Digma Preemptive Observability - Preempt performance and scaling issues in pre-production

Congrats team digma, awesome launch!

WHAT IS DIGMA Digma's Preemptive Observability 👀 brings an innovative approach for using observability data to preempt issues before they manifest, instead of relying on alerts to fix them after the fact 🤦‍♂️. OBSERVABILITY IN THE AGE OF GENAI 🤖 AI code generation is revolutionizing software development, enabling teams to build faster than ever before. But with speed comes risk—without visibility into potential flaws, AI-generated code can introduce performance issues, scalability bottlenecks, and security vulnerabilities that only surface in production. Dealing with a continuous stream of production incidents drags down the team's velocity and creates constant friction for end users. PREEMPT VS POST MORTEM 🧟 Teams that aim to stop issues early and before they reach production, cannot rely on a postmortem approach using APMs. These tools are built to alert the team to issues and facilitate investigation once the problem already occurred. Digma switches to a preemptive approach. It analyzes the same data as APMs and identifies specific code issues using patterns, nipping them in the bud while still in pre-production. To close the loop, Digma provides AI fix suggestions. KEY FEATURES → Continuously identify code performance, scaling issues, query problems, and other issue types 🐞 → Cut resolution time by automatically root cause analyzing each issue as well as providing AI-driven fix suggestions ⚡️ → Prevent breaking changes by highlighting the affected areas and impacted components for each code change and Pull Request → Scaling up your application by identifying which areas of your codebase will scale seamlessly and which may create bottlenecks ⚖️ → Prioritizing technical debt 💰 by assessing existing issues i impact and criticality → Using OTEL-based observability with all supported programming languages and platforms. ☕️ → IDE and code integration: See issues, insights, and analytics within the code itself as well as metrics and traces 🔭 THE PREEMPTIVE OBSERVABILITY ANALYSIS (POA) ENGINE The Digma Preemptive Observability Analysis (POA) engine introduces an advanced approach to observability by proactively identifying potential issues before they materialize in production. It achieves this by analyzing observability tracing data, even when data volumes are low. Leveraging pattern matching and anomaly detection techniques, Digma’s algorithm extrapolates expected application performance metrics, enabling it to detect deviations or potential problems that have not yet impacted the application. In analyzing the tracing data, Digma pinpoints the issue to the specific responsible code and commits. We are super excited to bring Digma to more teams and see the kind of impact it makes on your development process. 🙏 Roni & Nir Digma co-founders https://digma.ai Try our live sandbox: https://sandbox.ui.prod.digma.sy...

How is Digma different from other observability tools?

Looks great, team. Regarding production, I’m curious about any potential performance impacts and resource consumption. Could you elaborate on that?

Do I need to make code changes for Digma to work?

How does Digma alert teams to issues in pre-production?

Congrats on the launch team @Digma Preemptive Observability

Can Digma help prepare my application for sudden scaling?

This sounds like a smart way to catch issues early! How does it integrate with existing workflows?

Looks super interesting! What's the pricing model for a single developer vs. team?