We're excited to announce the launch of BitDive SaaS - our fully hosted, cloud-based observability platform built for modern Java microservices. This launch marks a major milestone in making deep performance tracing and real-time insight available to everyone, instantly and effortlessly.

Now, instead of setting up infrastructure or maintaining backend components, developers can get started in just minutes. The BitDive agent connects your application to our platform, and you're immediately able to trace distributed requests, profile methods, visualize service dependencies, and capture runtime data - all in a single place.

Yesterday, we announced the MCP Server (Model Context Protocol) integration for BitDive. This new capability allows you to access full runtime context for any method executed in production — including input parameters, return values, exceptions, SQL queries, and downstream calls. MCP turns observability into a daily development tool, not just a monitoring system.

Why do we need production profiling at all?​

Application performance isn't abstract. It's about real issues: errors, timeouts, lost users, and wasted money. But to understand what exactly is slow, it's not enough to know that "CPU is high." You need detail: which service, which method, which request, which parameters.

We're excited to announce the release of BitDive 1.0.1! This release brings significant improvements to configuration management, especially for applications using Spring profiles, and several performance enhancements.

We're excited to announce that BitDive is now featured on GoodFirms, a leading platform for software reviews and recommendations!

BitDive brings code-level observability, distributed tracing, and real-time profiling to modern Java applications, especially in Kubernetes environments.

Explore our profile to learn how BitDive can revolutionize your application monitoring with method-level insights and seamless integration.

Check out our profile at GoodFirms and leave us a review!

Monitoring and optimizing Java workloads in Kubernetes presents unique challenges. From the dynamic nature of microservices to the complexity of distributed systems, traditional tools often fall short. BitDive offers a revolutionary approach to code-level observability and real-time monitoring, purpose-built for Kubernetes environments.

Modern applications are increasingly becoming business-critical. Unstable performance, prolonged downtime, or a lack of visibility into what's happening inside the system can lead to significant financial losses and reputational damage. Meanwhile, traditional logging-based methods of monitoring often fall short: logs may be insufficient, or they get lost in a massive stream of messages.

Microservices architecture offers businesses flexibility, independent development teams, and the ability to scale individual services. However, the more complex and distributed a system is, the more pressing it becomes to have centralized monitoring and a clear view of how services interact.

The Challenge of Debugging Distributed Applications​

Distributed systems have become the backbone of modern software architecture. But with this complexity comes the challenge of tracking down errors and understanding their impact across multiple services. Relying solely on logs or traditional error-tracking tools often leaves developers frustrated, chasing incomplete information.

That's why BitDive introduces a game-changing solution that combines error interception, distributed tracing, correlation IDs, metrics, and alerts—delivering developers a complete observability toolkit for debugging distributed applications with ease and precision.

In today's cloud-native environments, maintaining optimal application performance requires multiple complementary approaches. While these tools share some features, they serve distinct purposes in modern performance management.

Application Performance Management (APM)​

APM's evolution reflects the changing landscape of application architecture. Originally designed for monolithic applications, modern APM tools now handle the complexities of distributed systems and microservices.