Parasoft has made another step in strategically integrating AI and ML quality enhancements where development teams need them most, such as using natural language for troubleshooting or checking code in real time.
In today's high-stakes race to deliver innovative products without disruptions, the importance of feature management and experimentation has never been more clear. But what strategies are driving success, and which tools are truly moving the needle?
To shed light on these questions, Harness partnered with LeadDev to release The State of Feature Management & Experimentation 2024, an in-depth report revealing the practices behind the top-performing software teams. The report, based on insights from 500 engineering leaders, uncovers one critical element that separates the best from the rest: effective release monitoring.
The Power of Statistical Insight
The survey highlights a striking statistic: 82% of teams excelling in feature management and experimentation can measure system performance and user behavior at the feature level. Meanwhile, only 16% of their peers succeed without this critical capability. This stark contrast underscores a powerful truth — release monitoring is not just helpful; it's essential for identifying issues before they impact users.
The Risks of Flying Blind
Without a robust feature management solution that includes release monitoring, teams risk deploying features without fully understanding their real-world impact. This lack of visibility can allow bugs, performance issues, and broken user experiences to slip through, especially during gradual rollouts. Often, these problems don't surface immediately but cause severe disruptions when features go live. Many leaders mistakenly believe traditional application monitoring tools (APMs) provide enough oversight. However, APMs focus on overall system health and lack the precision to track individual feature impacts — making them inadequate for progressive delivery. The only way to ensure smooth rollouts is with a feature management platform that integrates real-time release monitoring.
The High Cost of DIY Solutions
For companies prioritizing innovation, relying on a DIY feature flagging system often leads to inefficiencies and missed opportunities. Best practices in feature management and experimentation require trusted, purpose-built tools, with release monitoring at their core. A piecemeal approach can't keep up with the speed and complexity of modern software delivery.
Choosing the Right Tools for the Job
When evaluating feature management platforms, it's crucial to look beyond basic functionality. Most platforms demand extensive setup and manual effort to link feature flags with performance data. Only top-tier solutions offer out-of-the-box release monitoring that tracks critical metrics from the moment a flag is created.
Why Monitoring Drives Success
As the industry evolves, release monitoring will become the bedrock of safe, efficient software delivery. Teams that embrace this capability will ensure every feature rollout is a step forward, not a gamble.
Industry News
MuleSoft announced the general availability of full lifecycle AsyncAPI support, enabling organizations to power AI agents with real-time data through seamless integration with event-driven architectures (EDAs).
Numecent announced they have expanded their Microsoft collaboration with the launch of Cloudpager's new integration to App attach in Azure Virtual Desktop.
Progress announced the completion of the acquisition of ShareFile, a business unit of Cloud Software Group, providing a SaaS-native, AI-powered, document-centric collaboration platform, focusing on industry segments including business and professional services, financial services, industrial and healthcare.
Incredibuild announced the acquisition of Garden, a provider of DevOps pipeline acceleration solutions.
The Open Source Security Foundation (OpenSSF) announced an expansion of its free course “Developing Secure Software” (LFD121).
Redgate announced that its core solutions are listed in Amazon Web Services (AWS) Marketplace.
LambdaTest introduced a suite of new features to its AI-powered Test Manager, designed to simplify and enhance the test management experience for software development and QA teams.
StackHawk launched Oversight to provide security teams with a birds-eye view of their API security program.
DataStax announced the enhancement of its GitHub Copilot extension with its AI Platform-as-a-Service (AI PaaS) solution.
Opsera partnered with Databricks to empower software and DevOps engineers to deliver software faster, safer and smarter through AI/ML model deployments and schema rollback capabilities.
GitHub announced the next evolution of its Copilot-powered developer platform.
Crowdbotics released an extension for GitHub Copilot, available now through the GitHub and Azure Marketplaces.
Copado has integrated Copado AI into its Community to streamline support and accelerate issues resolution.
Mend.io and HeroDevs have forged a new partnership allowing Mend.io to offer HeroDevs support for deprecated packages.