Are you interested in performing time series forecasting or anomaly detection, but you don’t know where to start? If so, you’re not alone. There is an overwhelming variety of libraries, algorithms, and workflow recommendations for these tasks. As a Developer Advocate at InfluxDB, the leading time series database, I’ve researched time series data science methodologies and best practices for forecasting and anomaly detection.
I’ve learned a lot about serverless in my first full year at Stackery after joining from the Ops-focused automation company, Puppet. I’ve learned how to deploy rich CMS-backed web applications in a serverless way, how to cast incantations using CloudFormation’s intrinsic functions, but most of all I’ve learned that there’s a lot to learn in order to be successful in AWS.
Mutual of Enumclaw, a 100-year-old insurance company from Washington, modernized their policy processing system in order to reduce TCO and focus on their software and customers - not infrastructure. However, they realized serverless development still presents many DevOps challenges like environments, workflows, documentation and local development.
If you've ever had to be on the receiving end of a monitoring system that uses email for alerts, you know how noisy things can get. Particularly if you're working in an agency or freelance-like environment, with dozens of client sites to maintain. You get so many emails that you start looking into integrations with third-party services like Zapier, and coming up with more and more complex rules to try reduce the noise.
During the next nine weeks, our team will work to improve the overall experience of Qovery. We gathered all your feedback (thank you to our wonderful community 🙏), and we decided to make significant changes to make Qovery a better place to deploy and manage your apps. This series will reveal all the changes and features you will get in the next major release of Qovery. Let's go!
When DevOps teams talk about monitoring a database, the primary motivation is to ensure that the database won’t suffer a performance hiccup. Long queries, timeouts and table scans are among the most popular causes behind lousy customer experience. However, in recent years, more data has been shifted to cloud databases.
In an expanded and commercial industry space new and innovative opportunities are presented to retail organizations from several novel sources of data, log files, and from transaction information to sensor data to achieve unmatched value and combative advantage in their respective fields. In order to attain customer satisfaction and to flourish their business, people across the organization must be empowered, so that swift and accurate decisions can be attained.
Five worthy reads is a regular column on five noteworthy items we discovered while researching trending and timeless topics. In this week’s edition, let’s explore how quantum computing works and how it impacts cybersecurity.
Troubleshooting issues in your applications can be a complicated task requiring visibility into various components. In the worst-case scenario, to understand what is happening and why it is happening you will need metrics, logs, and traces combined together. Having that information will give you the possibility to slice and dice the data and get to the root cause efficiently. In this article, we will focus on logs and how to configure logging for your Java applications.
