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By Eran Kinsbruner
In the rapidly evolving landscape of software development, the integration of generative AI has become a game-changer for organizations striving to deliver high-quality software at scale. Among its many transformative applications, autonomous debugging stands out as a critical advancement, offering the potential to revolutionize the way development teams tackle errors and maintain operational efficiency.
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By Barark Ben Ari
JIT Access, sometimes referred to as just-in-time provisioning or just-in-time privileged access management (JIT PAM), is a security strategy that grants users access privileges for limited time periods. Access is granted on an “as-needed” basis. For example, if a developer requires access to a specific platform for a week or as part of an on-call access to production duty, a JIT Access system can provide that access and automatically revoke it after the time period ends.
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By Ilan Peleg
The software world is changing rapidly due to advancements in GenAI. These technologies are disrupting traditional processes and driving automation across every part of the SDLC. The market for AI code tools is estimated to reach $30 billion by 2032. It started with code generation, then moved to testing, QA, automatic pull requests, and beyond.
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By Tal Yitzhak
According to a recent study, failing tests alone cost the enterprise software market an astonishing $61 billion annually. This figure mirrors the vast number of resources devoted to rectifying software failures, translating into about 620 million developer hours lost each year. On average, engineers spend 13 hours to resolve a single software failure, a statistic that paints a stark picture of the current state of debugging efficiency.
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By Eran Kinsbruner
Throughout the first half of 2024, Lightrun has focused on developing a range of solutions and improvements aimed at enhancing developer observability and live debugging. These advancements help organizations significantly reduce their MTTR for complex issues while boosting developer productivity. Read more below the main new features as well as the key product enhancements that were released in H1 of 2024!
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By Tal Yitzhak
Over the last few decades, software systems have grown complex due to the emergence of cloud-native architectures and multi-cloud environments. On the one hand, this makes it difficult to detect issues faster in the deployed application. It also requires intricate coordination between development, DevOps, and SRE teams, as they are also expected to speed up the whole software delivery process.
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By Eran Kinsbruner
In software development, dynamic instrumentation is a powerful linchpin between the development and debugging workflows. With software complexity reaching unprecedented levels, it is also a key enabler in boosting developer productivity in the pursuit of building performant and error-free software. Let’s explore the concept of dynamic instrumentation and understand how it boosts software development processes with unparalleled insights into the source code.
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By Tal Yitzhak
In the dynamic landscape of modern application development, managing telemetry across diverse environments and technologies can be a daunting task. Adding to that challenge is the multiple groups that are involved in the software development life cycle within an organization.
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By Eran Kinsbruner
Software debugging has undergone many transcendental shifts. These shifts are as fascinating as the transition from the biological origins of the term ‘debugging’ to its computer science incarnation. The moth that caused the first computer bug has led to a metamorphosis of the debugging scope to cover a much broader role in software development over the years. Live debugging is the latest manifestation of this evolution.
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By Tal Yitzhak
According to PYPL (PopularitY of Programming Language), Python has been the most popular programming language worldwide from 2018 to the present. Remarkably, Python’s popularity has grown by 2.5% over the last five years. In contrast, Java, the previously most popular language, has seen a 4.8% decrease in its popularity. While Java is typically faster than Python, Python is easier to read with its simpler syntax.
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By Lightrun
In this insightful webinar hosted by Lightrun and moderated by Eran Kinsbruner, global head of product marketing and best-selling author in the software development space we delved into the latest developments in software development and performance, focusing on the recent Google DORA report. In the first segment of the webinar, Nathen Harvey and Amanda Lewis from Google Cloud's DORA team provided a comprehensive overview of the latest report's findings, highlighting the emerging emphasis on Performance and Reliability in the industry.
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By Lightrun
This video outlines the Lightrun management server. It explains the various features and components of the server including user management and administration, platform security features, troubleshooting actions monitoring and management, log management and much more.
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By Lightrun
In this tutorial, we explore how to create and use tagging and custom sources as part of your troubleshooting strategy across complex remote and distributed workload applications.
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By Lightrun
In this demo we show how easy and fast it is to run through an entire source code project scan and identify the low quality static logs that are candidates to be omitted and replaced with dynamic logs. Lightrun LogOptimizer empowers developers to take action and be accountable for their logging costs.
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By Lightrun
In this demo video we show how developers can shift left observability and debug in runtime an EKS cluster from their IDE. The demo shows how developers can debug a remote Java application that is deployed on 3 different EKS pods (Dev, Staging, Production) directly from their IntelliJ IDE in runtime and add logs and snapshots.
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By Lightrun
In this demo we show case how using Chronosphere platform and Lightrun dynamic observability at runtime, developers can easily troubleshoot and resolve complex issues across cloud native applications.
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By Lightrun
In this demo we show how developers can easily create a Metric action directly from the IntelliJ IDE for a distributed Java application and pipe the Metric data to IBM's Instana platform for further analysis and actionable consumption.
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By Lightrun
In this video we demonstrate how to troubleshoot an AWS Lambda servereless application with Lightrun by placing a virtual breakpoint (snapshot) and observing its output within the Lightrun IDE plugin.
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By Lightrun
This demo shows how to use Lightrun Metrics and measure the performance of 20 instances of a java running application. Using Lightrun dynamic observability and the key Metrics below developers can measure their app performance in runtime.
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By Lightrun
As financial apps continuously evolve towards more distributed architectures, highlight competitive landscape, and more digital users across so many different platforms, the cost of failure as well as the ability to quickly and efficiently troubleshoot end-user issues is becoming key for these organizations success. In addition, many of these financial organizations are still required to support a mix of legacy and cloud-native applications.
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By Lightrun
This datasheet details various specifications and requirements for installing and running Lightrun in production.
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By Lightrun
As experienced cybersecurity engineers with strong cloud and SaaS backgrounds, the Lightrun team fully recognizes the importance of embedding security as part of the product design and delivery. This document provides a high-level overview of Lightrun's security model, architecture and primary controls. While there are no 100% bulletproof solutions, the Lightrun platform is designed with a significant investment in security from the ground up, as outlined in this document.
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Lightrun is a Developer Native Observability Platform, enabling developers to securely add logs, performance metrics and traces to production and staging in real time, on demand.
Insert logs and metrics in real time even while the service is running. Debug monolith microservices, Kubernetes, Docker Swarm, ECS, Big Data workers, serverless, and more.
Developer-Native Observability Platform:
- Increase developer productivity: Spend less time debugging and more time coding. No more restarting, redeploying and reproducing when debugging.
- Enhance site reliability: Reduce MTTR and increase customer satisfaction. Identify and resolve bugs faster with less downtime.
- Resolve bugs faster: Add logs, snapshots, and metrics dynamically to your live app. Skip the traditional CI/CD pipelines.
- Debug in production, staging, anywhere: Lightrun does not interrupt running apps. Debug in any environment: production, staging, testing, dev, etc.
Save your valuable debugging time and keep your service reliable.