In my last blog post, I wrote about the explicit costs of incidents — the ones you can easily track based on dollars lost. But the cost of incidents goes beyond the time spent resolving them. While we’re spending our time managing incidents (that includes mitigating and retrospectives), we’re incurring a large opportunity cost in terms of releasing the next big thing.
Splunk has become one of several players in the observability industry, offering a set of features and a specific focus on legacy and security use cases. That being said, how does Splunk compare to Coralogix as a complete full-stack observability solution? Let’s dive into the key differences between Coralogix vs Splunk, including customer support, pricing, cost optimization, and more.
Too often, we in IT get so busy performing the day-to-day work and fighting the many fires that come at us each day that we neglect to take a moment and focus on ways we can be strategic about how we do our jobs. When building or expanding IT Service Management offerings, it’s important to understand how taking time to focus on service strategy can greatly improve the efficiency of service delivery. First, let’s begin by defining a few terms.
User expectations — those of employees and customers alike — are turning up the heat for businesses and their IT departments. Could the demand for nonstop, fast, and basically flawless digital services be any higher?
When it comes to observability, your organization will have no shortage of options for tools and platforms. Between open source software and proprietary vendors, you should be able to find the right tools to fit your use case, budget and IT infrastructure. Observability should be cost-efficient, easy to implement and customers should be provided with the best support possible.
Vector search is a powerful tool in the information retrieval tool box. Using vectors alongside lexical search like BM25 is quickly becoming commonplace. But there are still a few pain points within vector search that need to be addressed. A major one is text embedding models and handling larger text input.
Our friends at Tracetest recently released an integration with Honeycomb that allows you to build end-to-end and integration tests, powered by your existing distributed traces. You only need to point Tracetest to your existing trace data source—in this case, Honeycomb. This guest post from Adnan Rahić walks you through how the integration works.
In recent years, the landscape of application development has experienced a paradigm shift, largely driven by the rise of containerization and microservices architectures. Amid this transformation, Express.js has emerged as a dynamic and versatile framework that stands as a one-stop shop for crafting robust web applications. Its popularity owes much to its minimalist approach, allowing developers to swiftly build APIs and web applications with ease.
