Best Debugging Tools for Startups

The AI-Powered Python and JavaScript Generator/Debugger/Tutor. Become a pro-coder in seconds. Generate pro-level code in an instant. Type what you need, run the program, and boom! The Whizzy AI model will compute your request and generate your code in an editable code window, so you can touch it up and personalize it however you need. Don't hassle with clunky and slow IDE's, the integrated CodeEngine will run your Python code and generate outputs, and plots, seamlessly. The ScriptRepo allows you to save your favorite creations with ease. We'll keep them secure so your can come back to them anytime. Limited availability. Request access now and secure your own personalized AI-Powered Python Code generation tool.

Log management. Upgraded. With Honeycomb. Honeycomb is built for modern dev teams to better understand application performance, debug & improve log management. With rapid query, find unknown unknowns across system logs, metrics & traces with interactive charts for the deepest view against raw, high cardinality data. Configure Service Level Objective (SLOs) on what users care about so you cut-down noisy alerts and prioritize the work. Reduce on-call toil, ship code faster and keep customers happy. Pinpoint the cause. Optimize your code. See your prod in hi-res. Our SLOs tell you when your customers are having a bad experience so that you can immediately debug why those issues are happening, all within the same interface. Use our Query Builder to easily slice and dice your data to visualize behavioral patterns for individual users and services (grouped by any dimensions).

Defang is a developer-centric platform that simplifies the process of developing, deploying, and debugging cloud applications. By leveraging AI-assisted tooling, Defang enables developers to swiftly transition from an idea to a deployed application on their preferred cloud provider. The platform supports multiple programming languages, including Go, JavaScript, and Python, allowing developers to start with sample projects or generate project outlines using natural language prompts. With a single command, Defang builds and deploys applications, handling configurations for computing, storage, load balancing, networking, logging, and security. The Defang Command Line Interface (CLI) facilitates interactions with the platform, offering installation options via shell scripts, Homebrew, Winget, Nix, or direct download. Developers can define services using compose.yaml files, which Defang utilizes to deploy applications to the cloud.

Latta AI is an innovative platform designed to streamline the software development process by automating the detection and resolution of bugs. By recording user sessions and applying AI-driven fixes, Latta AI enables developers, project managers, and testers to focus more on feature development, thereby boosting productivity and accelerating release cycles. The platform integrates seamlessly with popular version control systems like GitHub and GitLab and maintains strict security protocols to ensure code privacy and protection. Additionally, Latta AI offers a plugin for JetBrains IDEs, allowing developers to access its bug-fixing tools directly within their development environment. This integration facilitates quick identification and resolution of issues without the need to leave the IDE. Overall, Latta AI aims to reduce the time developers spend on debugging by up to 40%, enhancing efficiency and allowing teams to focus on innovation.

SwapCode AI is a special helper that makes it easy to change one kind of code into another. Imagine if you were playing with blocks, and you wanted to turn a square block into a round one—it does that for code! It helps developers and teams make their code work in new ways without breaking anything. It works with lots of different types of code, like the ones used to make websites, games, and apps. For example, if you have a puzzle piece that fits in a Java puzzle but needs to fit in a Python puzzle, SwapCode AI knows how to reshape it perfectly! It even makes sure the new piece is easy to read and use. SwapCode AI is super smart and fits right into your tools, so you can use it while you’re working without any extra steps. It helps teams work together, even if they’re using different tools or languages.

Developer-centric tool to monitor and improve AI features powered by LLMs and other foundation models. Our simple SDK gives you an intuitive and actionable view of how your generative AI applications are performing in production. Integrate LLM management into your existing codebase and developer workflow. Use our fine-grained access controls and audit logs to maintain full control over your data. Derive actionable insights on how to improve LLM user interactions. Not only are these teams best-equipped to integrate these new capabilities into existing software products, but their proclivity to deploy, iterate, and improve will also be ever more pertinent going forward. As software becomes increasingly malleable, we believe engineering teams will be the driving force behind turning that malleability into delightful and hyper-personalized user experiences. Developers will be at the center of the generative AI revolution.

Unexpected results happen all the time. With full visibility into the entire chain sequence of calls, you can spot the source of errors and surprises in real time with surgical precision. Software engineering relies on unit testing to build performant, production-ready applications. LangSmith provides that same functionality for LLM applications. Spin up test datasets, run your applications over them, and inspect results without having to leave LangSmith. LangSmith enables mission-critical observability with only a few lines of code. LangSmith is designed to help developers harness the power–and wrangle the complexity–of LLMs. We’re not only building tools. We’re establishing best practices you can rely on. Build and deploy LLM applications with confidence. Application-level usage stats. Feedback collection. Filter traces, cost and performance measurement. Dataset curation, compare chain performance, AI-assisted evaluation, and embrace best practices.

Using runtime information, Digma integrates into your IDE to continuously highlight issues, regressions, and problems, as you code. Immediately see how any function scales in CI or production and spot issues while still in development. Accelerate code changes and avoid endless regressions, by analyzing how the code performs, Digma provides critical analytics on usage, errors, and performance baselines to make sense of forgotten code and ownerless libraries. Immediately understand what’s causing bottlenecks and slowdowns in your code. With valuable data such as code execution times, scaling limitations, and N+1 query issues – you can quickly fix it. Pull Request feedback and code review annotation get way easier when your team integrates Digma into your GitOps cycle. Digma lets you understand it and start working on it fearlessly – no matter how large or complex.

Optimize ML models by capturing training metrics in real-time and sending alerts when anomalies are detected. Automatically stop training processes when the desired accuracy is achieved to reduce the time and cost of training ML models. Automatically profile and monitor system resource utilization and send alerts when resource bottlenecks are identified to continuously improve resource utilization. Amazon SageMaker Debugger can reduce troubleshooting during training from days to minutes by automatically detecting and alerting you to remediate common training errors such as gradient values becoming too large or too small. Alerts can be viewed in Amazon SageMaker Studio or configured through Amazon CloudWatch. Additionally, the SageMaker Debugger SDK enables you to automatically detect new classes of model-specific errors such as data sampling, hyperparameter values, and out-of-bound values.