Operations | Monitoring | ITSM | DevOps | Cloud

Today we break down another exciting edition of Founders and Friends, the podcast we’ve created to hold conversations with visionary leaders shaping the tech industry. Today’s conversation features Paul Stovell, co-founder and CEO of Octopus Deploy, and of course, JD Trask, co-founder and CEO of Raygun. Together, they explore the realities of running software businesses, from the evolving nature of agile practices to scaling software teams efficiently. What’s in this article.

SQL Server integration services is a powerful data integration and workflow platform provided by Microsoft. It can be used to automate data extraction, transformation, and other ETL processes. You can use SSIS to export data from various data sources like flat files, database servers, spreadsheets, etc. Due to these capabilities, SQL Server integration services are widely used in building data warehousing, business intelligence, and database migration tasks.

Database migration involves transferring data, schemas, and other database objects from one database system to another. How can you migrate data from SQL Server to Oracle with minimal disruption and maximum efficiency? In this article, we will explore the key reasons why companies might choose to migrate from SQL Server to Oracle and how to tackle migration challenges. Also, we’ll provide step-by-step guides on how to execute this migration using the following tools.

Grafana is an open source platform for real-time data display and monitoring. One of its functions is the creation of interactive and customizable dashboards that make metric analysis from several sources, such as databases, monitoring systems and cloud platforms. Its flexibility and compatibility with multiple data providers make it an essential tool for observability and decision making in IT environments.

Traditional programming is built around well-defined inputs and deterministic logic. Developers write functions that take structured inputs, apply a predefined set of operations, and return a structured output. This model works well when the input space is predictable, but it struggles with problems where inputs are ambiguous, unstructured, or constantly evolving.

In today’s fast-paced digital landscape, businesses are moving their operations to the cloud more than ever before. This shift brings incredible benefits like scalability, flexibility, and cost-efficiency. While it does introduce various common cloud monitoring challenges, there are effective solutions that organizations can implement to ensure optimal performance, security, and cost control.

AI is now a go-to tool for everything from writing to coding. Modern LLMs are so powerful that, with the right prompt and a few adjustments, they can handle tasks almost effortlessly. At Coroot, we’ve been experimenting with AI for observability. Our goal is to make it useful in the final stage of troubleshooting—when we’ve already identified which service is causing issues, like Postgres, but finding the exact root cause is still tricky due to the many possible scenarios.

Google Cloud Platform (GCP) is a suite of cloud computing services that runs on the same infrastructure Google uses internally for its products, such as Google Search and YouTube. With a global network of data centers, GCP offers over 200 fully managed services spanning compute, storage, databases, AI/ML, analytics, networking, and more, enabling businesses to innovate and scale without heavy upfront infrastructure costs.

In this article, we’ll walk you through Obkio’s powerful Network Performance Monitoring features by exploring the “Network Performance” tab in Obkio’s Network Performance Monitoring App. We’ll guide you through the video demonstration and take a closer look at the “Network Performance” tab, which provides a comprehensive overview of your network’s health.

The relational database industry has changed a lot in 25 years. Find out how these changes have impacted the role of a DBA, and the industry as a whole, with Redgate Advocate Kellyn Gorman. Over the past 25 years, the relational database industry has experienced a dramatic transformation. With Oracle, SQL Server, MySQL, and PostgreSQL as foundational technologies, these databases have evolved in response to the emergence of big data, NoSQL, cloud computing, and, most recently, AI.