Apache Kafka, born at LinkedIn in 2010, has revolutionized real-time data streaming and has become a staple in many enterprise architectures. As it facilitates seamless processing of vast data volumes in distributed ecosystems, the importance of visibility into its operations has risen substantially. In this blog, we’re setting our sights on the step-by-step deployment of a containerized Kafka cluster, accompanied by a Python application to validate its functionality. The cherry on top?

Ever since its release in September 2014, Kubernetes has been equally powerful and meme-able in the engineering world. For all the magic of its container orchestration and compute resource management, it’s also mysterious and, to many, confounding — especially when it comes time to pay for it. As we’ve written before, migrating to Kubernetes often means losing cost visibility.

We recently moved our infrastructure fully into Google Cloud. Most things went very smoothly, but there was one issue we came across last week that just wouldn’t stop cropping up. What follows is a tale of rabbit holes, red herrings, table flips and (eventually) a very satisfying smoking gun. Grab a cuppa, and strap in. Our journey starts, fittingly, with an incident getting declared... 💥🚨

We explain why you should connect the leading two cloud providers, the options available, and which one is right for your business.

Success in the cloud continues to be elusive for many organizations. A recent Forbes article describes how financial services firms are struggling to succeed in the cloud, citing Accenture Research that found that only 40% of banks and less than half of insurers fully achieved their expected outcomes from migrating to cloud. Similarly, a 2022 KPMG Technology Survey found that 67% of organizations said they had failed to receive a return on investment in the cloud.

Google Cloud Operations, formerly known as Stackdriver, is relatively new to the observability space. That being said, its position in the GCP ecosystem makes the platform a serious contender. Let’s explore some of the key ways in which Google Cloud Operations differs from Coralogix, a strong full-stack observability platform and leader in providing in-stream log analysis for logs, metrics, tracing and security data.

As technology advances and business environments become increasingly competitive, your DevOps team has to continuously improve your product. The challenge is to free up their time so that they can release new product features and improve existing ones. Automating repetitive tasks is one way to accomplish this. Manual approaches also tend to generate or miss errors, slow time to market, and fail to test and monitor system health quickly enough.

SharePoint is a Microsoft-owned platform that provides an extensive range of solutions for content management and collaboration within and outside an organization. Built on a web-based technology stack, it integrates seamlessly with Microsoft Office 365 and offers features like document libraries, team sites, intranets, extranets, and advanced search functionalities. It can be deployed both on-premises or in the cloud.

Azure Database is a comprehensive cloud-based service Microsoft offers as part of its Azure cloud computing platform. It provides various database solutions to cater to different application needs, offering scalability, reliability, and performance. Here’s a quick look at Azure Database: Database Types: Azure Database supports various databases, including SQL databases, NoSQL databases, and data warehousing solutions.

You’re a savvy SaaS business leader, so you already know the importance of keeping costs low to maximize your margins. What you might not have considered, however, is how tracking unit cost in your cloud spend data can help you achieve optimizations far beyond what you’d get with traditional cost-cutting methods. Keep reading to learn how cloud spend unit costs can drive savings you never knew were possible.