The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.
Public cloud environments are heavily instrumented and can give you metrics on practically any level of the infrastructure. AWS is no exception. Metrics are not only useful for monitoring and troubleshooting issues in a cloud environment - they can also be tied directly to automated actions. So you can leverage them to remediate issues instantly, as they happen.
High availability and flawless performance of business applications are vital to maintaining a company’s online reputation and keeping its customers satisfied. If a business-critical application crashes, frustrated users may abandon the service, leading to a loss in brand value and revenue. Internal business application performance issues can also cause a drop in employee productivity. To prevent these performance issues, enterprises turn to application performance monitoring solutions.
In a previous blog post, we built a small Python application that queries Elasticsearch using a mix of vector search and BM25 to help find the most relevant results in a proprietary data set. The top hit is then passed to OpenAI, which answers the question for us. In this blog, we will instrument a Python application that uses OpenAI and analyze its performance, as well as the cost to run the application.
When people hear the word “migration,” they typically think about migrating from on-prem to the cloud. In reality, companies do migrations of varying types and sizes all the time. However, many teams delay making critical migrations or technical upgrades because they don’t have the proper tools and frameworks to de-risk the process.
