Best Debugging Tools for Amazon Web Services (AWS)

TrustInSoft Analyzer is a C and C++ source code analyzer powered by formal methods, mathematical & logical reasonings that allow for exhaustive analysis of source code. This analysis can be run without false positives or false negatives, so that every real bug in the code is found. Developers receive several benefits: a user-friendly graphical interface that directs developers to the root cause of bugs, and instant utility to expand the coverage of their existing tests. Unlike traditional source code analysis tools, TrustInSoft’s solution is not only the most comprehensive approach on the market but is also progressive, instantly deployable by developers, even if they lack experience with formal methods, from exhaustive analysis up to a functional proof that the software developed meets specifications. Companies who use TrustInSoft Analyzer reduce their verification costs by 4, efforts in bug detection by 40, and obtain an irrefutable proof that their software is safe and secure.

Bugsnag monitors application stability so you can make data-driven decisions on whether you should be building new features, or fixing bugs. ‍ We are a full stack stability monitoring solution with best-in-class functionality for mobile applications. Rich, end-to-end diagnostics to help you reproduce every error. A simple and thoughtful user experience for all your apps in one dashboard. The definitive metric for app health — the common language for product and engineering teams. Not all bugs are worth fixing. Focus on the ones that matter to your business. Extensible libraries with opinionated defaults and countless customization options. Subject matter experts who care deeply about error reduction and the health of your apps.

Empower your Android teams with virtual devices that truly scale. With all testing frameworks based on ADB, Appium, Espresso, Robotium, etc. Works with popular continuous integration solutions CircleCI, Bitrise, Terraform, etc. No nested virtualization to speed up your tests and operations with or without a dedicated GPU. Instant access to unlimited virtual devices that can be run simultaneously for test sharding or parallel testing. Available from Android 4.4 to latest Android versions, in all screen sizes and on a large variety of platforms including our own but also AWS, Google, Azure and Alibaba. Control over your infrastructure with no maintenance needs. Best-in-class security and reliability for enterprise needs. Infinite scalability with cloud providers datacenters. Dedicated GPUs are available on selected devices. Emulate 3000+ virtual Android device configurations (Android versions, screen size, hardware capacities, etc.)

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.

Shoreline is the Cloud Reliability platform — the only platform that lets DevOps engineers build automations in an afternoon, and fix issues forever. Shoreline reduces on-call complexity by running across clouds, Kubernetes clusters, and VMs allowing operators to manage their entire fleet as if it were a single box. Debugging and repairing issues is easy with advanced tooling for your best SREs, automated runbooks for the broader team, and a platform that makes building automations 30X faster. Shoreline does the heavy lifting, setting up monitors and building repair scripts, so that customers only need to configure them for their environment. Shoreline’s modern “Operations at the Edge” architecture runs efficient agents in the background of all monitored hosts. Agents run as a DaemonSet on Kubernetes or an installed package on VMs (apt, yum). The Shoreline backend is hosted by Shoreline in AWS, or deployed in your AWS virtual private cloud.

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.

Luciq is an AI-powered mobile observability platform designed for app developers and enterprises to monitor, diagnose, and improve mobile applications seamlessly. The solution brings together bug reporting, crash analytics, session replay, and performance monitoring in one unified SDK that supports Android, iOS, web and hybrid apps. It enables users to capture detailed device logs, network traces, annotated screenshots, videos and user feedback, while automatically correlating events and errors using machine learning to prioritize issues by impact. Developers gain visibility into user sessions where things went wrong, reproduce defects through replay, and resolve issues faster using integrations with JIRA, Slack, Zapier, Zendesk and other tools. With Luciq’s “Agentic Mobile Observability” approach, the system surface the most critical problems, suggests root-causes and even recommends remediations, helping teams increase velocity, improve app stability and enhance user experience.