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!

Efficient monitoring tools are crucial for maintaining the performance, security, and reliability of your infrastructure. This comprehensive guide covers the top 10 best monitoring tools for IT infrastructure, offering insights into their features, benefits, and use cases. We'll also provide a monitoring tools list and examples to help you choose the best solutions for your needs.

Transitioning from a monolithic system to a cloud-native microservices environment, Ritchie Bros. sought to modernize their observability infrastructure to support the transition and fuel future growth. Ritchie Bros. has been a pioneering force in the auctioneering market for nearly 70 years, charting remarkable growth through a strategic mix of organic expansion and acquisitions.

In the ever-evolving IT landscape, the Observability Dilemma casts a strategic shadow: To SaaS or not to SaaS, a question being dealt with by many IT professionals today. As organizations grapple with the complexities of maintaining system health and performance, navigating change while staying secure, choosing between the allure of cloud-based services and the on-premises sanctuary becomes pivotal.

Modern Applications can use a lot of external services, some of those interactions are expected, others not so much. There could be many reasons for those unexpected interactions, ranging from security vulnerabilities and various malware to outdated code and various reporting and statistics software may report to its creator or a third party. These unexpected interactions can be a security risk, and may also raise privacy concerns.

Every Python developer has heard about the GIL (Global Interpreter Lock) This lock simplifies memory management and ensures thread safety, but it also limits the performance of multi-threaded, CPU-bound programs because threads can’t run Python code in parallel. Here is a great explanation of why Python requires the GIL by Python’s creator, Guido van Rossum: Guido van Rossum: Will Python ever remove the GIL? | Lex Fridman Podcast Clips.

The business of observability is all about data: what you’re observing in the data, how you’re visualizing it, what it indicates about the state of your environment, and how to address issues that may occur. Creating your own perspective for observability, and understanding what you’re seeing, can be difficult.

Getting the right people working in the CoPE is crucial to success because these change agents must limber up the organization and promote the flexibility necessary to perform resilience. We’ll look for teammates who share enough in common to work well together, but who don’t necessarily perfectly overlap so that they can play off each other’s strengths.

Two years ago, we shared our experiences with adopting AWS Graviton3 and our enthusiasm for the future of AWS Graviton and Arm. Once again, we're privileged to share our experiences as a launch customer of the Amazon EC2 R8g instances powered by AWS Graviton4, the newest generation of AWS Graviton processors. This blog elaborates our Graviton4 preview results including detailed performance data. We've since scaled up our Graviton4 tests with no visible impact to our customers.

Reliability testing and observability are similar in one important way: engineering teams know they should be doing it, but they’re not sure how to start, or they don’t have the right resources, or they need to focus on competing priorities like feature development and incident response. In an ideal world, reliability and observability would be automated processes that configure, monitor, and run themselves.