Check Point® Software Technologies Ltd.(link is external) announced major advancements to its family of Quantum Force Security Gateways(link is external).
The application of maturity metrics to everything that we do in today's business environment frequently creates the requirement to perform difficult, far-reaching calculations.
It's not necessarily those measurements that span huge sets of complex data that present the most challenging prospects. Often, it's a compilation of those metrics that attempt to analyze the advancement of fuzzier, process-oriented initiatives that can leave one grasping for just the right analysis methods.
Attempting to weigh the current level of DevOps maturity within your organization is precisely one of those daunting propositions that can leave today's business and technology pros searching for meaningful answers.
Sure, there are some well-established metrics(link is external) that can serve as inherent measurements of overall DevOps success, including deployment frequency rates, average lead times, meant time to recovery (MTTR), and of course, any figures resulting from dedicated Application Performance Monitoring (APM).
Yet, perhaps even more valuable than some of these numbers, or of greater import to practitioners for purposes of self-assessment, are metrics that help analyze precisely how ongoing DevOps adoption compares to similar efforts among peers.
At the end of the day, widely touted unicorns can publicize stunning evidence of their agile transformations, driven by DevOps methodologies; yet, for most organizations this is a long-term, iterative process aided greatly by some understanding of how they compare to less revolutionary examples.
After all, getting a feel for where you're ahead of the curve or behind the 8-ball might be just the thing to help DevOps-oriented teams offer evidence of progress, or the need for increased investment, the next time management comes looking for answers.
For instance, related to development(link is external), perhaps your teams are already actively tracking feature request lead times; but is there an agreement between business, dev and ops regarding the performance of critical services (transaction counts, performance, uptime, etc.) necessary to meet pre-defined business goals?
In the deployment arena, you likely have systems in place to note changes in frequency; however, does your organizational structure and tooling support cross-functional teams that put greater emphasis on the processes associated with releasing new capabilities, rather than supporting individual roles?
As far as management is concerned, you're probably employing APM to ensure improved visibility, response, uptime and availability. That said, is your monitoring able to distinguish the most critical and recurrent problems, and how they impact business services – without necessitating lengthy configuration and base-lining?
Industry News
Sauce Labs announced the general availability of iOS 18 testing on its Virtual Device Cloud (VDC).
Infragistics announced the launch of Infragistics Ultimate 25.1, the company's flagship UX and UI product.
CIQ announced the creation of its Open Source Program Office (OSPO).
Check Point® Software Technologies Ltd.(link is external) announced the launch of its next generation Quantum(link is external) Smart-1 Management Appliances, delivering 2X increase in managed gateways and up to 70% higher log rate, with AI-powered security tools designed to meet the demands of hybrid enterprises.
Salesforce and Informatica have entered into an agreement for Salesforce to acquire Informatica.
Red Hat and Google Cloud announced an expanded collaboration to advance AI for enterprise applications by uniting Red Hat’s open source technologies with Google Cloud’s purpose-built infrastructure and Google’s family of open models, Gemma.
Mirantis announced Mirantis k0rdent Enterprise and Mirantis k0rdent Virtualization, unifying infrastructure for AI, containerized, and VM-based workloads through a Kubernetes-native model, streamlining operations for high-performance AI pipelines, modern microservices, and legacy applications alike.
Snyk launched the Snyk AI Trust Platform, an AI-native agentic platform specifically built to secure and govern software development in the AI Era.
Bit Cloud announced the general availability of Hope AI, its new AI-powered development agent that enables professional developers and organizations to build, share, deploy, and maintain complex applications using natural language prompts, specifications and design files.
AI-fueled attacks and hyperconnected IT environments have made threat exposure one of the most urgent cybersecurity challenges facing enterprises today. In response, Check Point® Software Technologies Ltd.(link is external) announced a definitive agreement to acquire Veriti Cybersecurity, the first fully automated, multi-vendor pre-emptive threat exposure and mitigation platform.
LambdaTest announced the launch of its Automation MCP Server, a solution designed to simplify and accelerate the process of triaging test failures.
DefectDojo announced the launch of their next-gen Security Operations Center (SOC) capabilities for DefectDojo Pro, which provides both SOC and AppSec professionals a unified platform for noise reduction and prioritization of SOC alerts and AppSec findings.
Check Point® Software Technologies Ltd.(link is external) has been recognized on Newsweek’s 2025 list of America’s Best Cybersecurity Companies(link is external).
Red Hat announced enhanced features to manage Red Hat Enterprise Linux.