Check Point® Software Technologies Ltd. announced it has been named as a Recommended vendor in the NSS Labs 2025 Enterprise Firewall Comparative Report, with the highest security effectiveness score.
Improving end-user customer experience is one of the key objectives of an application performance management solution in a production environment. By leveraging the application performance data earlier in the development cycle, DevOps teams can ensure readiness for exceptional customer experience before deploying any application in production. Finally, harnessing the business data in application transactions and logs and correlating them with operational data can provide actionable business insights.

In this blog, I will discuss five steps to DevOps success leveraging an application performance management solution in production. I'll also discuss how application performance analytics earlier in the development lifecycle will help foster BizDevOps success.
1. Monitor and manage performance with the business in mind
In order to minimize the application downtime and expedite remediation of application performance issues, you will need to understand business impact of different transactions and their dependencies on various application components and underlying infrastructure. You need to be looking at every aspect of a business transaction – starting from the user experience, the application performance, how the application interacts with the infrastructure, and then finally what is the business impact and how is the business performing.
2. Don't just manage production apps – Ensure readiness in pre-production
It has become commonplace that the goal of any mobile application is to give exceptional experience to their end-customer so they can get a five-star rating from iTunes stores or Google Play. Any web application has similar goals for earning their end-user loyalty. In order to achieve these challenging goals in production, you will need to ensure that your applications are tested and ready for desirable performance in pre-production before they are deployed in production.
It is helpful if you can use the same application performance management tool that you use in your production environment for monitoring tests in a pre-production environment under a production like environment. An APM solution can let you set policies that can trigger automated actions to report issues or simply to notify of successful/unsuccessful test runs during pre-production.
Having deep application transaction traces, detailed snapshots of applications, and underlying infrastructure is also very important to understand the root cause of any performance issue so that developers can fix them before it surfaces in production.
3. When stuff happens (and it will), collaborate effectively with Dev, Ops and Biz
In addition to ensuring production readiness before deployment and having a complete end-to-end visibility into the production environment, it is very important to have processes and tools that foster collaboration between development, operations, and business teams. It helps to get everyone on the same page by looking at the same Business Transaction data, focus on metrics that translate to the business value the application delivers and dive in deeper when appropriate.
4. Change is most often the cause of poor performance, so understand changes to improve performance
Once the application is deployed in production, it is critical to watch for any changes in the environment since the majority of IT outages are caused by improperly implemented changes. So, in order to minimize the very costly application downtime, it is important to understand the performance impact of every change – software, server and database upgrades, infrastructure changes.
You should also compare your application before and after a new code release, code sprints and even bug fixes, and assess the impact the new code had on application performance in both pre-production and production environment.
5. Unlock actionable business insights with Application Analytics
Harnessing the business data in transactions and logs and correlating them with operation data can help you unlock actionable business insights. For example, understanding which users had trouble checking out of your e-commerce application during an outage and what products were in their cart can provide that data to your marketing team so that they can execute on a win back campaign.
Similarly, in case there are multiple business transactions having performance issues, you can prioritize the resolution based on the revenue impact of transactions.
Industry News
Buoyant announced upcoming support for Model Context Protocol (MCP) in Linkerd to extend its core service mesh capabilities to this new type of agentic AI traffic.
Dataminr announced the launch of the Dataminr Developer Portal and an enhanced Software Development Kit (SDK).
Google Cloud announced new capabilities for Vertex AI Agent Builder, focused on solving the developer challenge of moving AI agents from prototype to a scalable, secure production environment.
Prismatic announced the availability of its MCP flow server for production-ready AI integrations.
Aptori announced the general availability of Code-Q (Code Quick Fix), a new agent in its AI-powered security platform that automatically generates, validates and applies code-level remediations for confirmed vulnerabilities.
Perforce Software announced the availability of Long-Term Support (LTS) for Spring Boot and Spring Framework.
Kong announced the general availability of Insomnia 12, the open source API development platform that unifies designing, mocking, debugging, and testing APIs.
Testlio announced an expanded, end-to-end AI testing solution, the latest addition to its managed service portfolio.
Incredibuild announced the acquisition of Kypso, a startup building AI agents for engineering teams.
Sauce Labs announced Sauce AI for Insights, a suite of AI-powered data and analytics capabilities that helps engineering teams analyze, understand, and act on real-time test execution and runtime data to deliver quality releases at speed - while offering enterprise-grade rigorous security and compliance controls.
Tray.ai announced Agent Gateway, a new capability in the Tray AI Orchestration platform.
Qovery announced the release of its AI DevOps Copilot - an AI agent that delivers answers, executes complex operations, and anticipates what’s next.
Check Point® Software Technologies Ltd. announced it is working with NVIDIA to deliver an integrated security solution built for AI factories.
Hoop.dev announced a seed investment led by Venture Guides and backed by Y Combinator. Founder and CEO Andrios Robert and his team of uncompromising engineers reimagined the access paradigm and ignited a global shift toward faster, safer application delivery.




