmethods and Coder have partnered to bring enterprises a new way to deploy secure, high-performance and AI-ready Cloud Development Environments (CDEs).
Gearset announced the expansion of its new Observability functionality to include Flow and Apex error monitoring.
Check Point® Software Technologies Ltd. announced that U.S. News & World Report has named the company among its 2025-2026 list of Best Companies to Work For.
Postman announced new capabilities that make it dramatically easier to design, test, deploy, and monitor AI agents and the APIs they rely on.