Operations | Monitoring | ITSM | DevOps | Cloud

Software testing is a rapidly evolving landscape where automation has replaced traditional manual practices significantly in recent years. Artificial intelligence (AI) and machine learning (ML) advancements introduced a groundbreaking approach to software testing known as autonomous testing. This article aims to provide a comprehensive guide on autonomous testing tools, highlighting their benefits, and the top tools available.

Asaf and I founded Logz.io in 2015 to provide developers with the ultimate open source log management experience. With our product, logging with the ELK Stack was simple, efficient, and automated for the first time – so customers could save engineering costs and accelerate MTTR.

In this post I will introduce sysgrok, a research prototype in which we are investigating how large language models (LLMs), like OpenAI's GPT models, can be applied to problems in the domains of performance optimization, root cause analysis, and systems engineering. You can find it on GitHub.

By storing copies of your content in geographically distributed servers, content delivery networks (CDNs) enable you to extend the reach of your app without sacrificing performance. CDNs lessen the demand on individual web hosts by increasing the number and regional spread of servers that are able to respond to incoming requests for cached content. As a result, they can deliver web content faster and provide a better experience for your end users.

In my previous blog post, I discussed how transitioning from legacy monolithic applications to microservices based applications running on Kubernetes brings a range of benefits, but that it also increases the application’s attack surface. I zoomed in on creating security policies to harden the distributed microservice application, but another key challenge this transition brings is observing and monitoring the workload communication and known and unknown security gaps.

Looking to get started with log aggregation? Or perhaps take your logging game to a whole new, more advanced level? You’ve come to the right place. Grafana Loki is a key component of Grafana Labs’ open and composable Grafana LGTM stack (Loki for logs, Grafana for visualization, Tempo for traces, Mimir for metrics).

As our customers share their frustrations with the volume and growth of their observability data, we’ve got our eyes set on making it easier to manage. Our Spring 4.1 Launch involved enhancements to the Cribl suite of products — Cribl Stream, Cribl Edge, and Cribl Search — that give users more choice and control over their end-to-end observability architecture.

In a world where data is continuously growing, the need for integrated and centralized data is becoming increasingly important. Businesses are becoming more data-intensive, and by 2025, organizations need to leverage the power of their data to make informed decisions and stay competitive. Data integration plays a crucial role in enabling businesses to access, analyze and act on such data, with the data integration market expected to grow at a fast pace of a CAGR of 11.4% in 2027.