Operations | Monitoring | ITSM | DevOps | Cloud

With the increasing list of databases — SQL and NoSQL, each with its own strengths and use cases — it’s essential to understand how these systems differ and which one is right for your specific requirements. In this article, we’ll break down their features, advantages, and real-world use cases, helping you make the best choice for your project.

Microsoft SQL Server is a critical database component of many business applications, ensuring data integrity, fast query performance, and seamless transactions. However, maintaining peak performance requires proactive monitoring of essential metrics. In this blog, we’ll explore the key SQL Server performance metrics you should track and how they help prevent performance issues, optimize resource usage, and enhance database efficiency.

In the log aggregation game, the biggest difficulty you face can be setting up parsing rules for your logs. To qualify this statement: simply getting log files into Graylog is easy. Graylog also has out-of-the-box parsing of a wide variety of common log sources, so if your logs fall into one of the many categories of log for which there is either a dedicated Input; a dedicated Illuminate component; or that uses a defined Syslog format; then yes, parsing logs is also easy.

Logstash is a powerful tool for ingesting, transforming, and shipping data from various sources. Visibility into Logstash is critical for optimizing performance and troubleshooting issues related to data ingestion. We’ve greatly improved the Logstash integration to display the status of your Logstash nodes and pipelines at a glance. The integration is now powered by Elastic Agent, which queries Logstash monitoring APIs for data that populates managed dashboards.

Over the past two years, artificial intelligence (AI) has experienced remarkable growth, significantly influencing various sectors and daily life. In 2023, the release of advanced large language models (LLMs), such as OpenAI’s GPT-4 and Google DeepMind’s Gemini, marked a pivotal shift by enabling AI systems to process and generate diverse data types, including text, images, and audio.

Government compliance regulations are becoming more complex every year. For businesses, staying compliant means balancing a growing list of laws and policies while facing tighter budgets, limited resources, and increasing scrutiny. Failing to comply isn’t just risky—it can result in hefty fines, reputational damage, and operational inefficiencies. This is where automation can be a game-changer.

2024 was a huge year for Apache DataFusion, and 2025 is looking to be even bigger. The project officially became a top-level Apache Software Foundation project, achieved best-in-class performance for querying Parquet files in the ClickBench benchmark, and had a research paper accepted for SIGMOD.

Who doesn’t love a virtual try-on when shopping online or a quick scan in the physical store that tells exactly when their favorite item will be available in the store? These everyday conveniences, powered by AI, once seemed like science fiction. Traditional AI has already revolutionized retail - from computer vision managing inventory to machine learning predicting demand.

In today’s digital-first world, IT teams rely on a vast array of tools to monitor, manage, and optimize infrastructure. Network monitoring tools, security platforms, IT service management (ITSM) solutions, and observability stacks provide real-time insights into digital environments’ health and performance. But there’s a catch—most of these tools stop at alerting.

Grafana’s extensibility has always been one of the keys to its success. It comes with a wide range of data sources that allow you to query your data no matter where it lives, visualizations to help you quickly make sense of that data, and apps that can provide complete observability solutions, all in a single package.